Image processing and Retrieval Trends

Mobile Visual Search (MVS)

2012-01-26T17:02:00.001+02:00

An amazing presentation by Oge Marques!!!!

Watch the (full length !!! ) video here: http://www.foerderverein-technische-fakultaet.at/2012/01/ruckblick-mobile-visual-search-video-slides/

Abstract

Mobile Visual Search (MVS) is a fascinating research field with many open challenges and opportunities which have the potential to impact the way we organize, annotate, and retrieve visual data (images and videos) using mobile devices. This talk is structured in four parts:

(i) MVS — opportunities: where I present recent and relevant numbers of the mobile computing market, particularly in the field of photography apps, social networks, and mobile search.

(ii) Basic concepts: where I explain the basic MVS pipeline and discuss the three main MVS scenarios and associated challenges.

(iii) Advanced technical details: where I explain technical aspects of feature extraction, indexing, descriptor matching, and geometric verification, discuss the state of the art in these fields, and comment on open problems and research opportunities.

(iv) Examples and applications: where I show recent and significant examples of academic research (e.g., Stanford Product Search System) and commercial apps (e.g., Google Goggles, oMoby, kooaba) in this field.

Great stuff professor Marques, thanks for sharing

ΠΡΟΣΚΛΗΣΗ ΕΚΔΗΛΩΣΗΣ ΕΝΔΙΑΦΕΡΟΝΤΟΣ ΓΙΑ ΤΗΝ ΕΚΠΟΝΗΣΗ ΔΙΔΑΚΤΟΡΙΚΗΣ ΔΙΑΤΡΙΒΗΣ

2012-01-25T13:00:00.001+02:00

Στα πλαίσια του ερευνητικού προγράμματος ΘΑΛΗΣ, η Ομάδα Επεξεργασίας Εικόνας και Πολυμέσων (http://ipml.ee.duth.gr/) του Τμήματος Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών του Δημοκριτείου Πανεπιστημίου Θράκης, θα διερευνήσει νέες μεθοδολογίες για την αποτελεσματική ανάκτηση τριδιάστατων (3Δ) αντικειμένων (στατικών και 3Δ βίντεο).

Σε αυτό το πρόγραμμα υπάρχουν δύο (2) χρηματοδοτούμενες θέσεις για εκπόνηση διδακτορικών διατριβών.

Οι θέσεις είναι άμεσα διαθέσιμες. Παρόλη την άμεση διαθεσιμότητα, ενθαρρύνονται να εκδηλώσουν το ενδιαφέρον τους υποψήφιοι οι οποίοι διαθέτουν τα απαιτούμενα προσόντα και θα έχουν ολοκληρώσει τις βασικές ή μεταπτυχιακές σπουδές τους μέχρι τον ερχόμενο Σεπτέμβρη.

Είναι επιθυμητό οι υποψήφιοι να έχουν υπόβαθρο σε τουλάχιστον κάποιο από τα θέματα που αφορούν σε Γραφικά, Επεξεργασία Εικόνας και Αναγνώριση Προτύπων καθώς και να έχουν επαρκή εμπειρία στον προγραμματισμό είτε σε περιβάλλον Matlab είτε σε οποιοδήποτε άλλο περιβάλλον προγραμματισμού C/C++/C#.

Οι υποψήφιοι που θα επιλεγούν θα δουλέψουν σε ένα δυναμικό περιβάλλον και θα συνεργασθούν με ερευνητές ιδρυμάτων του εσωτερικού (Εθνικό Καποδιστριακό Πανεπιστήμιο Αθηνών – Τμήμα Πληροφορικής, Ε.Κ. «ΑΘΗΝΑ» – Ινστιτούτο Πολιτιστικής και Εκπαιδευτικής Τεχνολογίας, ΕΚΕΦΕ «ΔΗΜΟΚΡΙΤΟΣ» - Ινστιτούτο Πληροφορικής και Τηλεπικοινωνιών) καθώς και με ερευνητές ιδρυμάτων του εξωτερικού (University of Houston – USA, Vrije Universiteit Brussel – Belgium, Utrecht University - Netherlands, Consiglio Nazionale delle Ricerche - Italy).

The faster-than-fast Fourier transform

2012-01-20T09:02:00.001+02:00

Article from MITNews

For a large range of practically useful cases, MIT researchers find a way to increase the speed of one of the most important algorithms in the information sciences.

The Fourier transform is one of the most fundamental concepts in the information sciences. It’s a method for representing an irregular signal — such as the voltage fluctuations in the wire that connects an MP3 player to a loudspeaker — as a combination of pure frequencies. It’s universal in signal processing, but it can also be used to compress image and audio files, solve differential equations and price stock options, among other things.
The reason the Fourier transform is so prevalent is an algorithm called the fast Fourier transform (FFT), devised in the mid-1960s, which made it practical to calculate Fourier transforms on the fly. Ever since the FFT was proposed, however, people have wondered whether an even faster algorithm could be found.
At the Association for Computing Machinery’s Symposium on Discrete Algorithms (SODA) this week, a group of MIT researchers will present a new algorithm that, in a large range of practically important cases, improves on the fast Fourier transform. Under some circumstances, the improvement can be dramatic — a tenfold increase in speed. The new algorithm could be particularly useful for image compression, enabling, say, smartphones to wirelessly transmit large video files without draining their batteries or consuming their monthly bandwidth allotments.
Like the FFT, the new algorithm works on digital signals. A digital signal is just a series of numbers — discrete samples of an analog signal, such as the sound of a musical instrument. The FFT takes a digital signal containing a certain number of samples and expresses it as the weighted sum of an equivalent number of frequencies.
“Weighted” means that some of those frequencies count more toward the total than others. Indeed, many of the frequencies may have such low weights that they can be safely disregarded. That’s why the Fourier transform is useful for compression. An eight-by-eight block of pixels can be thought of as a 64-sample signal, and thus as the sum of 64 different frequencies. But as the researchers point out in their new paper, empirical studies show that on average, 57 of those frequencies can be discarded with minimal loss of image quality.

Heavyweight division
Signals whose Fourier transforms include a relatively small number of heavily weighted frequencies are called “sparse.” The new algorithm determines the weights of a signal’s most heavily weighted frequencies; the sparser the signal, the greater the speedup the algorithm provides. Indeed, if the signal is sparse enough, the algorithm can simply sample it randomly rather than reading it in its entirety.
“In nature, most of the normal signals are sparse,” says Dina Katabi, one of the developers of the new algorithm. Consider, for instance, a recording of a piece of chamber music: The composite signal consists of only a few instruments each playing only one note at a time. A recording, on the other hand, of all possible instruments each playing all possible notes at once wouldn’t be sparse — but neither would it be a signal that anyone cares about.
The new algorithm — which associate professor Katabi and professor Piotr Indyk, both of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), developed together with their students Eric Price and Haitham Hassanieh — relies on two key ideas. The first is to divide a signal into narrower slices of bandwidth, sized so that a slice will generally contain only one frequency with a heavy weight.
In signal processing, the basic tool for isolating particular frequencies is a filter. But filters tend to have blurry boundaries: One range of frequencies will pass through the filter more or less intact; frequencies just outside that range will be somewhat attenuated; frequencies outside that range will be attenuated still more; and so on, until you reach the frequencies that are filtered out almost perfectly.
If it so happens that the one frequency with a heavy weight is at the edge of the filter, however, it could end up so attenuated that it can’t be identified. So the researchers’ first contribution was to find a computationally efficient way to combine filters so that they overlap, ensuring that no frequencies inside the target range will be unduly attenuated, but that the boundaries between slices of spectrum are still fairly sharp.

Article from MITNews

WIAMIS 2012: The 13th International Workshop on Image Analysis for Multimedia Interactive Services 23rd - 25th May 2012, Dublin City University, Ireland

2012-01-17T18:25:00.001+02:00

The International Workshop on Image Analysis for Multimedia Interactive Services is one of the main international events for the presentation and discussion of the latest technological advances in interactive multimedia services. The objective of the workshop is to bring together researchers and developers from academia and industry working in the areas of image, video and audio applications, with a special focus on analysis. After a series of successful meetings starting in 1997 in Louvain, WIAMIS 2012 will be held in Dublin City University, Ireland.

All accepted and registered papers will be published in the workshop proceedings which will be indexed and distributed by IEEExplore.

Topics of interest include, but are not limited to:

3D data processing and visualization;
Multimedia content analysis and understanding;
Content-based browsing, indexing and retrieval of images, video and audio;
Content-based copy detection;
Emotional based content classification and organization;
2D/3D feature extraction;
Advanced descriptors and similarity metrics for multimedia;
Segmentation and reconstruction of objects in 2D/3D image sequences;
Motion analysis and tracking;
Multi-modal analysis for event recognition;
Analysis for coding efficiency and increased error resilience;
Analysis and tools for content adaptation;
Content summarization and personalization strategies;
End-to-end quality of service support;
Multimedia analysis for new and emerging applications;
Multimedia analysis hardware and middleware;
Semantic web and social networks;
Advanced interfaces for content analysis and relevance feedback;
Video/audio-based human behavior analysis;
Advanced multimedia applications.

Proposal for Special Session: 9th Dec, 2011

Notification of Special Session Proposal Acceptance:23rd Dec, 2011

Paper Submission: 3rd Feb, 2012

Notification of Acceptance: 30th March, 2012

Camera-ready Papers: 13th April, 2012

http://wiamis.dcu.ie/

3D Photo Ring HD Update v2.3

2012-01-13T11:43:00.001+02:00

3D Photo Ring is an iOS app that shows your photos in an interactive three-dimensional arrangement including a color sorting feature. The app also provides an interactive slideshow and can display EXIF meta-data.

Now, a new update has been released, which integrates lots of improvements:

Autorotate support
Pinch for zooming
Color sorting significantly improved
Loading of photos more than 2 times faster
Aspect ratio problems fixed
Switching photos (fullscreen mode) by device tilt
Sensibility of rotation speed configurable in settings
Persistent storage of settings
Automatic rotation of ring on demand
Automatic check for changes in photo library on startup
Several bugfixes

The iPad version of the app (3D Photo Ring HD) is currently available at half the price.

More information here: http://vidoTouch.com/

US Moves Toward Banning Photoshop In Cosmetics Ads

2012-01-12T09:14:00.001+02:00

Article from Business Insider

Procter & Gamble has agreed to never again run an ad for its CoverGirl mascara because it used "enhanced post-production" and "photoshopping" to make eyelashes look thicker than they were in real life. P&G agreed to the ban even though it disclosed in the ad that the image was enhanced.

The move is the latest in a series of baby steps that U.S. and international advertising regulators have taken to ban the use of Photoshop in advertising when it is misleading to consumers.

The company's decision was described in a ruling by the National Advertising Division, the U.S. industry watchdog that imposes self-regulation on the advertising business. NAD is part of the Council of Better Business Bureaus. Its rulings are respected and followed by most advertisers because it enjoys a close relationship with the FTC, from which it has historically drawn some of its senior staff. Recalcitrant advertisers who refuse to withdraw or amend misleading ads are referred by the NAD to the FTC, which has the power to fine, sue or bring injunctions against companies.

When asked whether this was a de facto ban on Photoshop, NAD director Andrea Levine told us:

"You can’t use a photograph to demonstrate how a cosmetic will look after it is applied to a woman’s face and then – in the mice type – have a disclosure that says ‘okay, not really.’”

The ad in question was for CoverGirl NatureLuxe Mousse Mascara, which promised “2X more volume” on women's lashes. After reviewing the ad, P&G agreed to yank it. (A different CoverGirl ad is shown here.) The NAD ruling said:

"… [P&G] advised NAD it has permanently discontinued all of the challenged claims and the photograph in its advertisement. NAD was particularly troubled by the photograph of the model – which serves clearly to demonstrate (i.e., let consumers see for themselves) the length and volume they can achieve when they apply the advertised mascara to their eyelashes. This picture is accompanied by a disclosure that the model’s eyelashes had been enhanced post production."

In a footnote, the NAD said it was following the lead of its sister body in the U.K., the Advertising Standards Authority, which in July banned cosmetics ads featuring Julia Roberts and Christy Turlington because they used Photoshop. The NAD said:

"Advertising self-regulatory authorities recognize the need to avoid photoshopping in cosmetics advertisements where there is a clear exaggeration of potential product benefits."

"... the picture of Ms. Roberts had been altered using post production techniques (in addition to professional styling, make-up, photography and the product’s inherent covering and smoothing nature which are to be expected), exaggerating what consumers could expect to achieve through product use."

The U.K. ruling found the use of photo retouching misleading per se.
In the U.S., the FTC has has also tightened rules to hold celebrities accountable if they make claims in ads they know cannot be true.

And in France, in 2009, 50 politicians asked for health warnings to be imposed on fashion ads if they showed retouched models' bodies.

Article from Business Insider

MMM2012

2012-01-12T09:11:00.001+02:00

Congratulation to the Klagenfurt team for the organization! Fantastic job.

More Pictures From the Event

Image retrieval, Research Assistant (19 months)

2011-12-26T21:30:00.001+02:00

This post offers the opportunity to work on an UK Engineering and Physical Sciences Research Council and a Technology Strategy Board funded project PhotoBrief. The project will create a platform to create briefs which specify the need for images as well as the ability to find a suitable
image and negotiate for it. It will provide users with an environment for interactive brief creation and dynamic negotation of images. The project considers the image information seeking and retrieval behaviour of different user groups including professionals. Partners from industry
include an SEO (search engine optimisation) company, a mobile information company, and a media advertising company.

The project is based within the Centre for Interactive Systems Research which has 20 years experience of R&D in search algorithms and technologies, including a well-known search algorithm.

Applicants should be qualified in Information Retrieval (or related area). More specifically, knowledge of meta-data creation, text/image retrieval/ content-based techniques will be needed. The qualification sought is PhD or equivalent experience in field.

In this post you will develop novel brief creation and negotiation techniques that use meta-data about images, which has been captured to enable that image to be more findable. You will implement and integrate these in an image retrieval system. The project will make use of current
state-of-art meta-data techniques, collections, relevant open-source initiatives, and evaluation methods. You will be involved in integrating these, creating user interfaces, and developing new system functionality where necessary.

Strong programming skills are essential, and experience of any of the following areas is an advantage: Information Retrieval (IR); User-centred IR system design, implementation, and evaluation; Context learning, Adaptive IR, Recommender systems, Social media; Computer Supported Cooperative Working (CSCW); User Interface design and evaluation. Experience in collaborating with partners from industry is desirable.

For informal enquiries, please contact Dr. Ayse Goker:
ayse.goker.1@soi.city.ac.uk
Further details of the position available at:
http://tinyurl.com/bpevd9y

The post will also be advertised on www.jobs.ac.uk

Closing date: 23 January, 2011
Interview date: 1 February, 2011
Start date: March 2011

Further information:
www.soi.city.ac.uk/is/research/cisr
www.soi.city.ac.uk/~sbbb872

Merry Christmas and a happy 2012

2011-12-24T02:23:00.001+02:00

Personalize funny videos and birthday eCards at JibJab!

2011 PhD Challenge Winner - "Dirty Old Man"

2011-12-22T11:06:00.001+02:00

The goal of this year’s challenge was to get one of the nicknames “DIRTY OLD MAN” or “CRAZY CAT LADY”included in the byline for at least one author of a final, camera-ready version of a peer-reviewed academic paper

And the winner is:

Coherence Progress: A Measure of Interestingness Based on Fixed Compressors

By Tom Schaul, IDSIA/TU Munich
In Proceedings of the Conference on Artificial General Intelligence (August 2011)

Ετήσιο Βραβείο Καλύτερης Διδακτορικής Διατριβής του Ινστιτούτου Πληροφορικής και Τηλεματικής

2011-12-22T10:25:00.001+02:00

Το Ινστιτούτο Πληροφορικής και Τηλεματικής (ΙΠΤΗΛ) προκηρύσσει και φέτος το Ετήσιο Βραβείο Καλύτερης Διδακτορικής Διατριβής το οποίο έχει απονεμηθεί από Ελληνικό Πανεπιστήμιο στον ευρύτερο τομέα της Πληροφορικής-Τηλεματικής κατά την διάρκεια του προηγούμενου ημερολογιακού έτους.

Οι όροι του διαγωνισμού είναι οι ακόλουθοι:

Ο διδακτορικός τίτλος θα πρέπει να έχει απονεμηθεί από Ελληνικό Πανεπιστήμιο μέσα στο 2011.

Η διδακτορική διατριβή μπορεί να είναι γραμμένη είτε στα Ελληνικά είτε στα Αγγλικά.

Η διδακτορική διατριβή θα πρέπει να αναφέρεται σε ένα από τα θέματα στα οποία δραστηριοποιείται ερευνητικά το ΙΠΤΗΛ:

Επεξεργασία εικόνας
Όραση υπολογιστών
Αναγνώριση προτύπων
Επεξεργασία σήματος
Τεχνητή νοημοσύνη
Πολυμέσα
Εικονική και επαυξημένη πραγματικότητα
Δίκτυα και επικοινωνίες

Η υποβολή της διδακτορικής διατριβής θα γίνεται ηλεκτρονικά. Μαζί θα πρέπει να υποβάλλεται βεβαίωση από την γραμματεία της σχολής ότι ο διδακτορικός τίτλος απονεμήθηκε μέσα στο έτος που αναφέρει η προκήρυξη, καθώς και τα ονόματα και οι ηλεκτρονικές διευθύνσεις της Τριμελούς Επιτροπής.

Η επιτροπή κρίσης θα αποτελείται από Ερευνητές του ΙΠΤΗΛ.

Το βραβείο θα απονέμεται κατά την Ανοιχτή Ημέρα του ΙΠΤΗΛ και θα αποτελείται από βεβαίωση και χρηματικό ποσό 600 ευρώ. Το ΙΠΤΗΛ θα καλύπτει τα έξοδα μετακίνησης του νικητή, εντός Ελλάδας, για να παραστεί στην εκδήλωση και να παραλάβει το βραβείο προσωπικά. Το βραβευμένο διδακτορικό θα προβάλλεται από την ιστοσελίδα του ΙΠΤΗΛ καθώς και μέσω δελτίου τύπου.

Προθεσμία υποβολής υποψηφιοτήτων: 15 Ιανουαρίου 2012.

Υποβολή αιτήσεων μέσω της iστοσελίδας http://www.iti.gr/itiPHD

ClustTour By CERTH-ITI

2011-12-22T10:23:00.001+02:00

ClustTour is a better way to search, discover and browse interesting city areas, POIs and events. Whether you are planning a trip or just want to check out how a place looks like, ClustTour offers a large collection of photos, maps and descriptions. You may wonder, what's new in this? ClustTour is not based on "official" guides and "experts" but on how people like you capture what is interesting everyday.

Key Features:
* Explore over 30 cities with new cities added regularly.
* Browse and search in areas, spots, POIs and events views.
* See groups of photos, descriptions and where they are on the map.
* The map interactively groups spots for easier browsing. Zoom in and
out to see more or less.
* Search the Web with a single tap to learn more about the spot you browse.
* Mark your favorites for easy review and sharing.
* Enjoy the most interesting spots in every city!

How it works:
ClustTour applies advanced analysis technologies to large-scale anonymous user contributions to discover the most interesting locations and events. These range from famous landmarks, such as the Thessaloniki's White Tower, to events and activities like music concerts, shopping, bookcrossing and partying but also off-the-beaten-path spots, from hidden eateries to local artists collections. Every city area, POI and event is connected to informative photo groups, descriptions and search options when you want to learn more.
Everything in ClustTour is automatic. And when we say everything we mean everything! There is no human intervention in selecting areas, spots, events and photos. Well-tuned algorithms select what is most interesting based on people contributions. This way, sometimes, we might miss well-known landmarks (in any case you know where to find these) and some of the spots do not fully make sense but this way we find the hidden gems and we are sure that what ClustTour offers is what people and not what officials and experts think!

http://itunes.apple.com/app/clusttour/id487608260?mt=8

IBM Next 5 in 5: 2011

2011-12-21T10:31:00.001+02:00

IBM unveils its sixth annual "Next 5 in 5" -- a list of innovations with the potential to change the way people work, live and play over the next five years. The Next 5 in 5 is based on market and societal trends expected to transform our lives, as well as emerging technologies from IBM's Labs around the world that can make these innovations possible.

In this installment: you will be able to power your home with the energy you create yourself; you will never need a password again; mind reading is no longer science fiction; the digital divide will cease to exist; and junk mail will become priority mail.

Vision Algorithm to Automatically Parse Addresses in Google Street View

2011-12-20T16:20:00.001+02:00

Reprinted from http://www.popsci.com/technology/article/2011-12/google-wants-computer-vision-algorithms-can-read-addresses-street-view?utm_medium=referral&utm_source=pulsenews

Extracting Door Numbers Building numbers come in a huge variety of shapes, colors and sizes, making them difficult to model for machine vision. Netzer et al

Extrapolating numbers and letters from digital images is still a tough task, even for the best computer programmers. But it would be handy to extract business names, or graffiti, or an address from pictures that are already stored online. Aiming to make its Street View service even more accurate, Google would like to extract your house number from its own Street View photo cache.

Say what you will about Street View (and Helicopter View and Amazon View and etc.) — beyond the novelty factor, the images are full of potentially useful data. Using street numbers on the side of a house or business could make navigation programs more accurate, and help motorists or pedestrians find the right door by providing a preview on the Internet or a mobile device. But while handwriting algorithms are pretty advanced, software systems are still limited in their ability to extract information from images. Factors like blurring, lighting and other distortions can be a problem.

To improve matters, researchers at Google and Stanford devised a new feature-learning algorithm for a set of street numbers captured from a Street View database. They used 600,000 images from various countries and extracted the house numbers using a basic visual algorithm. Then the team used Amazon’s Mechanical Turk system to verify the arrangement of the numbers. The result was two sets of images: One with house number images as they appeared, and one with house numbers all resized to the same resolution.

Initially, traditional handcrafted visual learning algorithms didn’t work very well to extract the numbers. Next, the Google-Stanford team tried feature learning algorithms, which use various sets of parameters to learn recognition patterns. The new feature learning methods worked much better than the regular visual learning method: One of the algorithms (a K-means-based feature learning system) achieved 90 percent accuracy, compared to 98 percent for a human.

The system still needs improvement, but it could be useful for extracting number data from billions of images, the researchers say. Ultimately, this could make Street View a lot more accurate. Without a house-number-based view, an address in Street View is a default panorama, which might not actually be the address you want. Type in “30 Rockefeller Plaza,” for instance, and the first thing you see is a chocolatier next to the 30 Rock observation deck. You have to click and drag to see the NBC building.

“With the house number-based view angle, the user will be led to the desired address immediately, without any further interaction needed,” the paper authors explain.

Reprinted from http://www.popsci.com/technology/article/2011-12/google-wants-computer-vision-algorithms-can-read-addresses-street-view?utm_medium=referral&utm_source=pulsenews

ICMR 2012

2011-12-20T15:58:00.001+02:00

Effectively and efficiently retrieving information based on user needs is one of the most exciting areas in multimedia research. The Annual ACM International Conference on Multimedia Retrieval (ICMR) offers a great opportunity for exchanging leading-edge multimedia retrieval ideas among researchers, practitioners and other potential users of multimedia retrieval systems. This conference, puts together the long-lasting experience of former ACM CIVR and ACM MIR series, is set up to illuminate the state of the arts in multimedia (text, image, video and audio) retrieval.

ACM ICMR 2012 is soliciting original high quality papers addressing challenging issues in the broad field of multimedia retrieval. See the call-for-papers page for a detailed list of interested topics.

Paper Submission Deadline: January 15, 2012

http://www.icmr2012.org/

sFly: Search and Rescue of Victims in GPS-Denied Environments (no Vicon, no Laser, No GPS!)

2011-12-19T19:23:00.001+02:00

Final demo of the sFly European Project (2009-2011). This demo simulate a search and rescue in an outdoor GPS-denied factory environment. No laser, no GPS are used for navigation and mapping, but just a single camera and IMU onboard each vehicle. All the processing runs onboard, on a Core2Duo.
Three quadrocopters take off using visual SLAM, explore the environment, build a 3D map of it, and use it to localize themselves and potential victims by measuring the signal strengths of WiseNodes carried by each victim.

MPEG news: a report from the 98th meeting, Geneva, Switzerland

2011-12-19T17:03:00.001+02:00

Re-Print from http://multimediacommunication.blogspot.com/ (Author: Christian Timmerer)

MPEG news from its 98th meeting in Geneva, Switzerland with less than 140 characters and a lot of acronyms. The official press release is, as usual,here. As you can see from the press release, MPEG produced significant results, namely:

MPEG Dynamic Adaptive Streaming over HTTP (DASH) ratified
3D Video Coding: Evaluation of responses to Call for Proposals
MPEG royalty free video coding: Internet Video Coding (IVC) + Web Video Coding (WebVC)
High Efficiency Coding and Media Delivery in Heterogeneous Environments:MPEG-H comprising MMT, HEVC, 3DAC
Compact Descriptors for Visual Search (CDVS): Evaluation of responses to the Call for Proposals
Call for requirements: Multimedia Preservation Description Information (MPDI)
MPEG Augmented Reality (AR)

As you can see, a long list of achievements within a single meeting but let's dig inside. For each topic I've also tried to provide some research issues which I think are worth to investigate both inside and outside MPEG.

MPEG Dynamic Adaptive Streaming over HTTP (DASH): DASH=IS ✔

As the official press release states, the MPEG ratifies its draft standard for DASH and it comes better, the standard should become publicly available which I expect to happen somewhat early next year, approx. March 2012, or maybe earlier. I say "should" because there is no guarantee that this will actually happen but signs are good. In the meantime, feel free using our software to play around and we expect to update it to the latest version of the standard as soon as possible. Finally, IEEE Computer Society Computing Now has put together a theme on Video for the Universal Web featuring DASH.
Research issues: performance, bandwidth estimation, request scheduling (aka adaptation logic), and Quality of Service/Experience.

3D Video Coding: 3DVC=CfP eval ✔

MPEG evaluated more than 20 proposals submitted as a response to the call issued back in April 2011. The evaluation of the proposal comprised subjective quality assessments conducted by 13 highly qualified test laboratories distributed around the world and coordinated by the COST Action IC1003 QUALINET. The report of the subjective test results from the call for proposals on 3D video coding will be available by end of this week. MPEG documented the standardization tracks considered in 3DVC (i.e., compatible with MVC, AVC base-view, HEVC, ...) and agreed on a common software based on the best-performing proposals.
Research issues: encoding efficiency of 3D depth maps and compatibility for the various target formats (AVC, MVC, HEVC) as well as depth map estimation at the client side.

MPEG royalty free video coding: IVC vs. WebVC

In addition to the evaluation of the responses to the call for 3DVC, MPEG also evaluated the responses to the Internet Video Coding call. Based on the responses, MPEG decided to follow up with two approaches namely Internet Video Coding (IVC) and Web Video Coding (WebVC). The former - IVC - is based on MPEG-1 technology which is assumed to be royalty-free. However, it requires some performance boosts in order to make it ready for the Internet. MPEG's approach is a common platform called Internet video coding Test Model (ITM) which serves as the basis for further improvements. The latter - WebVC - is based on the AVC constrained baseline profile which performance is well-known and satisfactory but, unfortunately, it is not clear which patents of the AVC patent pool apply to this profile. Hence, a working draft (WD) of WebVC will be provided (also publicly available) in order to get patent statements from companies. The WD will be publicly available by December 19th.
Further information:

Research issues: coding efficiency with using only royalty free coding tools whereby the optimization is first towards royalties and then efficiency.

MPEG-H

A new star is born which is called MPEG-H referred to as "High Efficiency Coding and Media Delivery in Heterogeneous Environments" comprising three parts: Pt. 1 MMT, Pt. 2 HEVC, Pt. 3 3D Audio. There's a document called context and objective of MPEG-H but I can't find out whether it's public (I come back later on this).

Part 1: MMT (MPEG Media Transport) is progressing (slowly) but a next step should be definitely to check the relationship of MMT and DASH for which an Ad-hoc Group has been established (N12395), subscribe here, if interested.
Research issues: very general at the moment, what is the best delivery method (incl. formats) for future multimedia applications? Answer: It depends, ... ;-)
Part 2: HEVC (High-Efficiency Video Coding) made significant progress at the last meeting, in particular: only one entropy coder (note: AVC has two, CABAC and CAVLC which are supported in different profiles), 8 bit decoding (could be also 10 bit, probably done in some profiles), specific integer transform, stabilized and more complete high-level syntax and HRD description (i.e., reference picture buffering, tiles, slices, and wavefronts enabling parallel decoding process). Finally, a prototype has been demonstrated decoding HEVC in software on an iPad 2 at WVGA resolution and the 10min Big Buck Bunny sequence at SD resolution with avg. 800 kbit/s which clearly outperformed the corresponding AVC versions.
Research issues: well, coding efficiency, what else? The ultimative goal to have a performance gain of more than 50% compared to the predecessor which is AVC.

Part 3: 3D Audio Coding (3DAC) is in its early stages but there will be an event during San Jose meeting which will be announced here. As of now, use cases are provided (home theatre, personal TV, smartphone TV, multichannel TV) as well as candidate requirements and evaluation methods. One important aspect seems to be user experience for highly immersive audio (i.e., 22.2, 10.2, 5.1) including bitstream adaptation for low-bandwidth and low-complexity.
Research issues: sorry, I'm not really an audio guy but I assume it's coding efficiency, specifically for 22.2 channels ;-)

Compact Descriptors for Visual Search (CDVS)

For CDVS, responses to the call for proposals (from 10 companies/institutions) have been evaluated and a test model has been established based on the best performing proposals. The next steps include the improvement of the test model towards for inclusion in the MPEG-7 standard.
Research issues: descriptor efficiency for the intended application as well as precision on the information retrieval results.

Multimedia Preservation Description Information (MPDI)

The aim of this new work item is to provide "standard technology helping users to preserve digital multimedia that is used in many different domains, including cultural heritage, scientific research, engineering, education and training, entertainment, and fine arts for long-term across system, organizational, administrative and generational boundaries". It comes along with two public documents, the current requirements and a call for requirements which are due at the 100th MPEG meeting in April 2002.
Research issues: What and how to preserve digital multimedia information?

Augmented Reality (AR)

MPEG's newest project is on Augmented Reality (AR), starting with an application format for which a working draft exists. Furthermore, draft requirements and use cases are available. These three documents will be available on Dec 31st.
Research issues: N/A

Re-Print from http://multimediacommunication.blogspot.com/ (Author: Christian Timmerer)

Free Access to selected highly cited papers from IJPRAI

2011-12-17T22:33:00.001+02:00

World Scientific announce a free access to selected highly cited papers in the International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI). This is valid till 31 December 2011 so do take advantage of the access today!

Selected highly cited papers

ROBUST OBJECT TRACKING USING JOINT COLOR-TEXTURE HISTOGRAM
Abstract | Full Text - Free Access (PDF, 1673KB) | References - Free Access
INTELLIGENT SURVEILLANCE BASED ON NORMALITY ANALYSIS TO DETECT ABNORMAL BEHAVIORS
Abstract | Full Text - Free Access (PDF, 1820KB) | References - Free Access
FACIAL BIOMETRICS USING NONTENSOR PRODUCT WAVELET AND 2D DISCRIMINANT TECHNIQUES
Abstract | Full Text - Free Access (PDF, 885KB)) | References - Free Access
FACE DETECTION AND RECOGNITION USING MAXIMUM LIKELIHOOD CLASSIFIERS ON GABOR GRAPHS
Abstract | Full Text - Free Access (PDF, 1646KB) | References - Free Access
PRECISE EYE AND MOUTH LOCALIZATION
Abstract | Full Text - Free Access (PDF, 1692KB) | References - Free Access
ACCURATE IMAGE RETRIEVAL BASED ON COMPACT COMPOSITE DESCRIPTORS AND RELEVANCE FEEDBACK INFORMATION
Abstract | Full Text - Free Access (PDF, 2471KB) | References - Free Access

PLANT LEAF IDENTIFICATION BASED ON VOLUMETRIC FRACTAL DIMENSION
Abstract | Full Text - Free Access (PDF, 1495KB) | References - Free Access

GRAPH CLASSIFICATION BASED ON VECTOR SPACE EMBEDDING
Abstract | Full Text - Free Access (PDF, 2283KB) | References - Free Access
K-MEANS CLUSTERING FOR PROBLEMS WITH PERIODIC ATTRIBUTES
Abstract | Full Text - Free Access (PDF, 1214KB) | References - Free Access
CLASSIFICATION OF IMBALANCED DATA: A REVIEW
Abstract | Full Text - Free Access (PDF, 1232KB) | References - Free Access

ACRI 2012 Santorini Island, Greece, 24-27 September 2012

2011-12-17T22:29:00.001+02:00

Cellular automata (CA) present a very powerful approach to the study of spatio-temporal systems where complex phenomena build up out of many simple local interactions. They account often for real phenomena or solutions of problems, whose high complexity could unlikely be formalised in different contexts.

Furthermore parallelism and locality features of CA allow a straightforward and extremely easy parallelisation, therefore an immediate implementation on parallel computing resources. These characteristics of the CA research resulted in the formation of interdisciplinary research teams. These teams produce remarkable research results and attract scientists from different fields.

The main goal of the 10th edition of ACRI 2012 Conference (Cellular Automata for Research and Industry) is to offer both scientists and engineers in academies and industries an opportunity to express and discuss their views on current trends, challenges, and state-of-the art solutions to various problems in the fields of arts, biology, chemistry, communication, cultural heritage, ecology, economy, geology, engineering, medicine, physics, sociology, traffic control, etc.

Topics of either theoretical or applied interest about CA and CA-based models and systems include but are not limited to:

Algebraic properties and generalization
Complex systems
Computational complexity
Dynamical systems
Hardware circuits, architectures, systems and applications
Modeling of biological systems
Modeling of physical or chemical systems
Modeling of ecological and environmental systems
Image Processing and pattern recognition
Natural Computing Quantum Cellular Automata
Parallelism

This edition of the ACRI conference also hosts workshops on recent and important research topics on theory and applications of Cellular Automata like the following: Crowds and Cellular Automata (3rd edition), Asynchronicity and Traffic and Cellular Automata.

http://acri2012.duth.gr/

Terrain Surveillance Coverage using Cognitive Adaptive Optimization

2011-12-04T05:57:00.001+02:00

A centralized cognitive‐based adaptive methodology for optimal surveillance coverage using swarms of MAVs has been developed, mathematically analyzed and tested using extensive simulation experiments. The methodology has been successfully tested on a large variety of 2D and 3D non‐convex unknown environments. Moreover, the methodology has been applied using real‐data from the Birmensdorf test area and the ETHZ’s hospital area. A decentralized version of the methodology has been also proposed and evaluated for the 2D case.

Mathias Lux @ ACM MULTIMEDIA 2011

2011-11-30T21:57:00.001+02:00

Content based image retrieval with LIRe

You can also download the poster HERE

Google Scholar Citations Open To All

2011-11-17T10:35:00.001+02:00

Article from http://googlescholar.blogspot.com/2011/11/google-scholar-citations-open-to-all.html

A few months ago, we introduced a limited release of Google Scholar Citations, a simple way for authors to compute their citation metrics and track them over time. Today, we’re delighted to make this service available to everyone! Click here and follow the instructions to get started.
Here’s how it works. You can quickly identify which articles are yours, by selecting one or more groups of articles that are computed statistically. Then, we collect citations to your articles, graph them over time, and compute your citation metrics - the widely used h-index; the i-10 index, which is simply the number of articles with at least ten citations; and, of course, the total number of citations to your articles. Each metric is computed over all citations and also over citations in articles published in the last five years.
Your citation metrics will update automatically as we find new citations to your articles on the web. You can also set up automated updates for the list of your articles, or you can choose to review the suggested updates. And you can, of course, manually update your profile by adding missing articles, fixing bibliographic errors, and merging duplicate entries.
As one would expect, you can search for profiles of colleagues, co-authors, or other researchers using their name, affiliation, or areas of interest, e.g., researchers at US universities or researchers interested in genomics. You can add links to your co-authors, if they already have a profile, or you can invite them to create one.
You can also make your profile public, e.g., Alex Verstak, Anurag Acharya. If you choose to make your profile public, it can appear in Google Scholar search results when someone searches for your name, e.g., [alex verstak]. This will make it easier for your colleagues worldwide to follow your work.
We would like to thank the participants in the limited release of Scholar Citations for their detailed feedback. They were generous with their time and patient with an early version. Their feedback greatly helped us improve the service. The key challenge was to make profile maintenance as hands-free as possible for those of you who prefer the convenience of automated updates, while providing as much flexibility as possible for those who prefer to curate their profile themselves.
Here is hoping that Google Scholar Citations will help researchers everywhere view and track the worldwide influence of their own and their colleagues’ work.

ColorHug

2011-11-14T03:16:00.001+02:00

Face Recognition Makes the Leap From Sci-Fi

2011-11-14T03:06:00.001+02:00

Article from THE NEW YORK TIMES

FACIAL recognition technology is a staple of sci-fi thrillers like “Minority Report.”

But of bars in Chicago?

SceneTap, a new app for smart phones, uses cameras with facial detection software to scout bar scenes. Without identifying specific bar patrons, it posts information like the average age of a crowd and the ratio of men to women, helping bar-hoppers decide where to go. More than 50 bars in Chicago participate.

As SceneTap suggests, techniques like facial detection, which perceives human faces but does not identify specific individuals, and facial recognition, which does identify individuals, are poised to become the next big thing for personalized marketing and smart phones. That is great news for companies that want to tailor services to customers, and not so great news for people who cherish their privacy. The spread of such technology — essentially, the democratization of surveillance — may herald the end of anonymity.

And this technology is spreading. Immersive Labs, a company in Manhattan, has developed software for digital billboards using cameras to gauge the age range, sex and attention level of a passer-by. The smart signs, scheduled to roll out this month in Los Angeles, San Francisco and New York, deliver ads based on consumers’ demographics. In other words, the system is smart enough to display, say, a Gillette ad to a male passer-by rather than an ad for Tampax.

Those endeavors pale next to the photo-tagging suggestion tool introduced by Facebookthis year. When a person uploads photos to the site, the “Tag Suggestions” feature uses facial recognition to identify that user’s friends in those photos and automatically suggests name tags for them. It’s a neat trick that frees people from the cumbersome task of repeatedly typing the same friends’ names into their photo albums.

“Millions of people are using it to add hundreds of millions of tags,” says Simon Axten, a Facebook spokesman. Other well-known programs like Picasa, the photo editing software from Google, and third-party apps like PhotoTagger, from face.com, work similarly.

But facial recognition is proliferating so quickly that some regulators in the United States and Europe are playing catch-up. On the one hand, they say, the technology has great business potential. On the other, because facial recognition works by analyzing and storing people’s unique facial measurements, it also entails serious privacy risks.

Using off-the-shelf facial recognition software, researchers at Carnegie Mellon University were recently able to identify about a third of college students who had volunteered to be photographed for a study — just by comparing photos of those anonymous students to images publicly available on Facebook. By using other public information, the researchers also identified the interests and predicted partial Social Security numbers of some students.

“It’s a future where anonymity can no longer be taken for granted — even when we are in a public space surrounded by strangers,” says Alessandro Acquisti, an associate professorof information technology and public policy at Carnegie Mellon who directed the studies. If his team could so easily “infer sensitive personal information,” he says, marketers could someday use more invasive techniques to identify random people on the street along with, say, their credit scores.

Today, facial detection software, which can perceive human faces but not identify specific people, seems benign.

Some video chat sites are using software from face.com, an Israeli company, to make sure that participants are displaying their faces, not other body parts, says Gil Hirsch, the chief executive of face.com. The software also has retail uses, like virtually trying out eyeglasses at eyebuydirect.com, and entertainment applications, like moustachify.me, a site that adds a handle bar mustache to a face in a photo.

But privacy advocates worry about more intrusive situations.

Now, for example, advertising billboards that use facial detection might detect a young adult male and show him an ad for, say, Axe deodorant. Companies that make such software, like Immersive Labs, say their systems store no images or data about passers-by nor do they analyze their emotions.

But what if the next generation of mall billboards could analyze skin quality and then publicly display an ad for acne cream, or detect sadness and serve up an ad for antidepressants?

3D Photo Ring

2011-11-07T00:07:00.001+02:00

Is the default ‘Photos’ app on the iPhone too limiting, too boring and not convenient enough for your needs? Do you want to use a novel and amazing 3D interface for browsing, searching, and presenting your photos with the iPhone?

Photo Ring turns your iPhone into a convenient 3D photo browser with a stunning interface that enables you to keep track of hundreds of photos at a glance. Moreover, its color sorting technology allows you to save time on task and provides you with a 3D slideshow feature that allows for an automized presentation of your photos. Due to its innovative and natural 3D arrangement and powerful color-based organization feature, searching for photos on your iPhone and showing them to your friends becomes an exiting and fun task!

FEATURES:

Innovative and intuitive 3D browsing interface (zoomable 3D Ring)
Interactive 3D slideshow (animated 3D Wall; with pause/fast-forward/reverse feature)
Convenient interaction (e.g., kinetic ring rotation by wipe or tilt)
Sorting of photos by recording time
Sorting of photos by color
Inspection of EXIF/TIFF metadata of photos
Browsing of photos from different folders/events
Fullscreen photo mode with convenient switching function

PhotoRing is available for iPhone and iPad!

Important note (Nov 5, 2011): if your iPhone/iPad doesn’t run iOS 5 already, please wait until our next update (v2.2, available in a few days), which will fix a serious bug that only occurs for older iOS versions and prevents the app from loading your photos.

Screenshots

http://vidotouch.com/photo-ring

The 6th FTRA International Conference on Multimedia and Ubiquitous Engineering (MUE 2012)

2011-11-05T12:59:00.001+02:00

http://www.arcos.inf.uc3m.es/mue2012
Madrid, Spain, 10-13 July 2012
Papers due: January, 15, 2012
Notification: March, 15 2012
Camera ready: April, 15 2012
Conference dates: July, 10-13, 2012

The new multimedia standards (for example, MPEG-21) facilitate the seamless integration of multiple modalities into interoperable multimedia frameworks, transforming the way people work and interact with multimedia data. These key technologies and multimedia solutions interact and collaborate with each other in increasingly effective ways, contributing to the multimedia revolution and having a significant impact across a wide spectrum of consumer, business, healthcare, education, and governmental domains. Moreover, the emerging mobile computing and ubiquitous networking technologies enable users to access fully broadband mobile applications and new services anytime and everywhere. The continuous efforts have been dedicated to research and development in this wide area including wireless mobile networks, ad-hoc and sensor networks, smart user devices and advanced sensor devices, mobile and ubiquitous computing platforms, and new applications and services including location-based, context-aware, or social networking services.
This conference provides an opportunity for academic and industry professionals to discuss recent progress in the area of multimedia and ubiquitous environment including models and systems, new directions, novel applications associated with the utilization and acceptance of ubiquitous computing devices and systems. MUE 2012 is the next event in a series of highly successful the International Conference on Multimedia and Ubiquitous Engineering MUE-11 (Loutraki, Greece, June 2011), MUE-10 (Cebu, Philippines, August 2010), MUE-09 (Qingdao, China, June 2009), MUE-08 (Busan, Korea, April 2008), and MUE-07 (Seoul, Korea, April 2007).

Topics of interest
* Ubiquitous Computing and Technology
* Context-Aware Ubiquitous Computing
* Parallel/Distributed/Grid Computing
* Novel Machine Architectures
* Semantic Web and Knowledge Grid
* Smart Home and Generic Interfaces
* AI and Soft Computing in Multimedia
* Computer Graphics and Simulation
* Multimedia Information Retrieval (images, videos, hypertexts, etc.)
* Internet Multimedia Mining
* Medical Image and Signal Processing
* Multimedia Indexing and Compression
* Virtual Reality and Game Technology
* Current Challenges in Multimedia
* Protocols for Ubiquitous Services
* Ubiquitous Database Methodologies
* Ubiquitous Application Interfaces
* IPv6 Foundations and Applications
* Smart Home Network Middleware
* Ubiquitous Sensor Networks / RFID
* U-Commerce and Other Applications
* Databases and Data Mining
* Multimedia RDBMS Platforms
* Multimedia in Telemedicine
* Multimedia Embedded Systems
* Multimedia Network Transmission/Streaming
* Entertainment Industry
* E-Commerce and E-Learning
* Novel Multimedia Applications
* Computer Graphics
* Multimedia network transmission/streaming
* Security in Commerce and Industry
* Security in Ubiquitous Databases
* Key Management and Authentication
* Privacy in Ubiquitous Environment
* Sensor Networks and RFID Security
* Multimedia Information Security
* Forensics and Image Watermarking
* Cyber Security
* Intrusion detection
* Biometric Security
* New developments in handheld and mobile information appliances
* New paradigms: mobile cloud, personal networks, social and crowd computing, etc
* Operating systems aspects for personal mobile devices
* New technological advances for personal mobile devices
* End-user interface issues in the design and use of personal technologies
* Enabling technologies for personal multimedia and ubiquitous computing
* Multimedia applications and techniques for personal computing devices
* Usage of personal devices for on-line learning

Submissions
Submissions should not exceed 8 pages in IEEE CS proceedings paper format, including
tables and figures. All paper submissions must represent original and unpublished work.
Submission of a paper should be regarded as an undertaking that, should the paper be
accepted, at least one of the authors will register for the conference and present the
work. Submissions will be conducted electronically on the conference website.

Nano-spring make transparent, super-stretchy skin-like sensors

2011-10-26T12:42:00.001+03:00

Article from:

http://www.sciencecodex.com/read/stanford_researchers_build_transparent_superstretchy_skinlike_sensor-80227

When the nanotubes are airbrushed onto the silicone, they tend to land in randomly oriented little clumps. When the silicone is stretched, some of the "nano-bundles" get pulled into alignment in the direction of the stretching.

When the silicone is released, it rebounds back to its original dimensions, but the nanotubes buckle and form little nanostructures that look like springs.

"After we have done this kind of pre-stretching to the nanotubes, they behave like springs and can be stretched again and again, without any permanent change in shape," Bao said.

Stretching the nanotube-coated silicone a second time, in the direction perpendicular to the first direction, causes some of the other nanotube bundles to align in the second direction. That makes the sensor completely stretchable in all directions, with total rebounding afterward.

Additionally, after the initial stretching to produce the "nano-springs," repeated stretching below the length of the initial stretch does not change the electrical conductivity significantly, Bao said. Maintaining the same conductivity in both the stretched and unstretched forms is important because the sensors detect and measure the force being applied to them through these spring-like nanostructures, which serve as electrodes.

The sensors consist of two layers of the nanotube-coated silicone, oriented so that the coatings are face-to-face, with a layer of a more easily deformed type of silicone between them.

The middle layer of silicone stores electrical charge, much like a battery. When pressure is exerted on the sensor, the middle layer of silicone compresses, which alters the amount of electrical charge it can store. That change is detected by the two films of carbon nanotubes, which act like the positive and negative terminals on a typical automobile or flashlight battery.

The change sensed by the nanotube films is what enables the sensor to transmit what it is "feeling." Whether the sensor is being compressed or extended, the two nanofilms are brought closer together, which seems like it might make it difficult to detect which type of deformation is happening. But Lipomi said it should be possible to detect the difference by the pattern of pressure.

Using carbon nanotubes bent to act as springs, Stanford researchers have developed a stretchable, transparent skin-like sensor. The sensor can be stretched to more than twice its original length and bounce back perfectly to its original shape. It can sense pressure from a firm pinch to thousands of pounds. The sensor could have applications in prosthetic limbs, robotics and touch-sensitive computer displays. Darren Lipomi, a postdoctoral researcher in Chemical Engineering and Zhenan Bao, associate professor in Chemical Engineering, explain their work.

(Photo Credit: Steve Fyffe, Stanford News Service)

With compression, you would expect to see sort of a bull's-eye pattern, with the greatest deformation at the center and decreasing deformation as you go farther from the center.

"If the device was gripped by two opposing pincers and stretched, the greatest deformation would be along the straight line between the two pincers," Lipomi said. Deformation would decrease as you moved farther away from the line.

Bao's research group previously created a sensor so sensitive to pressure that it could detect pressures "well below the pressure exerted by a 20 milligram bluebottle fly carcass" that the researchers tested it with. This latest sensor is not quite that sensitive, she said, but that is because the researchers were focused on making it stretchable and transparent.

"We did not spend very much time trying to optimize the sensitivity aspect on this sensor," Bao said.

"But the previous concept can be applied here. We just need to make some modifications to the surface of the electrode so that we can have that same sensitivity."

Article from:

http://www.sciencecodex.com/read/stanford_researchers_build_transparent_superstretchy_skinlike_sensor-80227

Artificial intelligence community mourns John McCarthy

2011-10-26T12:36:00.001+03:00

Article from http://www.bbc.co.uk/news/technology-15444222

Artificial intelligence researcher, John McCarthy, has died. He was 84.

The American scientist invented the computer language LISP.

It went on to become the programming language of choice for the AI community, and is still used today.

Professor McCarthy is also credited with coining the term "Artificial Intelligence" in 1955 when he detailed plans for the first Dartmouth conference. The brainstorming sessions helped focus early AI research.

Prof McCarthy's proposal for the event put forward the idea that "every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it".

The conference, which took place in the summer of 1956, brought together experts in language, sensory input, learning machines and other fields to discuss the potential of information technology.

Other AI experts describe it as a critical moment.

"John McCarthy was foundational in the creation of the discipline Artificial Intelligence," said Noel Sharkey, Professor of Artificial Intelligence at the University of Sheffield.

"His contribution in naming the subject and organising the Dartmouth conference still resonates today."

LISP

Prof McCarthy devised LISP at Massachusetts Institute of Technology (MIT), which he detailed in an influential paper in 1960.

The computer language used symbolic expressions, rather than numbers, and was widely adopted by other researchers because it gave them the ability to be more creative.

"The invention of LISP was a landmark in AI, enabling AI programs to be easily read for the first time," said Prof David Bree, from the Turin-based Institute for Scientific Interchange.

"It remained the AI language, especially in North America, for many years and had no major competitor until Edinburgh developed Prolog."

Regrets

In 1971 Prof McCarthy was awarded the Turing Award from the Association for Computing Machinery in recognition of his importance to the field.

He later admitted that the lecture he gave to mark the occasion was "over-ambitious", and he was unhappy with the way he had set out his new ideas about how commonsense knowledge could be coded into computer programs.

However, he revisted the topic in later lectures and went on to win the National Medal of Science in 1991.

After retiring in 2000, Prof McCarthy remained Professor Emeritus of Computer Science at Stanford University, and maintained a websitewhere he gathered his ideas about the future of robots, the sustainability of human progress and some of his science fiction writing.

"John McCarthy's main contribution to AI was his founding of the field of knowledge representation and reasoning, which was the main focus of his research over the last 50 years," said Prof Sharkey

"He believed that this was the best approach to developing intelligent machines and was disappointed by the way the field seemed to have turned into high speed search on very large databases."

Prof Sharkey added that Prof McCarthy wished he had called the discipline Computational Intelligence, rather than AI. However, he said he recognised his choice had probably attracted more people to the subject.

Article from http://www.bbc.co.uk/news/technology-15444222

Throwable Camera Creates 360-Degree Panoramic Images

2011-10-25T22:23:00.001+03:00

Article from http://mashable.com/2011/10/25/throwable-ball-camera/

Are you, like so many others, tired of all those old-fashioned cameras you have to hold in order to take pictures? Well here’s a camera you get to throw.

The Throwable Panoramic Ball Camera is a foam-padded ball studded with 36 fixed-focus, 2-megapixel mobile phone camera modules capable of taking a 360-degree panoramic photo.

You use the camera by throwing it directly in the air. When the camera reaches the apex — measured by an accelerometer in the camera — all 36 cameras automatically take a picture. These distinct pictures are then digitally stitched together and uploaded via USB where they are presented in a spherical panoramic viewer. This lets users interactively explore their photos including a zoom function.

The results — as seen in the video above — are pretty darn impressive, but the Ball Camera is definitely not meant for shaky hands. Any spin on the ball when it’s thrown could distort the final image and you certainly wouldn’t want to drop the thing despite its 3D-printed foam padding. The 2-megapixel cameras are adequate but the quality drops as soon as users try to zoom in on distant elements. Besides, it looks a little difficult to fit the thing into a purse, let alone your pocket.

Right now, the Throwable Panoramic Ball Camera is not available to buy, though its creators have it pending a patent. Cool idea, but is it practical? Would you ever buy a camera you could throw? Let us know in the comments.

http://mashable.com/2011/10/25/throwable-ball-camera/

Rendering Synthetic Objects into Legacy Photographs

2011-10-24T18:11:00.001+03:00

Kevin Karsch, Varsha Hedau, David Forsyth, Derek Hoiem
To be presented at SIGGRAPH Asia 2011

Abstract

We propose a method to realistically insert synthetic objects into existing photographs without requiring access to the scene or any additional scene measurements. With a single image and a small amount of annotation, our method creates a physical model of the scene that is suitable for realistically rendering synthetic objects with diffuse, specular, and even glowing materials while accounting for lighting interactions between the objects and the scene. We demonstrate in a user study that synthetic images produced by our method are confusable with real scenes, even for people who believe they are good at telling the difference. Further, our study shows that our method is competitive with other insertion methods while requiring less scene information. We also collected new illumination and reflectance datasets; renderings produced by our system compare well to ground truth. Our system has applications in the movie and gaming industry, as well as home decorating and user content creation, among others.

http://kevinkarsch.com/publications/sa11.html

Top 10 ACM SIGMM Downloads

2011-10-24T11:11:00.001+03:00

http://sigmm.org/records/records1103/featured04.html

Here we present the top downloaded ACM SIGMM articles from the ACM Digital Library, from July 2010 to June 2011. We are hoping that this list gives a much deserved exposure to the ACM SIGMM's best articles.

Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Jinhui Tang, Tao Mei, Meng Wang, Hong-Jiang Zhang. Correlative multilabel video annotation with temporal kernels. In ACM Trans. Multimedia Comput. Commun. Appl. 5(1), 2008
Michael S. Lew, Nicu Sebe, Chabane Djeraba, and Ramesh Jain. Content-based multimedia information retrieval: State of the art and challenges. In ACM Trans. Multimedia Comput. Commun. Appl. 2(1), 2006
Ba Tu Truong, Svetha Venkatesh. Video abstraction: A systematic review and classification. In ACM Trans. Multimedia Comput. Commun. Appl. 3(1), 2007
Yu-Fei Ma, Hong-Jiang Zhang. Contrast-based image attention analysis by using fuzzy growing. In ACM Multimedia 2003
Simon Tong and Edward Chang. Support vector machine active learning for image retrieval. In ACM Multimedia 2001
J.-P. Courtiat, R. Cruz de Oliveira, L. F. Rust da Costa Carmo. Towards a new multimedia synchronization mechanism and its formal definition. In ACM Multimedia 1994
Gabriel Takacs, Vijay Chandrasekhar, Natasha Gelfand, Yingen Xiong, Wei-Chao Chen, Thanos Bismpigiannis, Radek Grzeszczuk, Kari Pulli, Bernd Girod. Outdoors augmented reality on mobile phone using loxel-based visual feature organization. In ACM SIGMM MIR 2008
Jiajun Bu, Shulong Tan, Chun Chen, Can Wang, Hao Wu, Lijun Zhang, Xiaofei He. Music recommendation by unified hypergraph: combining social media information and music content. In ACM Multimedia 2010
Hina Keval, M. Angela Sasse. To catch a thief -- you need at least 8 frames per second: the impact of frame rates on user performance in a CCTV detection task. In ACM Multimedia 2008
Mathias Lux, Savvas A. Chatzichristofis. Lire: lucene image retrieval: an extensible java CBIR library. In ACM Multimedia 2008

FaceLight – Silverlight 4 Real-Time Face Detection

2011-10-20T00:34:00.002+03:00

This article describes the simple facial recognition method that searches for a certain sized skin color region in a webcam snapshot. This technique is not as perfect as a professional computer vision library like OpenCV and the Haar-like features they use, but it runs in real time and works for most webcam scenarios.

C

2011-10-14T01:12:00.001+03:00

‎#include<stdio.h>
int main()
{
cout<< "Goodbye Dennis Ritchie";
return 0;
}

ACM International Conference on Multimedia Retrieval (ICMR) 2012

2011-10-11T17:10:00.001+03:00

Effectively and efficiently retrieving information based on user needs is one of the most exciting areas in multimedia research. The Annual ACM International Conference on Multimedia Retrieval (ICMR) offers a great opportunity for exchanging leading-edge multimedia retrieval ideas among researchers, practitioners and other potential users of multimedia retrieval systems. This conference, puts together the long-lasting experience of former ACM CIVR and ACM MIR series, is set up to illuminate the state of the arts in multimedia (text, image, video and audio) retrieval.

ACM ICMR 2012 is soliciting original high quality papers addressing challenging issues in the broad field of multimedia retrieval.

Topics of Interest (not limited to)
• Content/semantic/affective based indexing and retrieval
• Large-scale and web-scale multimedia processing
• Integration of content, meta data and social network
• Scalable and distributed search
• User behavior and HCI issues in multimedia retrieval
• Advanced descriptors and similarity metrics
• Multimedia fusion
• High performance indexing algorithms
• Machine learning for multimedia retrieval
• Ontology for annotation and search
• 3D video and model processing
• Large-scale summarization and visualization
• Performance evaluation
• Very large scale multimedia corpus
• Navigation and browsing on the Web
• Retrieval from multimodal lifelogs
• Database architectures for storage and retrieval
• Novel multimedia data management systems and applications
• Applications in forensic, biomedical image and video collections

Important Dates

Paper Submission: January 15, 2012
Notification of Acceptance: March 15, 2012
Camera-Ready Papers Due: April 5, 2012
Conference Date: June 5 - 8, 2012

http://www.icmr2012.org/index.html

Kinect Object Datasets: Berkeley's B3DO, UW's RGB-D, and NYU's Depth Dataset

2011-10-10T19:11:00.001+03:00

Articlw from http://quantombone.blogspot.com/2011/10/kinect-object-datasets-berkeleys-b3do.html

Why Kinect?

The Kinect, made by Microsoft, is starting to become quite a common item in Robotics and Computer Vision research. While the Robotics community has been using the Kinect as a cheap laser sensor which can be used for obstacle avoidance, the vision community has been excited about using the 2.5D data associated with the Kinect for object detection and recognition. The possibility of building object recognition systems which have access to pixel features as well as 2.5D features is truly exciting for the vision hacker community!

Berkeley's B3DO

First of all, I would like to mention that it looks like the Berkeley Vision Group jumped on the Kinect bandwagon. But the data collection effort will be crowdsourced -- they need your help! They need you to use your Kinect to capture your own home/office environments and upload it to their servers This way, a very large dataset will be collected, and we, the vision hackers, can use machine learning techniques to learn what sofas, desks, chairs, monitors, and paintings look like. They Berkeley hackers have a paper on this at one of the ICCV 2011workshops in Barcelona, here is the paper information:

A Category-Level 3-D Object Dataset: Putting the Kinect to Work
Allison Janoch, Sergey Karayev, Yangqing Jia, Jonathan T. Barron, Mario Fritz, Kate Saenko, Trevor Darrell
ICCV-W 2011
[pdf] [bibtex]

UW's RGB-D Object Dataset

On another note, if you want to use 3D for your own object recognition experiments then you might want to check out the following dataset: University of Washington's RGB-D Object Dataset. With this dataset you'll be able to compare against UW's current state-of-the-art.

In this dataset you will find RGB+Kinect3D data for many household items taken from different views. Here is the really cool paper which got me excited about the RGB-D Dataset:

A Scalable Tree-based Approach for Joint Object and Pose Recognition
Kevin Lai, Liefeng Bo, Xiaofeng Ren, and Dieter Fox
In the Twenty-Fifth Conference on Artificial Intelligence (AAAI), August 2011.

NYU's Depth Dataset

I have to admit that I did not know about this dataset (created by by Nathan Silberman of NYU), until after I blogged about the other two datasets. Check out the NYU Depth Dataset homepage. However the internet is great, and only a few hours after posted this short blog post, somebody let me know that I left out this really cool NYU dataset. In fact, it looks like this particular dataset might be at the LabelMe-level regarding dense object annotations, but with accompanying Kinect data. Rob Fergus & Co strike again!

Nathan Silberman, Rob Fergus. Indoor Scene Segmentation using a Structured Light Sensor. To Appear: ICCV 2011 Workshop on 3D Representation and Recognition

The PHD Movie!!!

2011-10-09T13:14:00.001+03:00

Screening @ Cyprus University of Technology
11/16/2011 - 7:00PM - CUT
Organized by: Cyprus University of Technology
Add to my google calendar

Visit www.phdcomics.com/movie to find a screening at your school. Is The PHD Movie not coming to your school? Ask your administration to sponsor a screening!

Exploring Photobios - SIGGRAPH 2011

2011-10-08T11:50:00.001+03:00

Panasonic unveils first robotic hairdresser

2011-10-07T09:50:00.001+03:00

The annual CEATEC technology in Tokyo gives Japanese technology companies a chance to let their hair down and show off robots far, far too odd for Western consumption.
Robot unicyclists and 'robot companions' are regulars at the show - often unveiled by otherwise normal technology companies. This year, Panasonic unveiled the first robotic hairdresser - as well as a robot 'doctor'.
Panasonic's robot hair washer uses advanced robot 'fingers' to massage the scalp while washing your head with jets of water and soap - rather like a car wash for your skull.
Information provided by cctv.com Thank you http://www.cctv.com

Recent Image Retrieval Techniques

2011-10-06T13:04:00.001+03:00

http://sglab.kaist.ac.kr/~sungeui/IR/Slides/

“Practical Image and Video Processing Using MATLAB®”

2011-10-04T09:52:00.001+03:00

This is the first book to combine image and video processing with a practical MATLAB(R)-oriented approach in order to demonstrate the most important image and video techniques and algorithms. Utilizing minimal math, the contents are presented in a clear, objective manner, emphasizing and encouraging experimentation.

The book has been organized into two parts. Part I: Image Processing begins with an overview of the field, then introduces the fundamental concepts, notation, and terminology associated with image representation and basic image processing operations. Next, it discusses MATLAB(R) and its Image Processing Toolbox with the start of a series of chapters with hands-on activities and step-by-step tutorials. These chapters cover image acquisition and digitization; arithmetic, logic, and geometric operations; point-based, histogram-based, and neighborhood-based image enhancement techniques; the Fourier Transform and relevant frequency-domain image filtering techniques; image restoration; mathematical morphology; edge detection techniques; image segmentation; image compression and coding; and feature extraction and representation.

Part II: Video Processing presents the main concepts and terminology associated with analog video signals and systems, as well as digital video formats and standards. It then describes the technically involved problem of standards conversion, discusses motion estimation and compensation techniques, shows how video sequences can be filtered, and concludes with an example of a solution to object detection and tracking in video sequences using MATLAB(R).

Extra features of this book include:

More than 30 MATLAB(R) tutorials, which consist of step-by-step guides to exploring image and video processing techniques using MATLAB(R)

Chapters supported by figures, examples, illustrative problems, and exercises

Useful websites and an extensive list of bibliographical references

This accessible text is ideal for upper-level undergraduate and graduate students in digital image and video processing courses, as well as for engineers, researchers, software developers, practitioners, and anyone who wishes to learn about these increasingly popular topics on their own.

http://www.ogemarques.com/

Call for participation in the ICPR 2012 Contests

2011-10-04T01:26:00.001+03:00

http://www.icpr2012.org/contests.html

We are happy to announce the opening of the six ICPR 2012 Contests, to be
held on November 11, 2012 in conjunction with the 21st International Conference on Pattern Recognition (www.icpr2012.org). The aim of the contests is to encourage better scientific development through comparing competing
approaches on a common dataset.

The Contests (see www.icpr2012.org/contests.html for full details and links):

    Gesture Recognition Challenge and Kinect Grand Prize
    HEp-2 Cells Classification
    Human activity recognition and localization
    Kitchen Scene Context based Gesture Recognition
    Mitosis Detection in Breast Cancer
    People tracking in wide baseline camera networks

Publications
================
There are no 'publications' for the contest participants other than what each contest organizer prepares. Contest participants are encouraged to submit their results as a normal paper to the main conference where it
will be reviewed as normal. Short introductions for each contest are planned to be included in the main proceedings.

Registration
================
Attending the contest sessions requires registration for the contest, which can be done using the main conference registration form. Registration for the main conference is not obligatory, but is necessary if you want to also attend the main conference.

Dates
================
Each Contest has its own time schedule. See the website of each contest for the dates.
The results of the competitions will be announced at the conference:November 11, 2012

CFP: VII Conf. on Articulated Motion and Deformable Objects (AMDO 2012)

2011-10-04T01:25:00.001+03:00

Andratx, Mallorca, Spain
11-13 July, 2012
http://dmi.uib.es/~ugiv/AMDO
amdo@uib.es

The Spanish Association for Pattern Recognition and Image Analysis (AERFAI) and the Mathematics and Computer Science Department of UIB are organising the seventh nternational conference AMDO 2012 that will take place in Puerto de Andratx, Mallorca. This conference is the natural evolution of AMDO previous workshops. The new goal of this conference is to promote interaction and collaboration among researchers working directly in the areas covered by the main tracks. The new perceptual user interfaces and the emerging echnologies increase the relation between aeas involved with human-computer interaction. The perspective of the AMDO 2012 conference will be to strengthen the relationship between the many areas that have as a key point the study of the human body using computer technologies as the main tool.
It is a great opportunity to encourage links between research in the areas of computer vision, computer graphics, advanced multimedia applications and multimodal interfaces that share common problems and frequently use similar techniques or tools. In this particular edition the related topics are divided in several tracks, including the topics above proposed.

AMDO 2012 will consist of three days of lecture sessions, both regular and invited presentations, a poster session and international tutorials. The conference fee (approx.450 euro) includes a social program (conference dinner, coffee breaks, snacks and cultural activities). Students, AERFAI and EG members can register at a reduced fee.

TOPICS INCLUDE (but not restricted to):
Track 1: Advanced Computer Graphics (Human Modelling & Animation)
Track 2: Human Motion (Analysis, Tracking, 3D Reconstruction & Recognition)
Track 3: Multimodal User Interaction & Applications
Track 4: Affective Interfaces (recognition and interpretation of emotions, ECAs - Embodied Conversational Agents in HCI)

PAPER SUBMISSION AND REVIEW PROCESS
Papers should describe original and unpublished work about the above or closely related topics. Please submit your paper electronically at our website (see URL above) using the software provided. All submissions should be in Adobe Acrobat (pdf). The AMDO2012 secretariat must receive your paper before March 12, 2012, 17:00 GMT
(London time). Up to ten pages will be considered. All papers submitted will be subjected to a blind review process by at least three members of the program committee. The review paper must not provide names and affiliation, and should include a title, a 150-word abstract, keywords and paper manuscript. Accepted papers will
appear in the LNCS Springer-Verlag international proceedings that will be published and distributed to all participants at the workshop. For more details and news, visit our web page. Selected papers will be nominated to be published in an extended version
in a newsletter with impact index.

N.B. Submission implies the willingness of at least one of the authors to register and to present the communication at the conference, if accepted.

IMPORTANT DEADLINES:
Submission of papers March 12, 2012
Notification of acceptance April 12, 2012
Camera-ready April 30, 2012
Early registration May 31, 2012
Late registration June 30 2012
VII AMDO Conference 2012 11-13 July 2012

Job offer : engineer position in mutlimedia retrieval systems' evaluation

2011-09-12T14:43:00.001+03:00

Position: research engineer.
Title: evaluation of content-based image and video document indexing systems
Duration: from 18 to 24 months.
Target starting date: 1st November 2011.
Location: Laboratory of Informatics of Grenoble: http://www.liglab.fr/
Team: Multimedia Information Indexing and Retrieval: http://mrim.imag.fr/
Salary: between 1900 and 2200 € net per month depending upon experience.
Contact: Georges Quénot (Researcher at CNRS, HDR), Georges.Quenot@imag.fr.

In the context of the Quaero Programme (http://www.quaero.org), the recruited person will:
* participate to the development or adaptation of image and video corpus annotation tools;
* manage the use of these tools by a team of annotators for the effective creation of annotated corpus;
* participate to the creation or adaptation of tools for the evaluation of content-based image and video document indexing systems;
* participate to the organization of evaluation campaigns for such systems;
* participate to the administrative management of the project.
Expected skills: Unix/Linux, Windows, C/C++, Java, XML, HTML/CGI.
http://mrim.imag.fr/en/Positions/poste-IQ1b.pdf

Congratulations to DEMIR research team for winning the ImageCLEF-MED 2011 Ad-hoc image-based retrieval task using CEDD

2011-09-12T00:24:00.001+03:00

Congratulations to DEMIR research team for winning the ImageCLEF-MED 2011 Ad-hoc image-based retrieval task using CEDD!!!!

Abstract. This paper present the details of participation of DEMIR (Dokuz Eylul University Multimedia Information Retrieval) research team to the context of our participation to the ImageCLEF 2011 Medical Retrieval task. This year, we evaluated fusion and re-ranking method which is based on the best low level feature of images with best text retrieval result. We improved results by examination of different weighting models for retrieved text data and low level features. We tested multi–modality image retrieval in ImageCLEF 2011 medical retrieval task and obtained the best seven ranks in mixed retrieval, which includes textual and visual modalities. The results clearly show that proper fusion of different modalities improve the overall retrieval performance.

Read the paper http://clef2011.org/resources/proceedings/Alpkocak_Clef2011.pdf

An eBay for science.

2011-08-29T01:48:00.001+03:00

Reported by Zoë Corbyn, in Nature News, 19 Aug. 2011.

Last week, Science Exchange in Palo Alto, California, launched a website allowing scientists to outsource their research to ‘providers’ — other researchers and institutions that have the facilities and equipment to meet requesting scientists’ needs. Nature asked the company’s co-founder, researcher-turned-entrepreneur Elizabeth Iorns, how the website works, and what an online marketplace for experiments could mean for the future of research.

What is Science Exchange?

It is an online marketplace for scientific experiments. Imagine eBay, but for scientific knowledge. You post an experiment that you want to outsource, and scientific service providers submit bids to do the work. The goal is to make scientific research more efficient by making it easy for researchers to access experimental expertise from core facilities with underutilized capacity.

Where did the idea come from?

It was through my work as a breast-cancer biologist at the University of Miami in Florida. I wanted to conduct some experiments outside my field, and realized that I needed an external provider. What followed was an entirely frustrating process, and when I found the provider it was difficult to pay them because they were outside my university’s purchasing system. When I talked to other scientists, it became clear that this was a really big problem, but also one that could be solved with a marketplace. Development of the website started around a kitchen table in Miami in April.

Why would researchers want to participate?

So they can access technologies that their university doesn’t offer; if their own institutional facilities are too busy; if they just generally want to speed up the research process; or if they want a good deal. Prices can vary dramatically: for example, through our platform I have seen bids to perform a microRNA study ranging from US$3,500 to $9,000. Those who do the work can also build reputations independent of their publications by gaining feedback from those they work with.

Why might universities want their facilities to participate?

There are huge budget incentives. It allows institutions to make the most of their existing facilities, which means that they don’t have to subsidize them as much. Also, if researchers can use Science Exchange to access the latest equipment, institutions can be more flexible about when they buy new instruments.

How are you intending to make a profit?

We take a small commission if we match a researcher with a provider and they use us to do the transaction — 5% for projects under $5,000, which is tiny in comparison with what researchers can save by examining prices from multiple providers. For projects costing more than $5,000, it is a lower commission and a sliding scale: we aren’t going to charge $50,000 on a $1-million experiment.

How are you funded?

By Ycombinator, a start-up accelerator programme in Mountain View, California, and angel investors. We have raised $320,000 so far and are looking to raise another $1 million. We have big plans to expand.

What has the response been like?

We launched after a short beta period and the growth is crazy. We now have close to 1,000 scientists using our site and 50–100 signing up every day. More than 70 institutions have providers registered with us, including Stanford University in California, Harvard University in Cambridge, Massachusetts, and, of course, Miami.

Is the service limited to particular regions of the world?

Anyone from anywhere can use it. We had initially thought our focus would be in the United States but we have had a lot of interest from overseas researchers, particularly interest in the facilities that are available here.

Article From:Zoë Corbyn, in Nature News, 19 Aug. 2011.

Script#

2011-08-28T19:51:00.001+03:00

Script# brings productivity to Ajax and JavaScript development. Script# is a free tool that enables developers to author C# source code and subsequently compile it into regular script that works across all modern browsers, and in doing so, leverage the productivity and power of existing .NET tools as well as the Visual Studio IDE. Script# empowers you with a development methodology and approach that brings software engineering, long term maintainability and scalable development approaches for your Ajax applications, components and frameworks.

Script# is used extensively by developers within Microsoft building Ajax experiences in Windows Live, Office to name just a couple, as well as by a external developers and companies including Facebook. If you’re building Ajax-based RIA applications, you owe it to yourself to try Script# today and see if it can help improve your own Ajax development!

The Script# Project

Productivity and better tooling are primary motivators behind Script#. At the same time, a fundamental design tenet and driving philosophy behind the design of Script# is to produce script that resembles hand-written script that is aware and faithful to the script runtime environment found in browsers. Specifically the compiler does not introduce unnecessary layers of abstraction or indirection. The idea is you’re simply writing script in a better and pragmatic way, rather than trying to port a .NET application to the browser, which is more likely to produce impractical results.

Script# allows programming against the DHTML DOM APIs and JavaScript APIs, as well as Silverlight 1.0 script API. The compiler itself isn’t coupled to any one particular framework. You can use Script# to program against Microsoft ASP.NET Ajax as well as other 3rd party frameworks such as ExtJS (via Ext#). At the same time, the compiler is complemented by an optional ScriptFX framework, which is a small framework built using Script# itself. Finally, if you have existing scripts, they can be imported and then used from new C# code so you don’t have to rewrite everything from scratch to start using Script#.

Scripts generated using Script# are honest-to-goodness plain old JavaScript files, that you can freely deploy into your applications, and there is no runtime dependency on the Script# compiler. This is further explained in the Understanding Script#page. You will need .NET 2.0+ and/or Visual Studio on your development machine. You can also use Visual C# Express which is available for free.

Script# is an evolving project, but is quite mature and ready for use in real-world projects such as those listed in the showcase. Script# is being used both internally within Microsoft as well as external applications. It was first released in May 2006 (introductory blog post). Over the course of the last two+ years, it has been regularly updated with new features and bug fixed based on actual usage and feedback from developers like you. You can read about the latest release on the release historypage. Please do continue sending any feedback on Script# that you might have.

The content on this site will be updated periodically to include additional concepts and tutorials. Please subscribe to the Script# feed to stay up-to-date or check this page often.

http://projects.nikhilk.net/ScriptSharp

Compact Composite Descriptors for Content Based Image Retrieval

2011-08-25T20:59:00.001+03:00

Authors: Savvas A. Chatzichristofis, Yiannis S. Boutalis

This book covers the state of the art in image indexing and retrieval techniques paying particular attention in recent trends and applications. It presents the basic notions and tools of content-based image description and retrieval, covering all significant aspects of image preprocessing, features extraction, similarity matching and evaluation methods. Particular emphasis is given in recent computational intelligence techniques for producing compact content based descriptors comprising color, texture and spatial distribution information. Early and late fusion techniques are also used for improving retrieval results from large probably distributed inhomogenous databases. The book reports on the basic international standards and provides an updated presentation of the current retrieval systems. Numerous utilities and techniques are implemented in software, which is provided as a supplementary material under an open-source license agreement. The book is particularly useful for postgraduate students and researchers in the field of image retrieval, who want to easily elaborate and test state of the art techniques and possibly incorporate it in their development.

ISBN-13: 978-3-639-37391-2

ISBN-10: 363937391X

EAN: 9783639373912

Book language: English

Publishing house: VDM Verlag Dr. Müller

Website: http://www.vdm-verlag.de/

Number of pages: 216

Published at: 2011-08-24

Category: Informatics, IT

Price: 79.00 €

Order from : More Books or Amazon

Face recognition in London 2012 Olympic Games

2011-08-23T01:58:00.001+03:00

Original Article http://hosted.ap.org/dynamic/stories/E/EU_BRITAIN_HUNTING_FOR_RIOTERS?SITE=AP&SECTION=HOME&TEMPLATE=DEFAULT

LONDON (AP) -- Facial recognition technology being considered for London's 2012 Games is getting a workout in the wake of Britain's riots, a senior police chief told The Associated Press on Thursday, with officers feeding photographs of suspects through Scotland Yard's newly updated face-matching program.

Chief Constable Andy Trotter of the British Transport Police said the sophisticated software was being used to help find those suspected of being involved in the worst unrest London has seen in a generation.

But he cautioned that facial recognition makes up only a fraction of the police force's efforts, saying tips have mostly come from traditional sources, such as still images captured from closed circuit cameras, pictures gathered by officers, footage shot by police helicopters or images snapped by members of the public. One department was driving around a large video screen displaying images of suspects.

"There's a mass of evidence out there," Trotter said in a telephone interview. "The public are so enraged that people who wouldn't normally come forward are helping us - especially when they see their neighbors are coming back with brand new TVs."

Prime Minister David Cameron acknowledged Thursday that police were overwhelmed by rioting that began over the weekend in London and spread across the country over four days. Mobs of youths looted stores, set buildings aflame and attacked police officers and other people - a chaotic and humbling scene for a city a year away from hosting the Olympic Games.

At an emergency session of Parliament summoned to discuss the riots, Cameron said authorities were considering new powers, including allowing police to order thugs to remove masks or hoods, evicting troublemakers from subsidized housing and temporarily disabling cell phone instant messaging services. He said the 16,000 police deployed on London's streets to deter rioters and reassure residents would remain through the weekend.

A press officer with Scotland Yard - who also spoke anonymously, in line with force policy - confirmed that facial recognition technology was at the police's disposal, although he gave few other details. He said that generally the technology would only be used to help identify those suspected of serious crimes, such as assault, and that in most cases disseminating photographs to the general public remains a far cheaper and more effective way of finding suspects.

The facial-recognition technology used by police treats the human face like a grid, measuring the distance between a person's nose, eyes, lips and other features. It has recently been upgraded, according to an article published last year in Scotland Yard's bimonthly magazine, "The Job."

The March 2010 article said that the new program has been shown to work far better than older versions of the technology, with one expert quoted as saying that it had shown promise in identifying people from high-quality, face-on shots taken off of surveillance photographs, mobile phones, passports or the Internet.

A law enforcement official told the AP that to use the technology "you have to have a good picture of a suspect and it is only useful if you have something to match it against. In other words, the suspect already has to have a previous criminal record."

He spoke on condition of anonymity because he was not authorized to discuss ongoing investigations.

In another effort to identify suspects, police have released two dozen photos and videos to the picture-sharing website Flickr, where they've already gathered more than 400,000 hits. Some of those photographs have also been published by Britain's brash tabloid press. The Sun recently plastered them across its front page, along with a headline urging readers to report looters to the police.

The photographs on Flickr are mainly grainy images pulled from cameras, which may not be of much use to face-matching software. But detectives are already scanning the Web for pictures of high-quality photographs of rioters' faces, according to photojournalist Guilherme Zauith, who witnessed some of the disturbances in London and later posted images of clashes to the Internet.

Zauith said he was recently contacted by a London detective "saying that they saw my photos online and if I could send it to them to help to identify the people."

"They were looking for all kind of photographs showing faces," he said. Zauith, a 30-year-old Brazilian national, said he turned the photos over to the detective.

The West Midlands police were trying another approach: driving a van equipped with a large screen displaying 50 images of suspects through Birmingham.

Police said the "Digi-Van" will stop at key locations around the city to give shoppers and commuters a good look at the photographs in hopes they can help identify suspects.

Facial recognition technology is already widely employed by free-to-use websites such as Facebook and Google Inc.'s Picasa photo-sharing program.

Such programs have been of increasing interest to authorities as well. A person with the Olympic planning committee, speaking to the AP on condition of anonymity because of the sensitivity of security preparations, said that facial recognition software was being considered for use as a security measure during the Olympic Games.

Meanwhile, detectives are employing a host of other tactics to take aim at the rioters. Police departments across the country have made arrests linked to riot threats and boasts posted to social networking sites.

Trotter said that while investigations had been helped by looters "who publicize their actions on things like Facebook," a lot of arrests have come the old-fashioned way, through officers simply spotting suspects they'd seen before.

"It's not just the face that is recognizable," Trotter said. "It's been in the way they walk, or the clothes they're wearing or even tattoos."

http://hosted.ap.org/dynamic/stories/E/EU_BRITAIN_HUNTING_FOR_RIOTERS?SITE=AP&SECTION=HOME&TEMPLATE=DEFAULT

image source: http://www.theregister.co.uk/2008/01/28/hundred_percent_face_recognition_claim/

Introduction to Artificial Intelligence

2011-08-22T10:34:00.001+03:00

A bold experiment in distributed education, "Introduction to Artificial Intelligence" will be offered free and online to students worldwide during the fall of 2011. The course will include feedback on progress and a statement of accomplishment. Taught by Sebastian Thrun and Peter Norvig, the curriculum draws from that used in Stanford's introductory Artificial Intelligence course. The instructors will offer similar materials, assignments, and exams.

Artificial Intelligence is the science of making computer software that reasons about the world around it. Humanoid robots, Google Goggles, self-driving cars, even software that suggests music you might like to hear are all examples of AI. In this class, you will learn how to create this software from two of the leaders in the field. Class begins October 10.
Details on the course, including a syllabus is available here. Sign up above to receive additional information about participating in the online version when it becomes available.

A high speed internet connection is recommended as most of the course content will be video based. Access to a copy of Artificial Intelligence: A Modern Approach may be helpful but is not required. Peter Norvig is co-author of this text and is donating all royalties earned from his text to charity. Any edition of the textbook may be used but the third edition is preferred.

Stanford University's School of Engineering also offers other complete online courses at no cost. Click here to access Stanford Engineering Everywhere.

http://www.ai-class.com/

Stop Motion Photographer

2011-08-22T01:27:00.001+03:00

Who needs a video camera when you've got 2335 photos? Follow the adventures of two young photographers as they meet and create memories together.

Stop Motion Photographer (Behind The Scenes)

Call for MS students of UCS Lab@SeoulTech-National, Korea (Supervisor: James. J. Park)

2011-08-19T11:59:00.001+03:00

Ubiquitous Computing and Security (UCS) Research Lab (http://www.parkjonghyuk.net) is seeking for some active highly self-motivated full-time MS. students to conduct cutting-edge research in the area of Ubiquitous Computing, Security and Networks. UCS Lab is interested in several research topics in the follows;

1.Security field:
Ubiquitous Security: Home network, RFID, WSN Security
Security Protocol : Key management, Access Control, Authentication, privacy protection
Multimedia Security: DRM, MPEG-21 IPMP
Digital Forensics and Computer Security
Smartphone and mobile computing Security
IT Convergence Security

2.Intelligent Applications and Services field:
Context Awareness, Smart Home, Ubi-Home, Smartphone/Mobile Services, Ubiquitous and Pervasive Computing

3. Network field:
Wireless Sensor Networks, Mobile Ad hoc Networks, Network Management, Internet Technology, High Speed Networks,

** This field researches will be co-worked with Network Lab (Supervisor: Prof. Kilhung Lee, http://computer.snut.ac.kr/~khlee).
The students will be hired to join UCS Research Lab and work on some projects and FTRA(http://www.ftrai.org) related works.

Requirements:
We are looking for candidates who meets the following requirements:
-TOPIK level 4 or 5 (http://topikexam.wordpress.com)
-bachelor's degree in Computer Science and Engineering(CSE), extended CSE, or Applied Mathematics.
-outstanding programming skills: C, C++, java, etc.
-good communicative skills in English, both in speaking and in writing;
(**candidates from non-English speaking countries should be prepared to prove their English language skills**).

Support Program for MS. Students in UCS Lab@SeoulTech:
1.Schorship & Dormitory Support
1) The first semester: Both 1,500,000 KW and Dormitory (depend on review results).
2) Since the second semester:
Both of them will be fully suppored according to academic achievements (score: 4.3/4.5).
Only schorship (1,5000,000KW) will be supported according to academic achievements (score: 3.7/4.5).
2.Extra Supports: Depand on contributions in projects.
3.Incentive: Depend on publication performances.

Application:
For consideration, applications should be received by **Sept. 20, 2011**.
Interested candidates should submit to UCS Lab secretary (Mr.JS Park: jisoo08@gmail.com) by email the following:
- Motivation letter.
- Detailed curriculum vitae with Photo.
- Research future plan.
- proof of English language skills (if applicable).

Orasis Brain-Inspired Image Processing App, is now available in iTunes!

2011-08-17T11:49:00.001+03:00

Its main objective is to make your photos look closer to what your eyes perceived at the exact moment your photo was taken. Orasis will make your photos look more realistic, extracting visual information in the dark or bright areas, which was not visible in the original image.

Orasis is based on a PhD research, developed at the Electronics Lab of the Democritus University of Thrace. It incorporates neural characteristics of the Human Visual System, which ensures that the enhanced image will be much closer to what we perceive with our eyes. More information on Orasis, as well as an extended image database can be found in the website:

http://orasis-imaging.com/

The iTunes site is:

http://itunes.apple.com/us/app/orasis/id454408758?ls=1&mt=8

BRISK: Binary Robust Invariant Scalable Keypoints

2011-08-11T11:49:00.001+03:00

Stefan Leutenegger, Margarita Chli and Roland Siegwart, "BRISK: Binary Robust Invariant Scalable Keypoints", Proceedings of the IEEE International Conference on Computer Vision (ICCV) 2011.

Effective and efﬁcient generation of keypoints from animage is a well-studied problem in the literature and forms the basis of numerous Computer Vision applications. Established leaders in the ﬁeld are the SIFT and SURF algorithms which exhibit great performance under a variety of image transformations, with SURF in particular considered as the most computationally efﬁcient amongst the highperformance methods to date.

In this paper we propose BRISK, a novel method for keypoint detection, description and matching. A comprehensive evaluation on benchmark datasets reveals BRISK’s adaptive, high quality performance as in state-of-the-art algorithms, albeit at a dramatically lower computational cost (an order of magnitude faster than SURF in cases). The key to speed lies in the application of a novel scale-space FAST-based detector in combination with the assembly of a bit-string descriptor from intensity comparisons retrieved by dedicated sampling of each keypoint neighborhood

Video Presentation: http://margaritachli.com/videos/ICCV2011video1.avi

PDF: http://margaritachli.com/papers/ICCV2011paper.pdf

Recognition Using Visual Phrases

2011-08-11T11:39:00.001+03:00

CVPR 2011 Award Paper

Ali Farhadi (UIUC); Mohammad Amin Sadeghi (University of Illinois at Urbana-Champaign)

Abstract

In this paper we introduce visual phrases, complex visual composites like “a person riding a horse”. Visual phrases often display significantly reduced visual complexity compared to their component objects, because the appearance of those objects can change profoundly when they participate in relations. We introduce a dataset suitable for phrasal recognition that uses familiar PASCAL object categories, and demonstrate significant experimental gains resulting from exploiting visual phrases. We show that a visual phrase detector significantly outperforms a baseline which detects component objects and reasons about relations, even though visual phrase training sets tend to be smaller than those for objects. We argue that any multi-class detection system must decode detector outputs to produce final results; this is usually done with nonmaximum suppression. We describe a novel decoding procedure that can account accurately for local context without solving difficult inference problems. We show this decoding procedure outperforms the state of the art. Finally, we show that decoding a combination of phrasal and object detectors produces real improvements in detector results.

Presentation: http://techtalks.tv/talks/54190/

Lire Demo 0.9 alpha 2 just released

2011-08-09T20:05:00.001+03:00

Article from http://www.semanticmetadata.net/

Finally I found some time to go through Lire and fix several of the — for me — most annoying bugs. While this is still work in progress I have a preview with the demo uploaded to sf.net. New features are:

Auto Color Correlogram and Color Histogram features improved
Re-ranking based on different features supported
Enhanced results view
Much faster indexing (parallel, use -server switch for your JVM)
Much faster search (re-write of the searhc code in Lire)
New developer menu for faster switching of search features
Re-ranking of results based on latent semantic analysis

You can find the updated Lire Demo along with a windows launcher here, Mac and Linux users please run it using “java -jar … ” or double click (if your windows manager supports actions like that

Download Liredemo v0.9 alpha 2

The source is — of course — GPL and available in the SVN.

Congratulations Mathias!

CFP: EURASIP Journal on Advances in Signal Processing Special Issue On Social Media Processing and Semantic Modeling

2011-08-04T13:41:00.001+03:00

Automatic image/video annotation is still imperfect and error-prone due to the semantic gap. As a result, collaborative image/video tagging (such as Flickr and Youtube) has become very popular for people to share, tag and search images/videos. With the exponential growth of such social media, it has become increasingly important to have mechanisms that can support more effective searching from large-scale collections of social media. With the fast development of hardware technologies, users are looking for more and more sophisticated functions for social media processing and semantic modeling. To support the advanced functions, more sophisticated algorithms should be developed for understanding, processing and modeling the underlying semantics of social medias that may contain more than one medium of signals simultaneously. As a result, there are urge demands for more sophisticated algorithms for semantic modeling and processing of social medias. With the recent progress on computation infrastructure such as GFS, MapReduce, Cloud Computing and CUDA, it is possible for us to develop more effective techniques for social medial processing and semantic modeling. The topics for this special issue will include, but are not limited to:

• Advanced semantic models for social media processing, especially for multimedia social media data

• Social media computation and applications on advanced semantic models, such as clustering, reasoning and retrieval

• Novel semantic models for non-traditional signals, such as touch models for haptic devices, gesture models for touch screens, and 3D object models

• Automatic extraction algorithms for semantic models, either model driven or data driven

• Computation algorithms and infrastructures for the problems of model extraction and applications

Before submission authors should carefully read over the journal's Author Guidelines, which are located http://www.hindawi.com/journals/asp/guidelines.html. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/ according to the following timetable:

Manuscript Due October 15, 2011
First Round of Reviews January 15, 2012
Publication Date April 15, 2012

Lead Guest Editor:

Hangzai Luo, Software Engineering Institute, China East Normal University, Shanghai, CHINA; hzluo@sei.ecnu.edu.cn

Guest Editors:

Xiaofei He, State Key Lab of CAD&CG, College of Computer Science, Zhejiang University, Hangzhou, CHINA; xiaofeihe@cad.zju.edu.cn

Shin'ichi Satoh, National Institute of Informatics, Tkoyo, Japan; satoh@nii.ac.jp

Jianping Fan, Department of Computer Science, UNC-Charlotte, Charlotte, NC, USA; jfan@uncc.edu

7th INTERNATIONAL SUMMER SCHOOL ON PATTERN RECOGNITION (ISSPR) 4-9 SEPTEMBER 2011, Plymouth, UK

2011-08-04T00:18:00.001+03:00

http://www.patternrecognitionschool.com <http://pro.expressemail.in/link.php?M=1048308&N=3623&L=708&F=H>

Registration deadline: 10th August, 2011

It is a pleasure to announce the Call for Participation to the 7th International Summer School on Pattern Recognition. I write to invite you, your colleagues, and students within your department to attend this event. In 2010, the 6th ISSPR School held at Plymouth was a major success with over 90 participants. The major focus of 2011 summer school includes:

- A broad coverage of pattern recognition areas which will be taught in a tutorial style over five days by leading experts. The areas covered include statistical pattern recognition, Bayesian techniques, non-parametric and neural network approaches including Kernel methods, String matching, Evolutionary computation, Classifiers, Decision trees, Feature selection and Dimensionality reduction, Clustering, Reinforcement learning, and Markov models. For more details visit the event website.

- A number of prizes sponsored by Microsoft and Springer for best research demonstrated by participants and judged by a panel of experts. The prizes will be presented to the winners by Prof. Chris Bishop from Microsoft Research.

- Providing participants with knowledge and recommendations on how to develop and use pattern recognition tools for a broad range of applications.

3 Corporate Scholarships are still available towards discounted registration fee for students till 10th August, 2011 so this is an excellent opportunity for participants to register at an affordable cost. The fee includes registration and accommodation plus meals at the event. The registration process is online through the school website www.patternrecognitionschool.com <http://pro.expressemail.in/link.php?M=1048308&N=3623&L=708&F=H> which has further details on registration fees. Please note that the number of participants registering each year at the summer school is high with a limited number of seats available, and therefore early registration is highly recommended.

Should you need any help, then please do not hesitate to contact school secretariate at enquiries@patternrecognitionschool.com <mailto:enquiries@patternrecognitionschool.com>

Deb Roy: The birth of a word

2011-08-01T01:20:00.001+03:00

MIT researcher Deb Roy wanted to understand how his infant son learned language -- so he wired up his house with video cameras to catch every moment (with exceptions) of his son's life, then parsed 90,000 hours of home video to watch "gaaaa" slowly turn into "water." Astonishing, data-rich research with deep implications for how we learn.

Deb Roy studies how children learn language, and designs machines that learn to communicate in human-like ways. On sabbatical from MIT Media Lab, he's working with the AI company Bluefin Labs. Full bio and more links

http://www.ted.com/talks/deb_roy_the_birth_of_a_word.html

MPEG news: a report from the 97th meeting, Torino, Italy

2011-07-31T13:27:00.001+03:00

Original Article:http://multimediacommunication.blogspot.com/ by Christian Timmerer

The 97th MPEG meeting in Torino brought a few interesting news which I'd like to report here briefly. Of course, as usual, there will be an official press release to be published within the next weeks. However, I'd like to report on some interesting topics as follows:

MPEG Unified Speech and Audio Coding (USAC) reached FDIS status
Call for Proposals: Compact Descriptors for Visual Search (CDVS) !!!
Call for Proposals: Internet Video Coding (IVC)

MPEG Unified Speech and Audio Coding (USAC) reached FDIS status

ISO/IEC 23003-3 aka Unified Speech and Audio Coding (USAC) reached FDIS status and soon will be an International Standard. The FDIS itself won't be publicly available but the Unified Speech and Audio Coding Verification Test Report in September 2011 (most likely here).

Call for Proposals: Compact Descriptors for Visual Search (CDVS)

I reported previously about that and here comes the final CfP including the evaluation framework.
MPEG is planning standardizing technologies that will enable efficient and interoperable design of visual search applications. In particular we are seeking technologies for visual content matching in images or video. Visual content matching includes matching of views of objects, landmarks, and printed documents that is robust to partial occlusions as well as changes in vantage point, camera parameters, and lighting conditions.

There are a number of component technologies that are useful for visual search, including format of visual descriptors, descriptor extraction process, as well as indexing, and matching algorithms. As a minimum, the format of descriptors as well as parts of their extraction process should be defined to ensure interoperability.

It is envisioned that a standard for compact descriptors will:

ensure interoperability of visual search applications and databases,
enable high level of performance of implementations conformant to the standard,
simplify design of descriptor extraction and matching for visual search applications,
enable hardware support for descriptor extraction and matching in mobile devices,
reduce load on wireless networks carrying visual search-related information.

It is envisioned that such standard will provide a complementary tool to the suite of existing MPEG standards, such as MPEG-7 Visual Descriptors. To build full visual search application this standard may be used jointly with other existing standards, such as MPEG Query Format, HTTP, XML, JPEG, JPSec, and JPSearch.

The Call for Proposals and the Evaluation Framework is publicly available. From a research perspective, it would be interesting to see how technologies submitted as an answer to the CfP compete with existing approaches and applications/services.
Call for Proposals: Internet Video Coding (IVC)

I reported previously about that and the final CfP for Internet Video Coding Technologies will be available around August 5th, 2011. However, you may have a look at the requirements already which can reveal some interesting issues the call will be about:

Real-time communications, video chat, video conferencing,
Mobile streaming, broadcast and communications,
Mobile devices and Internet connected embedded devices
Internet broadcast streaming, downloads
Content sharing.

Requirements fall into the following major categories:

IPR requirements
Technical requirements
Implementation complexity requirements

Clearly, this work item has an optimization towards IPR but others are not excluded. In particular,

It is anticipated that any patent declaration associated with the Baseline Profile of this standard will indicate that the patent owner is prepared to grant a free of charge license to an unrestricted number of applicants on a worldwide, non-discriminatory basis and under other reasonable terms and conditions to make, use, and sell implementations of the Baseline Profile of this standard in accordance with the ITU-T/ITU-R/ISO/IEC Common Patent Policy.

Further information you may find at the MPEG Web site, specifically under the hot newssection and the press release. Working documents of any MPEG standard so far can be found here. If you want to join any of these activities, the list of Ad-hoc Groups (AhG) is available here (soon also here) including the information how to join their reflectors.

Original Article:http://multimediacommunication.blogspot.com/ by Christian Timmerer

ImageCLEF's Wikipedia Retrieval Task Results

2011-07-27T01:10:00.001+03:00

ImageCLEF is the cross-language image retrieval track which is run as part of the Cross Language Evaluation Forum (CLEF) campaign. The ImageCLEF retrieval benchmark was established in 2003 with the aim of evaluating image retrieval from multilingual document collections. Images by their very nature are language independent, but often they are accompanied by texts semantically related to the image (e.g. textual captions or metadata). Images can then be retrieved using primitive features based on pixels with form the contents of an image (e.g. using a visual exemplar), abstracted features expressed through text or a combination of both. The language used to express the associated texts or textual queries should not a ect retrieval, i.e. an image with a caption written in English should be searchable in languages other than English.

ImageCLEF's Wikipedia Retrieval task provides a testbed for the systemoriented evaluation of visual information retrieval from a collection of Wikipedia images. The aim is to investigate retrieval approaches in the context of a large and heterogeneous collection of images (similar to those encountered on the Web) that are searched for by users with diverse information needs.
In 2011, ImageCLEF's Wikipedia Retrieval used a collection of over 237000 Wikipedia images that cover diverse topics of interest. These images are associated with unstructured and noisy textual annotations in English, French, and German.

Overall, based on the best run per group, as illustrated in the following Table, we are 4th out of 11 in MAP:

Based on the best run per group, as illustrated in the following Table, we are 4nd out of 11 in P@10:

JOB: postdoc in animation and graphics at Edinburgh

2011-07-27T00:43:00.001+03:00

Postdoctoral position in Robotics and Animation. The successful candidate is expected to have (or be near completion) a PhD in the area of computer animation and graphics and the candidate is expected to have strong mathematical skills in the area of optimization and control theory, and good programming skills. It is also preferable to have experience working in the area of machine learning or robotics and have some familiarity of concepts such as character animation, 3D physical simulation and machine learning techniques. The post is funded by an EPSRC project that focuses on developing state-of-the-art motion generation systems for robotic manipulation under uncertainty using concepts of topology space and data driven dimensionality reduction. The appointee will be responsible for direct implementation of character / humanoid control in physical simulators (Open Dynamics Engine, PhysX), simulation of deformable objects including strands and cloth, and control of robots such as the Kuka LWR and Nao Humanoids.

The post is available from 1st September 2011 until 28th February 2014

http://www.jobs.ed.ac.uk/vacancies/index.cfm?fuseaction=vacancies.detail&vacancy_ref=3014534&go=GO

Contact Taku Komura <tkomura <at> ed <dot> ac <dot> uk> for more details.

Google acquires PittPatt

2011-07-24T01:30:00.001+03:00

Original Article: http://computervisioncentral.com/content/google-acquires-pittpatt01724

Computer vision startup Pittsburgh Pattern Recognition, known as PittPatt, has replaced its web page with an announcement that it has been acquired by Google. The amount is not disclosed. According to PittPatt's statement, it "will continue to tap the potential of computer vision in applications that range from simple photo organization to complex video and mobile applications." PittPatt's showcase application is face detection and recognition. PittPatt is a Carnegie-Mellon University (CMU) spin-off.

The announcement:

Joining Google is the next thrilling step in a journey that began with research at Carnegie Mellon University's Robotics Institute in the 1990s and continued with the launching of Pittsburgh Pattern Recognition (PittPatt) in 2004. We've worked hard to advance the research and technology in many important ways and have seen our technology come to life in some very interesting products. At Google, computer vision technology is already at the core of many existing products (such as Image Search, YouTube, Picasa, and Goggles), so it's a natural fit to join Google and bring the benefits of our research and technology to a wider audience. We will continue to tap the potential of computer vision in applications that range from simple photo organization to complex video and mobile applications.
We look forward to joining the team at Google!
The team at Pittsburgh Pattern Recognition

Original Article: http://computervisioncentral.com/content/google-acquires-pittpatt01724

2 computer vision PhD places at Edinburgh

2011-07-24T01:26:00.001+03:00

Applications are invited for two fully funded PhD students to work in the School of Informatics on the following topics:

* knowledge transfer to automate learning visual models

* learning visual object categories from consumer and advertisement videos

* leveraging the structure of natural sentences to aid visual learning

Applicants must have:

* Master degree (preferably in Computer Science or Mathematics)

* Excellent programming skills; the projects involve programming in Matlab and C++

* Solid knowledge of Mathematics (especially algebra and statistics)

* Highly motivated

* Fluent in English, both written and spoken

* UK or EU nationality

* Experience in computer vision and/or machine learning is a plus (ideally a master thesis in a related field)

The School of Informatics at Edinburgh is one of the top-ranked departments of Computer Science in Europe and offers an exciting research environment. Edinburgh is a beautiful historic city with a high quality of life.

Starting date: January 2012 or later

The PhD work will be carried out under the supervision of Vittorio Ferrari. He is currently with ETH Zurich. He will move to the University of Edinburgh in December 2011 and build a new research group in Computer Vision. For an overview of his current research activities, please visit

http://www.vision.ee.ethz.ch/~calvin/

For pre-screening, please send applications to the email address below, including:

* complete CV

* title and abstract of your master thesis

* complete grades for all exams passed during both the bachelor and master (to obtain this position you need high grades, especially in mathematics and programming disciplines)

* the name and email address of one reference (preferably your master thesis supervisor)

* if you already have research experience, please include a publication list.

Do we need an alternative to peer-reviewed journals?

2011-07-18T20:47:00.002+03:00

Original Post http://arstechnica.com/science/news/2011/07/do-we-need-an-alternative-to-peer-reviewed-journals.ars

The past week has seen rather lively discussion about the scientific publishing industry and peer review. Peter Murray-Rust has produced a series of posts about his issues with the process (start here then work your way forward), Joe Pickrell described his problems with peer-reviewed journals at Genomes Unzipped, and Stuart Lyman has a letter to the editor in Nature Biotechnology (subscription required). (It's also a topic that we've considered in the past.) As Wired's Dan MacArthur put it, "it is a source of constant wonder to me that so many scientists have come to regard a system [the existing publication process] that actively inhibits the rapid, free exchange of scientific information as an indispensable component of the scientific process." So what's the problem, and what should (or can) we do about it?

Who gets to read the science?

Until the relatively recent advent of open-access publishing, readers have been expected to foot the costs of the publishing process. A year of a single journal can cost a library six-figure sums. Noninstitutional users can expect to be charged around $30 for a single article, as can academic users whose library doesn't subscribe to the Journal of Obscure Factoids. If you've spent your life in well-funded research institutes, this might not seem like an issue. But, for those at smaller schools or from less-affluent countries, this can be a substantial barrier to being able to participate in the exchange and dissemination of scientific ideas. These paywalls also stand between taxpayers and the research they've supported.

As Stuart Lyman's letter to Nature Biotech points out, the price of access has also become a problem for private sector research. The large pharmaceutical companies that used to have well-stocked libraries have downsized or shut them down as part of their relentless cost-cutting. For small or even medium-size companies, the costs of institutional subscriptions quickly adds up.

The access issue is the one that's seen the most progress, with the creation of open-access journals where the publication costs are met by the authors, not the readers (authors had been paying fees to publish in some journals anyway). The effort to make publicly funded discoveries publicly available has also been gaining ground. From 2008 onwards, recipients of NIH funding have been subject to NIH's Public Access Policy, which requires that any publications that arise from its funds appear in either open-access journals or be placed in PubMed Central within 12 months. Similar policies have been implemented by other national funding bodies and private foundations, as well as individual institutions.

Some publishers have made attempts to have Congress overturn NIH's policy. It's an understandable move; for-profit publishers fear for their bottom line, while other journals are published by scientific societies, many of which depend on subscription revenues for basic operations. But this revenue model may have been dying on its own. The bulk of scientific literature is consumed electronically rather than in hard copy. Sure, it used to be that disseminating new scientific ideas involved printing lots of copies and shipping them, but how true is that in 2011?

Paying for peer review

Part of the price of a journal goes to cover the process of peer review, which has also been the subject of criticism. It costs both time and money, and weeks or months can pass between submitting a paper and having it accepted. Reviewers have to be found, and they are expected to spend hours doing a thorough job without compensation.

Despite all this effort, there are worries that the process doesn't work any better than chance. A common criticism is that peer review is biased towards well-established research groups and the scientific status quo. Reviewers are unwilling to reject papers from big names in their fields out of fear, and they can be hostile to ideas that challenge their own, even if the supporting data is good. Unscrupulous reviewers can reject papers and then quickly publishing similar work themselves.

Alternatives to the current system have been examined, but MIT didn't think much of their experiment with open peer review, and Nature's testing of these waters didn't really pan out either. Nature did find overwhelming support from authors, who felt that open peer review improved their papers; a more recent study from the Publishing Research Consortium that we reported on found similar things. These comments indicate that abandoning peer review entirely isn't a viable solution. To some extent, it has already happened with the arXiv, which is filled with all sorts of crap that makes The Daily Mail's science pages seem reputable.

Beyond arranging for peer review, journals act as gatekeepers—they screen submissions for interest or importance as well as just the veracity of the work. That, too, has provoked a response. PLoS ONE attempts to take the first part out of the equation:

Too often a journal's decision to publish a paper is dominated by what the Editor/s think is interesting and will gain greater readership—both of which are subjective judgments and lead to decisions which are frustrating and delay the publication of your work. PLoS ONE will rigorously peer-review your submissions and publish all papers that are judged to be technically sound. Judgments about the importance of any particular paper are then made after publication by the readership (who are the most qualified to determine what is of interest to them).

The problem with this (from where I'm sitting) is that the sheer volume of publications is already almost impossible to manage, making a degree of selectivity valuable. There's always going to be a place for highly selective publishing outlets for work deemed "important"—that's just human nature.

But highly selective journals feed into a final problem area: metrics, impact, and tracking. For better or worse (and I think there's a very strong case for it being worse), academic career progression and research funding are explicitly tied to where a scientist publishes their work. This is done through the use of impact factors, which we've written about extensively (and critically) in the past.

They're a very imperfect measure. Journals that publish reviews as well as research articles can increase their impact factor, and publishing retractions or corrections does so as well. We have the tools to do a better job now, thanks to the move online. There have been experiments with algorithms like PageRank, and one could easily see something that works like Facebook's "like" or Google's "+1" being used. But as a researcher's funding success and promotion remain tied to their publications, what's to stop them from gaming the system? (I envision researchers organizing teams of undergrads to +1 their bibliography.)

Taking a more holistic view towards an individual's career would certainly solve this problem, and it's a solution I'm all in favor of. Until that happens though, I don't think we're going to see things change much.

Although publishing will remain critical, it's hard to escape the sense that it's increasingly trailing behind the scientific community. Twitter, FriendFeed, Mendeley, and now Google+ have become venues where serious discussion about scientific work takes place. We're already seeing friction at some conferences; not everyone is happy having their talk livetweeted, and the backchannel can be cruel to speakers at times. But social media isn't going anywhere, and neither is academic blogging.

Recognizing the legitimacy of these will be a critical challenge for academia, but it might happen organically as a younger cohort replaces the boomers currently running the show. Fixing peer review is something that shouldn't wait, though. Unfortunately, it's easier to say than to do; I don't have any ready suggestions for how.

Lightsaber + Kinect + robotic arm = JediBot

2011-07-18T19:32:00.001+03:00

Original Post http://www.extremetech.com/extreme/90204-lightsaber-kinect-robotic-arm-jedibot

By combining a dexterous robotic arm, the movement tracking capabilities of Microsoft’s Kinect sensor, and some clever software, students at Stanford University have created what can only be called a JediBot. The arm is equipped with a bright red foam-dampened lightsaber, but for all intents and purposes it is trained to kill the opponent: a student with a green lightsaber (shouldn’t it be blue?)

Basically, the robot arm is pre-programmed with a bunch of “attack moves” and it defends by using the Kinect to track the green lightsaber. To attack, JediBot performs a random attack move, and if it meets resistance — another lightsaber, a skull, some ribs — it recoils and performs another, seemingly random, attack. It can attack once every two to three seconds — so it isn’t exactly punishing, but presumably it would only require a little knob-tweaking to make it a truly killer robot.

To defend, the JediBot uses the Kinect sensor to pick the green lightsaber out of the background (that’s why it isn’t blue), and performs depth analysis to work out where it is in comparison to the robot’s lightsaber. If you watch the video, the tracking is remarkably fast, and it’s probably very hard to actually land a blow on the robot. A video of the JediBot is embedded below.

The JediBot was created during Stanford University’s three-and-a-half-week Experimental Robotics course. Other students on the course used similar robotic arms to draw, take photos, play golf, and even flip burgers (and add ketchup!) A video of these other robotic applications is embedded below the JediBot video.

After last month’s story about the robot that can debone a pork ham, and last week’s revelation that IBM Watson might soon be taking over the role of salespeople and technical support personnel, you have to wonder whether we humans will perform any physically arduous or taxing tasks in the future.

Original Post http://www.extremetech.com/extreme/90204-lightsaber-kinect-robotic-arm-jedibot

What Caricatures Can Teach Us About Facial Recognition

2011-07-16T12:01:00.001+03:00

Original Article: http://www.wired.com/magazine/2011/07/ff_caricature/all/1

Wired asked four top caricaturists to sketch the writer of this story. The results are shown here and throughout the story. To read about how writer Ben Austen reacted to the images, see the end of the story.
Photo: Joshua Anderson; caricature: Court Jones

Our brains are incredibly agile machines, and it,s hard to think of anything they do more efficiently than recognize faces. Just hours after birth, the eyes of newborns are drawn to facelike patterns. An adult brain knows it’s seeing a face within 100 milliseconds, and it takes just over a second to realize that two different pictures of a face, even if they’re lit or rotated in very different ways, belong to the same person. Neuroscientists now believe that there may be a specific region of the brain, on the fusiform gyrus of the temporal lobe, dedicated to facial recognition.

Perhaps the most vivid illustration of our gift for recognition is the magic of caricature—the fact that the sparest cartoon of a familiar face, even a single line dashed off in two seconds, can be identified by our brains in an instant. It’s often said that a good caricature looks more like a person than the person himself. As it happens, this notion, counterintuitive though it may sound, is actually supported by research. In the field of vision science, there’s even a term for this seeming paradox—the caricature effect—a phrase that hints at how our brains misperceive faces as much as perceive them.

Human faces are all built pretty much the same: two eyes above a nose that’s above a mouth, the features varying from person to person generally by mere millimeters. So what our brains look for, according to vision scientists, are the outlying features—those characteristics that deviate most from the ideal face we carry around in our heads, the running average of every visage we’ve ever seen. We code each new face we encounter not in absolute terms but in the several ways it differs markedly from the mean. In other words, to beat what vision scientists call the homogeneity problem, we accentuate what’s most important for recognition and largely ignore what isn’t. Our perception fixates on the upturned nose, rendering it more porcine, the sunken eyes or the fleshy cheeks, making them loom larger. To better identify and remember people, we turn them into caricatures.

Ten years ago, the science of facial recognition—until then a somewhat esoteric backwater of artificial-intelligence research—suddenly became a matter of national security. The hazy closed-circuit images of Mohamed Atta, taped breezing through an airport checkpoint in Portland, Maine, enraged Americans and galvanized policymakers to fund research into automated recognition systems. We all imagined that within a few years, as soon as surveillance cameras had been equipped with the appropriate software, each face in a crowd would stand out like a thumbprint, its unique features and configuration offering a biometric key that could be immediately checked against any database of suspects.

Pawan Sinha, director of the Sinha Laboratory for Vision Research at MIT, thinks caricature is the key to better computer vision. For his Hirschfeld Project, to be started this year, Sinha's lab will analyze hundreds of caricatures by dozens of different artists, in order to isolate the facial proportions that are most important for recognition. This chart shows some of the myriad measurements that might prove crucial, like distance from pupil to pupil, distance from bottom lip to chin, or the area of the forehead.

But now a decade has passed, and face-recognition systems still perform miserably in real-world conditions. It’s true that in our digital photo libraries, and now on Facebook, pictures of the same person can be automatically tagged and collated with some accuracy. Indeed, in a recent test of face-recognition software sponsored by the National Institute of Standards and Technology, the best algorithms could identify faces more accurately than humans do—at least in controlled settings, in which the subjects look directly at a high-resolution camera, with no big smiles or other displays of feature-altering emotion. To crack the problem of real-time recognition, however, computers would have to recognize faces as they actually appear on video: at varying distances, in bad lighting, and in an ever-changing array of expressions and perspectives. Human eyes can easily compensate for these conditions, but our algorithms remain flummoxed.

Given current technology, the prospects for picking out future Mohamed Attas in a crowd are hardly brighter than they were on 9/11. In 2007, recognition programs tested by the German federal police couldn’t identify eight of 10 suspects. Just this February, a couple that accidentally swapped passports at the airport in Manchester, England, sailed through electronic gates that were supposed to match their faces to file photos.

All this leads science to a funny question. What if, to secure our airports and national landmarks, we need to learn more about caricature? After all, it’s the skill of the caricaturist—the uncanny ability to quickly distill faces down to their most salient features—that our computers most desperately need to acquire. Better cameras and faster computers won’t be enough. To pick terrorists out of a crowd, our bots might need to go to art school—or at least spend some time at the local amusement park.

In the 19th century, law enforcement knew that exaggerated art could catch crooks. When New York’s Boss Tweed, on the lam in Spain, was finally arrested in 1876, he was identified not with the aid of a police sketch but with a Thomas Nast caricature from Harper’s Weekly. Today, though, most police departments use automated facial-likeness generators, which tend to create a bland, average face rather than a recognizable portrait of the guilty party. Paul Wright, the president of Identi-Kit, one of the most commonly used composite systems in the US, concedes that the main value of his product is in ruling out a large fraction of the population. “Half the people might say a composite sketch looks like Rodney Dangerfield, another half like Bill Clinton. But it’s not useless. It doesn’t look like Jack Nicholson.”

Visit the annual convention of the International Society of Caricature Artists and you’ll find people who describe their face-depiction skills in far less modest terms. Take Stephen Silver, who began his career 20 years ago as a caricaturist at Sea World and is now a character designer for TV animation studios. “If they used caricatures for police composites today,” Silver says, “people would be like, ‘What is this, a joke?’ But the cops would catch the guy. If I drew a caricature, the guy would be shit out of luck.”

Daniel Almariei's caricature of author Ben Austen
Photo: Joshua Anderson; caricature: Daniel Almariei

Silver is one of 188 artists from 13 different countries who attended the most recent ISCA gathering, in Las Vegas. Over five days, and sometimes late nights, these artists draw one another’s faces over and over again, often in orgiastic clusters, the artist-subject pairings shifting repeatedly and assuming every conceivable angle. The caricatures produced are eventually displayed and voted on by the attendees, with the first-place winner awarded a Golden Nosey trophy. Silver won the prize in 2000, and it’s easy to see why. As he scans a room, he can size up faces and get the drop on each at a glance.

“I don’t care how many wrinkles there are around the eye or if there’s stubble,” he says. “Those features aren’t going to help me. You know who a person is from basic shapes.” He spies a red-haired woman across the room, takes aim at her head. “Do you see how its meat is all on the outside?” he asks. “With the features crammed into the center?” Next his sights shift to an African-American woman drawing busily at a foldout table. Her head is actually tiny, Silver points out, but the span from her bottom lip to the base of her neck is immense.

New Version of img(Rummager)

2011-07-13T23:22:00.001+03:00

Several Bugs Fixed

1. CCDs Late Fusion bug fixed

2. Mpeg 7 Late Fusion bug fixed

3. Color Histograms problem fixed (thanks to Oge Marques)

4. AutoCorrelogram problem fixed (thanks to Oge Marques)

5. Search from local folder problem fixed

New Features

6. Visual Words Search now supports several weight and normalization methods (8 new methods - using SMART)

7. Color Visual Words (CoViWo) – Alpha version

8. New methods for custom sized codebooks

9. New method for dynamically sized codebooks

10. New “Create index files” methods

11. SURF as well as CoViWo features are now saved in binary files (for faster retrieval)

12. XML files are now more compact

13. Batch mode is even faster

14. Select the number of the results for the TrecFiles (in batch mode) (for example - don't include the entire database but only the first 1000 results)

Please note that there is known bug with local features (SURF), Visual Words and Color Visual Words (CoViWo). If an image does NOT contain any points of interest, img(Rummager) crashes. This bug is because of EmguCV (probably the same problem appears when using OpenCV).

http://savvash.blogspot.com/p/imgrummager.html

TsoKaDo

2011-07-13T01:15:00.001+03:00

Abstract

In this paper, a new visually based query expansion method for image retrieval from distributed web search engines is proposed. The innovation of this method lies in the fact that the effectiveness of image retrieval is improved because it is based on recursive query recommendation. Until now, the problem of retrieving images, very close to the seeker’s desires from web search engines, is growing as well as the continuous increase of confusing image information over the Internet. The method, described in this paper, proposes a web image search engine, called TsoKaDo, which at first, given a user’s query, parses images from the three most known search engines, e.g. Google, Bing and Ask. Then, it classifies them in C automatically computed classes using Content Based techniques and more specific the Color and Edge Directivity Descriptor (CEDD). Consequently, the most representative image of each class is compared, using CEDD again, with the results parsed from Flickr, searched with the same keyword. Finally the tags of the top-K images of Flickr are classified based on their semantic distance, and are proposed to the user in order to expand his query for better results.

Please note that this web application is an undergraduate project!!!!!!

Another project from the Duth Robotics Team

The paper is currently under review. I ‘ll post more details ASAP!!!

Lazaros T. Tsochatzidis, Athanasios C. Kapoutsis, Nikolaos I. Dourvas, Savvas A. Chatzichristofis, Yiannis S. Boutalis, “QUERY EXPANSION BASED ON VISUAL IMAGE CONTENT”, «5th Panhellenic Scientific Conference for Undergraduate and Postgraduate Students in Computer Engineering, Informatics, related Technologies and Applications», September 30 to October 1, 2011, Kastoria, Greece, Submitted for Publication

Visir tsokado.nonrelevant.net

If You’re Happy and You Know It - Facebook will detect it

2011-07-13T01:07:00.001+03:00

Does the internet know when you’re smiling? That’s a rhetorical question. Of course it can.Face.com, makers of a top notch facial recognition API, recently announced it was now capable of detecting the moods and expressions of people in photos it scans. Now, not only can the API tell who you are, it can say whether you were happy, sad, smiling, or even kissing. Face.com is the creator of the popular PhotoFinder andPhotoTagger apps on Facebook, so you may soon see that capability on the social network as well as among the 20,000 developers who use the Face.com API. In related news, Facebook (using its own software) has been automatically using facial recognition to tag photos you upload since December of last year. They’ve already prompted the use of such facial scanning 2.7 billion times in the past six months! Learn more about their push for automated tagging in the video below. Facial recognition has grown so sophisticated, and cheap, that it seems it will soon leave no photo untagged, no mood unrecorded. If that idea makes you uneasy, don’t worry, the social network of the future knows exactly how you feel.

Facebook quietly rolled out their in-house facial recognition (Photo-Tag Suggest) in the US last December, allowing users to tag their friends, teaching the social network who was who. Soon there after, Facebook could automatically suggest who was in each picture, making tagging quick and easy. It’s a pretty awesome feature, and as of early June it was available “in most countries.”On June 30th, Facebook announced it had prompted its 750 million active users 2.7 billion times to try the automated tagging process, often with the rather ambiguous box on your homepage labeled “Photos are better with friends.” Naturally some privacy activists groups are crying foul, worrying that although the Photo Tag Suggest only works on your friends Facebook is collecting huge amounts of data on our appearance. ABC News has more:

http://singularityhub.com/2011/07/12/if-youre-happy-and-you-know-it-facebook-will-detect-it/

Multimodal Image Retrieval: ImageCLEF and beyond

2011-07-10T23:22:00.001+03:00

Speaker: Dr. Jayashree Kalpathy-Cramer, OHSU

THE NEW TEST IMAGES

2011-07-10T12:08:00.001+03:00

http://www.imagecompression.info/test_images/

The images historically used for compression research (lena, barbra, pepper etc...) have outlived their useful life and its about time they become a part of history only. They are too small, come from data sources too old and are available in only 8-bit precision.

These high-resolution high-precision images have been carefully selected to aid in image compression research and algorithm evaluation. These are photographic images chosen to come from a wide variety of sources and each one picked to stress different aspects of algorithms. Images are available in 8-bit, 16-bit and 16-bit linear variations, RGB and gray.

Download

RGB 8 bit (330 MB), RGB 16 bit (787 MB), RGB 16 bit linear (626 MB)
Gray 8 bit (103 MB), Gray 16 bit (285 MB), Gray 16 bit linear (207 MB)

You are encouraged to use these images for image compression research and algorithm evaluation. Suggestions for further improvements are always welcome.

Preview: click on the images to enlarge, you can enlarge multiple images at same time. You can also checkout results of various lossless and lossy compression algorithms on these images.

artificial
3072x2048
Computer generated using 3D modeling and ray-tracing.

big_building
7216x5412
Hasselblad H3D II-39

big_tree
6088x4550
Leaf Aptus 65

deer
4043x2641
Fuji Provia 100, film
(Not available in linear sets)

fireworks
3136x2352
Olympus E-330

flower_foveon
2268x1512

hdr
3072x2048
Leaf Cantare

These Images are available without any prohibitive copyright restrictions.

These images are (c) there respective owners. You are granted full redistribution and publication rights on these images provided:
1. The origin of the pictures must not be misrepresented; you must not claim that you took the original pictures. If you use, publish or redistribute them, an acknowledgment would be appreciated but is not required.
2. Altered versions must be plainly marked as such, and must not be misinterpreted as being the originals.
3. No payment is required for distribution of this material, it must be available freely under the conditions stated here. That is, it is prohibited to sell the material.
4. This notice may not be removed or altered from any distribution.

Acknowledgments

A lot of people contributed a lot of time and effort in making this test set possible. Thanks to everyone who shared their opinion in any of the discussions online or by email. Thanks to Axel Becker, Thomas Richter and Niels Fröhling for their extensive help in picking images, running all the various tests etc... Thanks to Pete Fraser, Tony Story, Wayne J. Cosshall, David Coffin, Bruce Lindbloom, rawsamples.ch and raw.fotosite.pl for the images which make up this set.

http://www.imagecompression.info/test_images/

Google Similar Images: I think I'll let the screenshot speak for itself–Part 2

2011-07-07T02:04:00.001+03:00

1. WOW- My girlfriend is a JEDI!!!!!

2. Do I look like HER?????

send me your Google Similar stories at savvash@gmail.com

Google Similar Images: I think I'll let the screenshot speak for itself

2011-07-07T01:27:00.001+03:00

More details about Google Visually Similar Images Soon.

MMM2012

2011-07-07T01:17:00.001+03:00

The 18th International MultiMedia Modeling Conference (MMM2012)
January 4-6, 2012 - Klagenfurt University, Klagenfurt, Austria.

The International MultiMedia Modeling (MMM) Conference is a leading international conference (http://mmm2012.org) for researchers and industry practitioners to share their new ideas, original research results and practical development experiences from all MMM related areas.
The conference calls for research papers reporting original investigation results and demonstrations in, but not limited to, the following areas related to multimedia modeling technologies and applications:

1. Multimedia Content Analysis
1.1 Multimedia Indexing
1.2 Multimedia Mining
1.3 Multimedia Abstraction and Summarization
1.4 Multimedia Annotation, Tagging and Recommendation
1.5 Multimodal Analysis for Retrieval Applications
1.6 Semantic Analysis of Multimedia and Contextual Data
1.7 Multimedia Fusion Methods
1.8 Media Content Browsing and Retrieval Tools

2. Multimedia Signal Processing and Communications
2.1 Media Representation and Algorithms
2.2 Audio, Image, Video Processing, Coding and Compression
2.3 Multimedia Security and Content Protection
2.4 Multimedia Standards and Related Issues
2.5 Advances in Multimedia Networking and Streaming
2.6 Multimedia Databases, Content Delivery and Transport
2.7 Wireless and Mobile Multimedia Networking

3. Multimedia Applications and Services
3.1 Multi-Camera and Multi-View Systems
3.2 Virtual Reality and Virtual Environment
3.3 Real-Time and Interactive Multimedia Applications
3.4 Mobile Multimedia Applications
3.5 Multimedia Web Applications
3.6 Interactive Multimedia Authoring Personalization
3.7 Sensor Networks (Video Surveillance, Distributed Systems)
3.8 Emerging Trends (e-learning, e-Health, Social Media, Multimedia Collaboration, etc.)

Paper Submission Guidelines:
============================
Papers should be no more than 10-12 pages in length (demo papers 3 pages), conforming to the formatting instructions of Springer Verlag, LNCS series (http://www.springer.com/lncs). Papers will be judged by an international program committee based on their originality, significance, correctness and clarity.
All papers should be submitted electronically in PDF format through the EasyChair submission system (https://www.easychair.org/conferences/?conf=mmm2012). The review process is single-blind, therefore please do not conceal authors’ identities from reviewers. To publish the paper in the conference, one of the authors needs to register and present the paper in the conference.

Important Dates:
================
Submission of full papers: July 22, 2011
Notification of acceptance: September 19, 2011
Camera-ready papers due: October 10, 2011
Author registration: October 10, 2011
Conference: January 4-6, 2012

For more information, please visit http://mmm2012.org

PROMISE Winter School 2012 - Information Retrieval meets Information Visualization

2011-07-07T01:12:00.001+03:00

Zinal, Valais - Switzerland
23 - 27 January 2012

The aim of the Promise Winter School on information retrieval and information visualization is to give participants a grounding in the core topics that constitute the multidisciplinary area of Multilingual Information Retrieval. The school is a week-long event consisting of guest lectures from invited speakers who are recognized experts in the field. The School is intended for PhD students, Masters students or senior researchers such as post-doctoral researchers form the fields of information visualization and information retrieval and related fields.

General Chair

Tiziana Catarci, Sapienza, University of Rome, Italy

Program Commitee

Maristella Agosti, University of Padua, Italy
Nicola Ferro, University of Padua, Italy
Henning Müller, University of Applied Sciences Western Switzerland, Switzerland
Guiseppe Santucci, Sapienza, University of Rome, Italy

Publicity Chair

Pamela Forner, Centre for the Evaluation of Language and Communication Technologies (CELCT), Italy
Hélène Mazo, Evaluations and Language resources Distribution Agency (ELDA), France

Local Organization

Alexandre Cotting, University of Applied Sciences Western Switzerland, Switzerland
Henning Müller, University of Applied Sciences Western Switzerland, Switzerland

Contacts

For any information please contact winter-school[at] promise-noe.eu

http://www.promise-noe.eu/events/winter-school-2012/

SiftGPU: A GPU Implementation of Scale Invariant Feature Transform (SIFT)

2011-07-06T18:51:00.001+03:00

http://www.cs.unc.edu/~ccwu/siftgpu/ - Changchang Wu

SIFT Implementation

SiftGPU is an implementation of SIFT [1] for GPU. SiftGPU processes pixels parallely to build Gaussian pyramids and detect DoG Keypoints. Based on GPU list generation[3], SiftGPU then uses a GPU/CPU mixed method to efficiently build compact keypoint lists. Finally keypoints are processed parallely to get their orientations and descriptors.

SiftGPU is inspired by Andrea Vedaldi's sift++[2] and Sudipta N Sinha et al's GPU-SIFT[4] . Many parameters of sift++ ( for example, number of octaves, number of DOG levels, edge threshold, etc) are also available in SiftGPU. The shader programs are dynamically generated according to the parameters that user specified.

SiftGPU also includes a GPU exhaustive/guided sift matcher SiftMatchGPU. It basically multiplies the descriptor matrix on GPU and find closest feature matches on GPU. Both GLSL and CUDA implementations are provided.

Requirements

SiftGPU requires a high-end GPU (like nVidia 8800) that has a large graphic memory and supports dynamic branching. GLSL for OpenGL is used by default, and CUDA is provided as an alternative for nVidia graphic cards. Haven't fully tested on ATI, but the GLSL shaders did pass the AMD Shader Analyzer (Catalyst 8.12), it should be working.

SiftGPU uses GLEW 1.51, DevIL1.77 (can be disabled), GLUT(viewer only), and CUDA(optional). You'll need to make sure that your system has all the dependening libraries of corresponding versions. To update the libaries, you'll need to replace the header files in SiftGPU\Include\, and the corresponding binaries.

NOTE FOR CUDA : 1. The thread block setting is currently tuned on nVidia GTX 8800. It may not be optimized for other GPUs. 2. The CUDA version is not compiled by default. You need to define CUDA_SIFTGPU_ENABLED to the compiler and recompile the package. For VS2010 users, you can just use SiftGPU_CUDA_Enabled solution.

Download

SiftGPU-V371 (5.0MB; Including code, manual , windows binary and some test images) Want to cite SiftGPU?
You might be interested in the Matlab Versions mex'd by Adam Chapman and by Parag. K. Mital

SimpleSIFT.cpp gives some examples of using SiftGPU and SiftMatchGPU.
Previous versions of SiftGPU can be found through this link. A complete change list can be found here.

Some minor updates since V360
1. Converted the MSVC Solution to Visual Studio V2010 and tested CUDA4 (6/2011)
2. Automatic switching from OpenGL to CUDA when OpenGL is not supported (1/2011)
3. Dropped the indirect data transfer path CPU->GL->CUDA (1/2011)
4. Dropped the CG implementation to simplify maintance (1/2011)
Some previous changes
6. Added device selection for Multi-threading (Check the example at MultiThreadSIFT.cpp).
5. Used SSE to speedup the descriptor normalization step for the OpenGL implementation.
4. Added CUDA-based SiftGPU/SiftMatchGPU implementation. See Figure below for the speed.
3. Added OpenGL-based sift matching implementation, check example #7 in manual. (Thanks to Zach)
2. Added function to compute descriptors for user-specified keypoints, check example #6 in manual.
1. Improved speed by %50 compared with V293. Look here for experiment details and explanations

Evaluation

Below is the evaluation of the speed of V340 on different image sizes. "-fo -1" means using upsampled image. "-glsl" uses GLSL and "-cuda" uses CUDA (The experiment images are all resized from this image) .

System : nVidia 8800GTX, 768MB, Driver 182.08, Windows XP, Intel 3G P4 CPU, 3.5G RAM. (V311 Speed)

Below is the comparision with Lowe's SIFT on box.pgm using the comparision code from Vedaldi's SIFT .

References

[1]   D. G. Lowe. Distinctive image features from scale-invariant keypoints . International Journal of Computer Vision, November 2004.
[2]   A. Vedaldi. sift++, http://vision.ucla.edu/~vedaldi/code/siftpp/siftpp.html.
[3]   G. Ziegler, et al. GPU point list generation through histogram pyramids. In Technical Report, June 2006.
[4]   Sudipta N Sinha, Jan-Michael Frahm, Marc Pollefeys and Yakup Genc, "GPU-Based Video Feature Tracking and Matching ",
        EDGE 2006, workshop on Edge Computing Using New Commodity Architectures, Chapel Hill, May 2006

4th International Conference on Agents and Artificial Intelligence

2011-07-05T01:53:00.001+03:00

ICAART (4th International Conference on Agents and Artificial Intelligence - http://www.icaart.org/) has an open call for papers, whose deadline is set for July 28, 2011. We hope you can participate in this conference by submitting a paper reflecting your current research in any of the following areas:

- Artificial Intelligence

- Agents

The conference will be sponsored by the Institute for Systems and Technologies of Information, Control and Communication (INSTICC) and held in cooperation with the Portuguese Association for Artificial Intelligence (APPIA), the Spanish Association for Artificial Intelligence (AEPIA) and the Association for the Advancement of Artificial Intelligence (AAAI). INSTICC is member of the Foundation for Intelligent Physical Agents (FIPA), Workflow Management Coalition (WfMC) and the Object Management Group (OMG).

ICAART would like to become a major point of contact between researchers, engineers and practitioners interested in the theory and applications in these areas. BBCQ Informatics applications are pervasive in many areas of Artificial Intelligence and Distributed AI, including Agents and Multi-Agent Systems. This conference intends to emphasize this connection, therefore, authors are invited to highlight the benefits of Information Technology (IT) in these areas. Ideas on how to solve problems using agents and artificial intelligence, both in R&D and industrial applications, are welcome. Papers describing advanced prototypes, systems, tools and techniques and general survey papers indicating future directions are also encouraged.

The conference program features a number of Keynote Lectures to be delivered by distinguished world-class researchers, including those listed below.

All accepted papers (full, short and posters) will be published in the conference proceedings, under an ISBN reference, on paper and on CD-ROM support.

A short list of presented papers will be selected so that revised and extended versions of these papers will be published by Springer-Verlag in a CCIS Series book.

A short list of papers will be selected for publication in a special issue of JOPHA - Journal of Physical Agents.

The proceedings will be submitted for indexation by Thomson Reuters Conference Proceedings Citation Index (ISI), INSPEC, DBLP and Elsevier Index (EI).

Best paper awards will be distributed during the conference closing session. Please check the website for further information (http://www.icaart.org/best_paper_awards.asp).

All papers presented at the conference venue will be available at the SciTePress Digital Library (http://www.scitepress.org/DigitalLibrary/). SciTePress is member of CrossRef (http://www.crossref.org/).

We also would like to highlight the possibility to submit to the following Satellite Workshop:

- 2nd International Workshop on Semantic Interoperability (IWSI)

Workshops, Special sessions as well as tutorials dedicated to other technical/scientific topics are also envisaged: companies interested in presenting their products/methodologies or researchers interested in holding a tutorial are invited to contact the conference secretariat. Workshop chairs and Special Session chairs will benefit from logistics support and other types of support, including secretariat and financial support, to facilitate the development of a valid idea.

Please check further details at the ICAART conference website (http://www.icaart.org).

Should you have any question please don't hesitate contacting me.

ICAART 2012 will be held in conjunction with ICPRAM (http://www.icpram.org/) and ICORES 2012 (http://www.icores.org/) in Vilamoura, Algarve, Portugal. Registration to ICAART will enable free access to the ICPRAM and ICORES conferences (as a non-speaker).

Card.io Lets You Pay on Mobile by Holding a Credit Card Up to the Phone

2011-07-04T01:44:00.001+03:00

Card.io, a new San Francisco-based startup led by two former AdMob employees, Mike Mettler and Josh Bleecher, is introducing a revolutionary idea that could transform mobile commerce: make it easier to pay. But how the company has accomplished this is a feat that will feel more like magic to the everyday mobile user. With card.io, you simply hold your credit card up to the phone. The software then "sees" the card information using the phone's camera and the payment is processed. No typing required!

To get the technology into the hands of those who need it most, card.io is targeting iOS developers at launch, specifically those in the e-commerce, local, ticketing, travel and daily deals space.

Card Scanning is Very Accurate, Says Company

The company has been in existence for only nine months, six of which were spent building card.io'score technology, the computer vision and machine learning algorithms which it uses to read the numbers of a credit card. Unlike several other check-scanning and business card scanning software programs, card.io doesn't use humans to verify the accuracy of scans - everything is programmatic. Of course this means that the scans themselves have to be highly accurate, and Mettler says they are.

However, the company wouldn't provide exact percentages here, only that the "vast majority" of scans should be accurate. But that's where the machine learning aspect comes into play. The more data that's processed, the better the software performs because it learns and improves over time.

Once the credit card information is entered, the developer can then continue to process the payment using their own merchant account as usual. Although card.io will be looking for merchant partners going forward, that's not the service it's offering today. Also of note, all the data card.io handles is secured using 128 bit-SSL and the service never stores card images on the phone or on the company's servers.

Going After E-Commerce, Not Point-of-Sale

Using technology to input the credit card details into a mobile device may seem like a step backwards when positioned alongside other upcoming mobile advances like NFC, a wireless technology that lets you pay for real-world goods with just a tap.

But NFC requires a special chip in handsets, and currently, few phones on the market offer this. It's still years out from mainstream adoption. Meanwhile, everyone has credit cards and these plastic, physical cards won't disappear anytime soon. Most importantly, card.io is not trying to compete with NFC or other innovations at the point-of-sale - it's going after the e-commerce market.

With a new software development kit (SDK) available now, the iOS (iPhone, iPad and iPod Touch) developers accepted into the company's private beta can integrate the technology into their own app. Initially, as noted above, card.io is most interested in developers working in the e-commerce, local, ticketing, travel and daily deals space. It is already working with a few companies here, including MogoTix for event tickets, TaskRabbit for local services and SamaSource for donations.

Card.io received $1 million in seed funding in January, led by former eBay exec Michael Dearing of Harrison Metal. Other investors include Jeff Clavier and Charles Hudson of SoftTech VC, Manu Kumar of K9 Ventures, Alok Bhanot (former VP, Risk Technology at PayPal), and Omar Hamoui (CEO/founder of AdMob).

iOS developers interested in joining the private beta have to plead their case here.

http://www.readwriteweb.com/mobile/2011/06/cardio-lets-you-pay-on-mobile-by-holding-credit-card-up-to-phone.php

DeepShot: Computer vision app for computer-smartphone communication

2011-07-04T01:39:00.001+03:00

This post by Computer Vision Central has been reprinted from Computer Vision Central's blog

Google Research and MIT CSAIL have developed a method for transferring an application's work state between a computer and a mobile phone using computer vision. The user can take an image of the computer screen using the mobile phone camera; the Deep Shotapp on the phone then identifies the current webpage on the computer and communicates with the computer to determine the URI of the application. For many web-based applications, the URI specifies both the application and the application state. Deep Shot also supports transfer in the other direction: an image of the computer display taken with the mobile phone is used to identify the computer to the phone. Deep Shot requires installation of software on both the computer and the phone. More information is available on Popular Science.

7th INTERNATIONAL SUMMER SCHOOL ON PATTERN RECOGNITION (ISSPR)

2011-07-03T11:07:00.001+03:00

4-9 SEPTEMBER 2011, Plymouth, UK

http://pro.expressemail.in/link.php?M=1048308&N=3119&L=707&F=T

Registration deadline: 11th July, 2011

In 2010, the 6th ISSPR School held at Plymouth was a major success with over 90 participants. The major focus of 2011 summer school includes:

- Providing participants with knowledge and recommendations on how to develop and use pattern recognition tools for a broad range of applications.

10 Corporate Scholarships are available towards discounted registration fee for students till 11th July, 2011 so this is an excellent opportunity for participants to register at an affordable cost. The fee includes registration and accommodation plus meals at the event. The registration process is online through the school website www.patternrecognitionschool.com which has further details on registration fees. Please note that the number of participants registering each year at the summer school is high with a limited number of seats available, and therefore early registration is highly recommended.

Lytro - The Start of a Picture Revolution

2011-06-25T08:27:00.001+03:00

Article from http://blog.lytro.com/

The Journey
Today, I am proud to announce the launch of Lytro and share our plans to bring an amazing new kind of camera to the consumer market.

This journey started for me eight years ago when I was in the PhD program at Stanford University. I loved photography then as I do now, but I was frustrated and puzzled by the apparent limitations of cameras. For example, I remember trying to take photos of Mei-Ahn, the five-year-old daughter of a close friend, but because she was so full of life, it was nearly impossible to capture the fleeting moments of her smile or perfectly focus the light in her eyes.

That experience inspired me to start the research that became my dissertation on light field photography, which had capabilities beyond what I could have ever hoped for. The journey soon accelerated with a full-body plunge into the world of entrepreneurship, with a dream to share this new technology with the world.

Today
I am thrilled to finally draw back the curtain and introduce our new light field camera company, one that will forever change how everyone takes and experiences pictures. Lytro’s company launch is truly the start of a picture revolution.

What began in a lab at Stanford University has transformed into a world-class company, forty-four people strong, sparkling with talent, energy and inspiration. It has taken a lot of hard work, late nights and tireless dedication to get Lytro to this point. I want to thank the entire team for their remarkable contributions, spirit, and camaraderie. I want to especially thank the very first believers: Colvin, Tim and Alex, the original magic engine of the company, and Manu, Charles and Allen for personally doing so much to help build this company. Besides the Lytro team, I want to thank my family, and my fiancé Yi (pictured above) for their continued support, confidence, and love.

We have something special here. Our mission is to change photography forever, making conventional cameras a thing of the past. Humans have always had a fundamental need to share our stories visually, and from cave paintings to digital cameras we have been on a long search for ways to make a better picture. Light field cameras are the next big step in that picture revolution.

The Future
Today is a big day for Lytro, but I believe it is just the beginning of a bright and exciting future. Photographers and casual shooters alike will be able to create and share new living pictures. I believe that as people begin to use light field cameras, we will see an explosion in new kinds of photographic art. It will be another wonderful journey to see how people use light field cameras, see where these new living pictures travel, and discover how each person chooses to take this revolution.

Welcome to Lytro! I hope you’ll follow us on the Lytro Blog, so we can keep you updated about the introduction of our first Lytro camera.

Ren Ng
Founder and CEO of Lytro

Learning Invariance through Imitation

2011-06-23T02:08:00.001+03:00

Graham W. Taylor, Ian Spiro, Chris Bregler and Rob Fergus

To appear at CVPR 2011, Colorado Springs, USA June 21-23 (download pdf) (supplementary material)

Sample retrieval results. Each row is a query. We select a test image (column 1) and find its 10 nearest neighbors using our method which we call Pose Sensitive Embedding (PSE). The blue text in each image indicates seed id (left) and distance (in embedded space) from the query (right).

Non-scientific abstract (for geeks and non-geeks)

Computer vision has hit the mainstream with applications such as cars that detect pedestrians, motion capture for animation, and applications that let you cash a cheque by snapping a picture from your mobile phone. A great example of computer vision in the consumer market is Microsoft's Kinect gaming system which can accurately detect the pose of one or more individuals allowing gameplay to be controlled using just the body. Such a system must be able to detect pose reliably under a wide variety of conditions - different players, unusual clothing, poor lighting, cluttered backgrounds, and other sources of variation. One way that we could perform pose estimation is keeping around a large database of examples of people in a variety of poses along with labels indicating the configuration of the body in 2D or 3D. When presented with a new example (without labels) we can compare it against the database to find the best match. We then can assign the labels of the best match to the new example. However, the matching (or similarity) problem is a very tough one - especially due to the large amount of input variability due to the factors described above. If we had many examples of people in similar pose but under differing conditions, we could use machine learning to construct an algorithm that matches based on the important information (e.g. pose) and ignores the distracting information (e.g lighting, clothing, background, etc.). But how do we collect such data? In a somewhat unusual move for computer scientists, we turned to the Dutch progressive-electro band C-Mon and Kypski. Their music video/crowdsourcing project "One Frame of Frame" asks people on the web to replace one frame of the band's music video for the song "More or Less" with a capture from a webcam. A visitor to the band's website is shown a single frame of the video and asked to perform an imitation in front of the camera. The new contribution is spliced into the video which updates once an hour. This turns out to be the perfect data source for learning an algorithm to compute similarity based on pose. Armed with the band's data and a few machine learning tricks up our sleeves, we built a system that is highly effective at matching people in similar pose but under widely different settings.

Scientific abstract (for geeks)

Supervised methods for learning an embedding aim to map high-dimensional images to a space in which perceptually similar observations have high measurable similarity. Most approaches rely on binary similarity, typically defined by class membership where labels are expensive to obtain and/or difficult to define. In this paper we propose crowd-sourcing similar images by soliciting human imitations. We exploit temporal coherence in video to generate additional pairwise graded similarities between the user-contributed imitations. We introduce two methods for learning nonlinear, invariant mappings that exploit graded similarities. We learn a model that is highly effective at matching people in similar pose. It exhibits remarkable invariance to identity, clothing, background, lighting, shift and scale.

Schematic of our approach. We assume for each frame of video, there exists an unobserved low-dimensional representation of pose, Z. A seed image is generated by mapping from pose space to pixels, X, through an unobserved interpretation function. Our method learns a nonlinear embedding, f(X|θ) which approximates Zwith a low-dimensional vector. In the example above, users are asked to imitate seed images taken from a music video (http://oneframeoffame.com).

http://movement.nyu.edu/imitation/

Intel announces Haswell's processor instructions

2011-06-21T03:01:00.001+03:00

http://computervisioncentral.com/content/intel-announces-haswells-processor-instructions01665

Intel has announced new processor instructions for the Haswell chip architecture that would be useful for image and video processing. According to an Intel Blog, the target applications include face detection, hash generation, and database manipulation. For example, the new floating-point-multiply-accumulate instructions "operate on scalar, 128-bit packed single and double precision data types, and 256-bit packed single and double-precision data types."

Intel's processor improvements come in a 2-year "tick-tock" succession of architecture improvements (tick) and process shrinks (tock). The current generation processor is the Sandy Bridge, which is followed by Ivy Bridge. Haswell is the newest architecture definition after Ivy Bridge.

3-D movie shows what happens in the brain as it loses consciousness

2011-06-20T17:08:00.001+03:00

http://www.manchester.ac.uk/aboutus/news/display/?id=7143

University of Manchester researchers have for the first time been able to watch what happens to the brain as it loses consciousness.

Using sophisticated imaging equipment they have constructed a 3-D movie of the brain as it changes while an anaesthetic drug takes effect.

Brian Pollard, Professor of Anaesthesia at Manchester Medical School, will tell the European Anaesthesiology Congress in Amsterdam today (Saturday) that the real-time 3-D images seemed to show that losing consciousness involves a change in electrical activity deep within the brain, changing the activity of certain groups of nerve cells (neurons) and hindering communication between different parts of the brain.

He said the findings appear to support a hypothesis put forward by Professor Susan Greenfield, of the University of Oxford, about the nature of consciousness itself. Prof Greenfield suggests consciousness is formed by different groups of brain cells (neural assemblies), which work efficiently together, or not, depending on the available sensory stimulations, and that consciousness is not an all-or-none state but more like a dimmer switch, changing according to growth, mood or drugs. When someone is anaesthetised it appears that small neural assemblies either work less well together or inhibit communication with other neural assemblies.

Professor Pollard, whose team is based at Manchester Royal Infirmary, said: “Our findings suggest that unconsciousness may be the increase of inhibitory assemblies across the brain’s cortex. These findings lend support to Greenfield’s hypothesis of neural assemblies forming consciousness.”

The team use an entirely new imaging method called “functional electrical impedance tomography by evoked response” (fEITER), which enables high-speed imaging and monitoring of electrical activity deep within the brain and is designed to enable researchers to measure brain function.

The new device was developed by a multidisciplinary team drawn from the Schools of Medicine and Electrical and Electronic Engineering at The University of Manchester, led by Professor Hugh McCann and with support from a Wellcome Trust Translation Award.

The machine itself is a portable, light-weight monitor, which can fit on a small trolley. It has 32 electrodes that are fitted around the patient’s head. A small, high-frequency electric current (too small to be felt or have any effect) is passed between two of the electrodes, and the voltages between other pairs of electrodes are measured in a process that takes less than one-thousandth of a second.

An ‘electronic scan’ is therefore carried out and the machine does this whole procedure 100 times a second. By measuring the resistance to current flow (electrical impedance), a cross-sectional image of the changing electrical conductivity within the brain is constructed. This is thought to reflect the amount of electrical activity in different parts of the brain. The speed of the response of fEITER is such that the evoked response of the brain to external stimuli, such as an anaesthetic drug, can be captured in rapid succession as different parts of the brain respond, so tracking the brain’s processing activity.

“We have looked at 20 healthy volunteers and are now looking at 20 anaesthetised patients scheduled for surgery,” said Professor Pollard. “We are able to see 3-D images of the brain’s conductivity change, and those where the patient is becoming anaesthetised are most interesting.

“We have been able to see a real time loss of consciousness in anatomically distinct regions of the brain for the first time. We are currently working on trying to interpret the changes that we have observed, as we still do not know exactly what happens within the brain as unconsciousness occurs, but this is another step in the direction of understanding the brain and its functions.”

The team at Manchester is one of many worldwide investigating electrical impedance tomography (EIT), but this is its first application to anaesthesia. Professor Pollard said that a huge amount of research still needed to be done to fully understand the role EIT could play in medicine.

“If its power can be harnessed, then it has the potential to make a huge impact on many areas of imaging in medicine,” he said. “It should help us to better understand anaesthesia, sedation and unconsciousness, although its place in medicine is more likely to be in diagnosing changes to the brain that occur as a result of, for example, head injury, stroke and dementia.

“The biggest hurdle is working out what we are seeing and exactly what it means, and this will be an ongoing challenge.”

http://www.manchester.ac.uk/aboutus/news/display/?id=7143

Automatic Illustration with Cross-media Retrieval in Large-scale Collections

2011-06-19T13:23:00.001+03:00

Filipe Coelho, Cristina Ribeiro - CBMI 2011

Abstract:

In this paper, we approach the task of finding suit-able images to illustrate text, from specific news stories to more generic blog entries. We have developed an automatic illustration system supported by multimedia information retrieval, that analyzes text and presents a list of candidate images to illustrate it. The system was tested on the SAPO-Labs media collection, containing almost two million images with short descriptions, and the MIRFlickr-25000 collection, with photos and user tags from Flickr. Visual content is described by the Joint Composite Descriptor and indexed by a Permutation-Pre x Index. Illustration is a three-stage process using textual search, score filtering and visual clustering. A preliminary evaluation using exhaustive and approximate visual searches demonstrates the capabilities of the visual descriptor and approximate indexing scheme used.

Slides: http://www.inescporto.pt/~fcoelho/web/_media/files/slidescbmi11.pdf

Paper: http://www.inescporto.pt/~fcoelho/web/_media/files/cbmi11.pdf

The Cell: An Image Library

2011-06-19T04:27:00.001+03:00

The Cell: An Image Library™ is a freely accessible, easy-to-search, public repository of reviewed and annotated images, videos, and animations of cells from a variety of organisms, showcasing cell architecture, intracellular functionalities, and both normal and abnormal processes. The purpose of this database is to advance research, education, and training, with the ultimate goal of improving human health.

This library is a public and easily accessible resource database of images, videos, and animations of cells, capturing a wide diversity of organisms, cell types, and cellular processes. The purpose of this database is to advance research on cellular activity, with the ultimate goal of improving human health.

Cells, the building blocks of tissues, undergo dramatic dynamic rearrangements and changes in shape and motility during our lifetimes; abnormalities in these processes underlie numerous human diseases. It is important that scientists and clinicians fully appreciate the structure and dynamic behavior of cells, including cells from diverse organisms, to make advancements to human health.

The Cell includes images acquired from historical and modern collections, publications, and by recruitment.

This Image Library is a repository for images and movies of cells from a variety of organisms. It demonstrates cellular architecture and functions with high quality images, videos, and animations. This comprehensive and easily accessible Library is designed as a public resource first and foremost for research, and secondarily as a tool for education. The long-term goal is the construction of a library of images that will serve as primary data for research.

The Library effort represents not only the creation of the electronic infrastructure, but also a systematic protocol for acquisition, evaluation, annotation, and uploading of images, videos, and animations.

http://cellimagelibrary.org/

Content Based Image Retrieval Using Visual-Words Distribution Entropy

2011-06-19T03:50:00.001+03:00

Savvas A. Chatzichristofis, Chryssanthi Iakovidou, and Yiannis S. Boutalis

Abstract.

Bag-of-visual-words (BOVW) is a representation of images which is built using a large set of local features. To date, the experimental results presented in the literature have shown that this approach achieves high retrieval scores in several benchmarking image databases because of their ability to recognize objects and retrieve near-duplicate (to the query) images. In this paper, we propose a novel method that fuses the idea of inserting the spatial relationship of the visual words in an image with the conventional Visual Words method. Incorporating the visual distribution entropy leads to a robust scale invariant descriptor. The experimental results show that the proposed method demonstrates better performance than the classic Visual Words approach, while it also outperforms several other descriptors from the literature.

This paper will be presented at

5th International Conference on Computer Vision / Computer Graphics Collaboration Techniques and Applications http://acivs.org/mirage2011/

Terrier 3.5 released

2011-06-19T03:45:00.001+03:00

Terrier, IR Platform v3.5 - 16/06/2011

http://terrier.org/

Terrier 3.5, the next version of the open source IR platform from the University of Glasgow (Scotland) has been released.

Significant update: Added Document-at-a-time (DAAT) retrieval for large indices; Refactored tokenisation for enhanced multi-language support; Upgraded Hadoop support to version 0.20 (NB: Terrier now requires Java 1.6); Added synonym support in query language and retrieval; Added out-of-the-box support for query-biased summaries and improved example web-based interface; Added new, 2nd generation DFR models as well as other recent effective information-theoretic models; Included many more JUnit tests (now 300+). Terrier 3.0 indices are compatible with Terrier 3.5.

Indexing

TR-117: Improve fields support by SimpleXMLCollection
TR-120: Error loading an additional MetaIndex structure (contributed by Javier Ortega, Universidad de Sevilla)
TR-106: Pipeline Query/Doc Policy Lifecycle (contributed by Giovanni Stilo, University degli Studi dell'Aquila and Nestor Laboratory - University of Rome "Tor Vergata")
TR-116: Lexicon not properly renamed on Windows
TR-118: SimpleXMLCollection - the term near the closing tag is ignored (contributed by Damien Dudognon, Institut de Recherche en Informatique de Toulouse)
TR-123: Null pointer exception while trying to index simple document (contributed by Ilya Bogunov)
TR-126: Logging improvements
TR-124: When processing docid tag in MEDLINE format XML file, xml context path is needed
TR-127: Easier refactoring of SinglePass indexers (contributed by Jonathon Hare, University of Southampton)
TR-108: Some indexers do not set the IterablePosting class for the DirectIndex (contributed by Richard Eckart de Castilho, Darmstadt University of Technology)
TR-136: Hadoop indexing misbehaves when terrier.index.prefix is not "data"
TR-137: TRECCollection cannot add properties from the document tags to the meta index at indexing time
TR-150: TRECCollection parse DOCHDR tags, including URLs should they exist (see TRECWebCollection)
TR-138: IndexUtil.copyStructure fails when source and destination indices are same
TR-140: Indexing support for query-biased summarisation
TR-144: CollectionRecordReader.next should not be recursive
TR-146, TR-148: Tokenisation should be done separately from Document parsing (the tokeniser can be set using the property tokeniser- see Non English language support in Terrier for more information on changing the tokenisation used by Terrier); Refactor Document implementations (e.g. TRECDocument and HTMLDocument are now deprecated in favour of the new TaggedDocument)
TR-147: Allow various Collection implementations to use different Document implementations
TR-158: Single pass indexing with default configuration doesn't ever flush memory

Retrieval

TR-16,TR-166: Extending query language and Matching to support synonyms
TR-157: Remove TRECQuerying scripting files: trec.models, qemodels, trec.topics.list and trec.qrels - use properties inTRECQuerying instead.
TR-156: Deploy a DAAT matching strategy - see org.terrier.matching.daat (partially contributed by Nicola Tonellotto, CNR)
TR-113: The LGD Loglogistic weighting model (contributed by Gianni Amati, FUB)

Fuller change log at http://terrier.org/docs/current/whats_new.html

Semantic hierarchies for image annotation: a survey

2011-06-19T03:39:00.001+03:00

Anne-Marie Tousch, Stéphane Herbin and Jean-Yves Audibert

In this survey, we argue that using structured vocabularies is capital to the success of image annotation. We analyze literature on image annotation uses and user needs, and we stress the need for automatic annotation. We briefly expose the difficulties posed to machines for this task and how it relates to controlled vocabularies. We survey contributions in the field showing how structures are introduced. First we present studies that use unstructured vocabulary, focusing on those introducing links between categories or between features. Then we review work using structured vocabularies as an input and analyze how the structure is exploited.

Highlights

► Literature on image annotation uses and user needs is reviewed. ► Approaches using unstructured or hierarchical vocabularies are compared. ► We argue that structured vocabularies is capital to automatic image annotation.

Keywords: Image annotation; Semantic description; Structured vocabulary; Image retrieval

http://www.sciencedirect.com/science/article/pii/S0031320311002652

Christos Faloutsos: How to find patterns in large graphs

2011-06-18T03:30:00.001+03:00

A video of CMU professor Christos Faloutsos‘s recent tech talk at LinkedIn on “Mining Billion-Node Graphs“.

World's First Coins With QR Codes Will Start Circulating in the Netherlands Next Week

2011-06-18T03:23:00.001+03:00

Determined to keep physical currency relevant in an age of bitcoins and NFC-equipped phones, the Dutch are turning their coins into little high-tech toys. These are purportedly the world’s firstcoins with QR codes, which currently link to the national mint, but after June 22 will link to a “surprise.”

The coins will be available starting June 22, in both silver (5€ ) and gold (10€). Right now the code resolves as www.q5g.nl, which takes you to a Dutch Ministry of Finance page (in Dutch).

There’s no explanation of what the surprise might be — maybe a contest, maybe a historical link, perhaps a video tour of the place where Dutch money gets made.

The U.S. produces some pretty high-tech cash, but the bills are designed to thwart counterfeiters, not necessarily to edify collectors or engage smartphone users. As far as we know this is the first currency to be embedded with a link to the Internet.

They likely won’t be replacing Dutch euros anytime soon, however — only a limited number of coins were produced, to celebrate the 100th anniversary of the national mint in Utrecht.

http://www.popsci.com/technology/article/2011-06/worlds-first-currency-qr-codes-will-start-circulating-netherlands-next-week

3D Holograms using Xbox Kinect

2011-06-18T03:16:00.001+03:00

Leia Holograph Holographs are just about impossible to capture in still images, resulting in that red blob you see to the right--but in person, it looks surprisingly good MIT

Michael Bove, the director of MIT’s Object-Based Media Group, got his grad students a Kinect for Christmas. The range-finding, motion-sensing camera add-on to Microsoft’s Xbox 360 game system turns the human body into a controller, but Bove’s students did something far more amazing with it. “A week later,” he says, “they were presenting holograms with it.” The students had hacked the Kinect, and found that it was a perfect tool for capturing images to project in three dimensions--in other words, for holograms.

(Oh, and a quick note about "holographs:" The word "holography" refers to the technique, and "holograms" are the results of it. "Holograph" is often used as a synonym for "hologram," but as Bove used the word "hologram" during our conversation, that's what I'll use here.)

Home holography video chat may sound like the stuff of Star Wars, but it’s closer than we think. Holography, like traditional 3-D filmmaking, has the end goal of a more immersive video experience, but the tech is completely different. 3-D cameras are traditional, fixed cameras, which simply capture two very slightly different streams to be directed to each eye individually--the difference between the two images creates the illusion of depth. If you change your position in front of a 3-D movie, the image you see will remain the same--it has depth, but only one perspective. (Curious about glasses-free 3-D? Check out our interactive primer.) A hologram, on the other hand, is made by capturing the scatter of light bouncing off a scene as data, and then reconstructing that data as a 3-D environment. That allows for much greater immersion--if you change your viewing angle, you'll actually see a different image, just as you can see the front, sides, and back of a real-life object by rotating around it. "If holography is done right," says Bove, "it's really quite stunning."

Capturing that scatter of light is no easy feat. A standard 3-D movie camera captures light bouncing off of an object at two different angles, one for each eye. But in the real world, light bounces off of objects at an infinite number of angles. Holographic video systems use devices that produce so-called diffraction fringes, basically fine patterns of light and dark that can bend the light passing through them in predictable ways. A dense enough array of fringe patterns, each bending light in a different direction, can simulate the effect of light bouncing off of a three-dimensional object.

The trick is making it live, fast and cheap. It is one of the OBMG’s greatest challenges: the equipment is currently extremely expensive, the amount of data massive. "[We’re] trying to turn holographic video from a lab curiosity into a consumer product," Bove says. They’re getting close. Using the Kinect, which costs just $150, and a laptop with off-the-shelf graphics cards, the OBMG crew was able to project holograms at seven frames per second. Previous breakthroughs, both at MIT and at other institutions like Cornell, could only achieve frame rates of one per every two seconds--far slower than the 30 frames per second required for movies or the 24 frames per second required for television. A week later, the MIT students had gotten the rig up to 15 frames per second. Bove says that's far from the limits of the Kinect hardware. The next step is to bring down the cost of the holographic display.

Hologram From Star Wars: LucasFilm

The current holographic display is a sophisticated acousto-optic modulator, a device that diffracts and shifts the frequency of light by using sound waves. But the OBMG is hoping to replace the modulator, a one-of-a-kind, highly expensive piece of equipment which was pioneered by Bove's predecessor Stephen Benton, with a consumer model they hope will be able to be manufactured in the near future for a mere few hundred dollars. In a matter of years, truly live holographic video chat could be wholly possible. Princess Leia's holographic plea for help? Child's play. After all, it was pre-recorded.

The challenge with real-time holographic video is taking video data—in the case of the Kinect, the light intensity of image pixels and, for each of them, a measure of distance from the camera—and, on the fly, converting that data into a set of fringe patterns. Bove and his grad students—James Barabas, David Cranor, Sundeep Jolly and Dan Smalley—have made that challenge even tougher by limiting themselves to off-the-shelf hardware.

In the group’s lab setup, the Kinect feeds data to an ordinary laptop, which relays it over the Internet. At the receiving end, a PC with three ordinary, off-the-shelf graphics processing units — GPUs — computes the diffraction patterns.

GPUs differ from ordinary computer chips — CPUs — in that their circuitry has been tailored to a cluster of computationally intensive tasks that arise frequently during the processing of large graphics files. Much of the work that went into the new system involved re-describing the problem of computing diffraction patterns in a way that takes advantage of GPUs’ strengths.

Home holography is a pretty incredible technology; it would have the potential to totally change the basic way we use displays, from media to chat. His path, by using cheap, easily found equipment, could be the fastest way to a holographic future, and it's especially thrilling that the Kinect, a $150 video game accessory most often used to teach the Soulja Boy dance, is a major component in making that future possible.

http://www.popsci.com/gadgets/article/2011-04/leia-your-living-room-creating-holograph-microsoft-kinect

Processing 1.5+

2011-06-18T03:10:00.001+03:00

Processing is an open source programming language and environment for people who want to create images, animations, and interactions. Initially developed to serve as a software sketchbook and to teach fundamentals of computer programming within a visual context, Processing also has evolved into a tool for generating finished professional work. Today, there are tens of thousands of students, artists, designers, researchers, and hobbyists who use Processing for learning, prototyping, and production.

» Free to download and open source
» Interactive programs using 2D, 3D or PDF output
» OpenGL integration for accelerated 3D
» For GNU/Linux, Mac OS X, and Windows
» Projects run online or as double-clickable applications
» Over 100 libraries extend the software into sound, video, computer vision, and more...
» Well documented, with many books available

To see more of what people are doing with Processing, check out these sites:

» Processing Wiki
» Processing Discussion Forum
» OpenProcessing
» CreativeApplications.Net
» O'Reilly Answers
» Vimeo
» del.icio.us
» Flickr
» YouTube

To contribute to the development, please visit Processing on Google Code to read instructions for downloading the code,building from the source, reporting and tracking bugs, and creating libraries and tools.

http://processing.org/

Download Kinect for Windows SDK beta

2011-06-16T20:57:00.001+03:00

The Kinect for Windows SDK beta is a starter kit for applications developers that includes APIs, sample code, and drivers. This SDK enables the academic research and enthusiast communities to create rich experiences by using Microsoft Xbox 360 Kinect sensor technology on computers running Windows 7.Learn more >

The Kinect for Windows SDK beta includes the following:

Drivers, for using Kinect sensor devices on a computer running Windows 7.
Application programming interfaces (APIs) and device interfaces, together with technical documentation.
Source code samples.

System requirements

Hardware

Kinect for Xbox 360 sensor
Computer with a dual-core, 2.66-GHz or faster processor
Windows 7�compatible graphics card that supports DirectX� 9.0c capabilities
2-GB RAM (4-GB RAM recommended)

Software

Windows 7 (x86 or x64)
Visual Studio 2010 Express (or other 2010 edition)
Microsoft .NET Framework 4.0
For additional requirements for samples, see the Readme file

Installation instructions

To install this SDK beta:

On this page, click Download to start the Kinect for Windows SDK beta download.
Click Run to start Setup, and follow the instructions in the Setup Wizard.
Or, to save the download on your computer so that you can install it later, click Save.

http://research.microsoft.com/en-us/um/redmond/projects/kinectsdk/download.aspx

Practical Image and Video Processing Using MATLAB

2011-06-15T18:21:00.001+03:00

Up-to-date, technically accurate coverage of essential topics in image and video processing

This is the first book to combine image and video processing with a practical MATLAB®-oriented approach in order to demonstrate the most important image and video techniques and algorithms. Utilizing minimal math, the contents are presented in a clear, objective manner, emphasizing and encouraging experimentation.

The book has been organized into two parts. Part I: Image Processing begins with an overview of the field, then introduces the fundamental concepts, notation, and terminology associated with image representation and basic image processing operations. Next, it discusses MATLAB® and its Image Processing Toolbox with the start of a series of chapters with hands-on activities and step-by-step tutorials. These chapters cover image acquisition and digitization; arithmetic, logic, and geometric operations; point-based, histogram-based, and neighborhood-based image enhancement techniques; the Fourier Transform and relevant frequency-domain image filtering techniques; image restoration; mathematical morphology; edge detection techniques; image segmentation; image compression and coding; and feature extraction and representation.

Extra features of this book include:

More than 30 MATLAB® tutorials, which consist of step-by-step guides to exploring image and video processing techniques using MATLAB®
Chapters supported by figures, examples, illustrative problems, and exercises
Useful websites and an extensive list of bibliographical references

About the Author

Oge Marques, PhD, is Associate Professor in the Department of Computer & Electrical Engineering and Computer Science at Florida Atlantic University. He has been teaching and doing research on image and video processing for more than twenty years, in seven different countries. Dr. Marques is the coauthor of Processamento Digital de Imagens and Content-Based Image and Video Retrieval and was editor-in-chief of the Handbook of Video Databases, a comprehensive work with contributions from more than 100 world experts in the field. He is a Senior Member of both the IEEE and the ACM.

http://ogemarques.com/

Preorder NOW

Google Launches Search By Image – It’s Like Goggles For The Desktop

2011-06-15T00:40:00.001+03:00

At the Inside Search event being held at San Francisco, Google has announced a new addition to its search features - Search by Image. The Search by Image feature is something like Google’s image search application for mobile devices – Google Goggles.

Those who have used service like TinEye will be familiar with what Search by Image does. Although technically similar to what Tiny Eye does, Google has taken it much further.

Google Search by Image

Suppose you have an image you want to search about. There are three ways for you to use Search by Image to search for the image:

You can upload the image.
You can also drag and drop the image into the search box.
If the image is online, you can paste the URL of the image into the search box.
You can also use extensions for Chrome and Firefox that Google will release.

After the image has been analyzed by the servers at Google, Google will attempt to identify the image and bring up search results related to it. The technology used for Search by Image is similar to that used by Google Goggles for smartphones.

The service is not live yet and Google will roll out the feature in the coming few days. You will know that Search by Image has been activated for you when you see a camera icon at the right of the search box.

Here is a video that Google has released introducing Search by Image:

http://digitizor.com/2011/06/15/google-search-by-image/

Minority Report-like Interface

2011-06-07T19:54:00.001+03:00

Evoluce presented at the RTT Excite a “Minority-Report”-like software for Kinect. WIN&I 2.0 beta multi-gesture software allows to rotate images and zoom in and out. Objects on the screen can be dragged and dropped by simple hand gestures in the air. By closing the hand the user grabs an object and can move it like in the real world.

Multi-touch applications can be controlled by both hands and gestures of fingers without touching the screen surface. Precise finger tracking allows to manipulate not only objects but also icons, images and videos on the screen. This natural user interface software enables also finger- and hand-tracking of multiple users at the same time. A huge variety of applications in gaming, consumer electronics, office, education, point of sale and medical systems can be controlled by touchless gestures in an intuitive way.

Evoluce will offer soon a Multi-Gesture SDK for Kinect™/Asus Xtion Pro™/ PrimeSensor™

The SDK will support developers to create natural user applications with a controller free experience and offers

• gesture module supporting finger gestures, push, zoom, rotate, drag & drop
• tracking and gesture recognition of both hands
• visual feedback: picture/animation/video
• “multi-touch” application control, e.g. Microsoft Touch Pack for Windows 7
• API´s: Windows 7 multitouch, TUIO
• mouse control
• skeleton tracking based on OpenNI™

http://kinecthacks.net/minority-report-like-interface/

ESSIR 2011: Top-K reasoning for NOT attending the European Summer School on IR

2011-06-02T17:46:00.001+03:00

ESSIR 2011 - European Summer School in Information Retrieval

29 Aug - 02 Sep 2011, Koblenz, Germany

http://essir.uni-koblenz.de/

Practical top-k reasoning in Information Retrieval:

Top-10 reasons NOT to attend ESSIR 2011

If you don't want to meet authors of best recent IR books as your lecturers, stay home.

If you prefer questions to answers, don't come to the plenary discussion with lecturers about doing successful PhD in IR.

If you are not interested in recent trends and directions in IR, avoid PhD symposiums. Do not submit any papers there!

If you don't need any feedback on your research/PhD topic, do not present anything in the poster/demo session. Grab some yummy fingerfood and disappear.

If you are not interested in highly reasonable fees, try to register as late as possible. Do not apply for school grants!

If you're not satisfied with best-price accommodation, stay home for free.

If your physician told you to avoid excitement, don't join the Rhine ship-cruise to the famous Loreley valley.

If you are indifferent to rivers, rocks, wineyards, volcanos, geysirs, medieval castles and world-best white wines, Rhineland will not attract your attention.

If you don't want to meet new people and exchange ideas, do not join our informal come-together activities.

If you don't trust Web 2.0, do not join our Facebook group. Do not follow us on Twitter, stay off our Flickr and Youtube contents.

====================================================

OTHERWISE.. what are you actually waiting for ?!

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Grant applications: until 01 June 2011 (apply NOW !!!)

Early registration: until 30 June 2011

http://essir.uni-koblenz.de/

Google I/O 2011: Cloud Robotics, ROS for Java and Android

2011-05-15T02:00:00.001+03:00

Article from http://www.ros.org/news/2011/05/google-io-2011-cloud-robotics-ros-for-java-and-android.html

Yesterday at Google I/O, developers at Google and Willow Garage announced a new rosjava library that is the first pure-Java implementation of ROS. This new library was developed at Google with the goal of enabling advanced Android apps for robotics.

The library, tools, and hardware that come with Android devices are well-suited for robotics. Smartphones and tablets are sophisticated computation devices with useful sensors and great user-interaction capabilities. Android devices can also be extended with additional sensor and actuators thanks to the Open Accessory and Android @ Home APIs that were announced at Google I/O

The new rosjava is currently in alpha release mode and is still under active development, so there will be changes to the API moving forward. For early adopters, there are Android tutorials to help you send and receive sensor data to a robot.

This announcement was part of a broader talk on Cloud Robotics, which was given by Ryan Hickman and Damon Kohler of Google, as well Ken Conley and Brian Gerkey of Willow Garage. This talk discusses the many possibilities of harnessing the cloud for robotics applications, from providing capabilities like object recognition and voice services, to reducing the cost of robotics hardware, to enabling the development of user interfaces in the cloud that connect to robots remotely. With the new rosjava library, ROS developers can now take advantage of the Android platform to connect more easily to cloud services.

Call for ICPR Contest Proposals

2011-05-13T19:43:00.001+03:00

The ICPR 2012 Contest Co-Chairs invite proposals for contests, whose results will be presented at the 21st International Conference on Pattern Recognition (www.icpr2012.org). The aim of the contests is to encourage better scientific development through comparing competing approaches on a common dataset. Each contest needs a contest organizer, who will be responsible for providing the dataset and setting clear competition tasks. The contest organizer should advertise the contest by Oct 1, 2011 (the schedule below is set so as to encourage contest participants to submit papers to main conference). The ICPR web site will also publicize the contest. The contest meeting will be a quarter/half day session (organizer's choice) at the conference on November 11, 2012, immediately before the start of the main conference. The format of the meeting is up to the contest organizer, but we anticipate it will include a description of the challenge and dataset, and a summary of performance on the different competition tasks. There could be presentations by the top scoring teams.

ICPR 2012 will be responsible for the following:

- Providing a meeting venue with necessary equipment and logistical support for the contests including support staff in each room.
- Duplicating contest notes and distributing them to the participants at the conference venue. Contest organizers are encouraged to make summary notes of their contest results for stimulating discussions in their sessions.

Important Contest Session Dates

Contest Proposal Deadline July 15, 2011

Notification of Acceptance August 15, 2011

Contest Announcement to Participants (Tasks, Dataset and Metrics) Oct 1, 2011

Submissions of Contest Results and submission of a 2-3 page report for copying and distribution to the participants. Oct 1, 2012

Results of the competition are announced at the conference Nov 11, 2012

How to Submit Proposal

To propose a contest, a PDF file containing the following information must be sent to the ICPR 2012 Contest Co-Chairs, Yasuyo Kita <y.kita(at)aist.go.jp> and Robert Fisher <rbf(at)inf.ed.ac.uk> by July 15, 2011 (All submissions will be acknowledged by email) :

1. Contest title and abstract
2. Name and contact information of the main organizer and at least 2 other expert committee members
3. General description of the problem
4. Description of the dataset to be used
5. Description of the actual competition tasks
6. Evaluation metrics
7. Plan of how to organize the contest
8. Estimated number of participants
9. Preference of a quarter day session or a half day session

Other points that should be taken into account are as follows:
* The dataset should be interesting, available, and sufficiently large.
* The tasks should be interesting and novel, but also accessible without too much domain specific knowledge.
* The evaluation metrics should be clear and easy to apply.

Image processing and Retrieval Trends

Mobile Visual Search (MVS)

ΠΡΟΣΚΛΗΣΗ ΕΚΔΗΛΩΣΗΣ ΕΝΔΙΑΦΕΡΟΝΤΟΣ ΓΙΑ ΤΗΝ ΕΚΠΟΝΗΣΗ ΔΙΔΑΚΤΟΡΙΚΗΣ ΔΙΑΤΡΙΒΗΣ

The faster-than-fast Fourier transform

WIAMIS 2012: The 13th International Workshop on Image Analysis for Multimedia Interactive Services 23rd - 25th May 2012, Dublin City University, Ireland

Topics of interest include, but are not limited to:

3D Photo Ring HD Update v2.3

US Moves Toward Banning Photoshop In Cosmetics Ads

MMM2012

Image retrieval, Research Assistant (19 months)

Merry Christmas and a happy 2012

2011 PhD Challenge Winner - "Dirty Old Man"

The goal of this year’s challenge was to get one of the nicknames “DIRTY OLD MAN” or “CRAZY CAT LADY”included in the byline for at least one author of a final, camera-ready version of a peer-reviewed academic paper

Ετήσιο Βραβείο Καλύτερης Διδακτορικής Διατριβής του Ινστιτούτου Πληροφορικής και Τηλεματικής

ClustTour By CERTH-ITI

IBM Next 5 in 5: 2011

Vision Algorithm to Automatically Parse Addresses in Google Street View

ICMR 2012

sFly: Search and Rescue of Victims in GPS-Denied Environments (no Vicon, no Laser, No GPS!)

MPEG news: a report from the 98th meeting, Geneva, Switzerland

Free Access to selected highly cited papers from IJPRAI

ACRI 2012 Santorini Island, Greece, 24-27 September 2012

Terrain Surveillance Coverage using Cognitive Adaptive Optimization

Mathias Lux @ ACM MULTIMEDIA 2011

Google Scholar Citations Open To All

ColorHug

Face Recognition Makes the Leap From Sci-Fi

3D Photo Ring

Screenshots

The 6th FTRA International Conference on Multimedia and Ubiquitous Engineering (MUE 2012)

Nano-spring make transparent, super-stretchy skin-like sensors

Artificial intelligence community mourns John McCarthy

Throwable Camera Creates 360-Degree Panoramic Images

Rendering Synthetic Objects into Legacy Photographs

Kevin Karsch, Varsha Hedau, David Forsyth, Derek HoiemTo be presented at SIGGRAPH Asia 2011

Abstract

Top 10 ACM SIGMM Downloads

FaceLight – Silverlight 4 Real-Time Face Detection

C

ACM International Conference on Multimedia Retrieval (ICMR) 2012

Important Dates

Kinect Object Datasets: Berkeley's B3DO, UW's RGB-D, and NYU's Depth Dataset

The PHD Movie!!!

Exploring Photobios - SIGGRAPH 2011

Panasonic unveils first robotic hairdresser

Recent Image Retrieval Techniques

“Practical Image and Video Processing Using MATLAB®”

Call for participation in the ICPR 2012 Contests

CFP: VII Conf. on Articulated Motion and Deformable Objects (AMDO 2012)

Job offer : engineer position in mutlimedia retrieval systems' evaluation

Congratulations to DEMIR research team for winning the ImageCLEF-MED 2011 Ad-hoc image-based retrieval task using CEDD

An eBay for science.

Script#

The Script# Project

Compact Composite Descriptors for Content Based Image Retrieval

Face recognition in London 2012 Olympic Games

Introduction to Artificial Intelligence

Stanford University's School of Engineering also offers other complete online courses at no cost. Click here to access Stanford Engineering Everywhere.

Stop Motion Photographer

Call for MS students of UCS Lab@SeoulTech-National, Korea (Supervisor: James. J. Park)

Orasis Brain-Inspired Image Processing App, is now available in iTunes!

BRISK: Binary Robust Invariant Scalable Keypoints

Recognition Using Visual Phrases

CVPR 2011 Award Paper

Lire Demo 0.9 alpha 2 just released

CFP: EURASIP Journal on Advances in Signal Processing Special Issue On Social Media Processing and Semantic Modeling

7th INTERNATIONAL SUMMER SCHOOL ON PATTERN RECOGNITION (ISSPR) 4-9 SEPTEMBER 2011, Plymouth, UK

Deb Roy: The birth of a word

MPEG news: a report from the 97th meeting, Torino, Italy

ImageCLEF's Wikipedia Retrieval Task Results

JOB: postdoc in animation and graphics at Edinburgh

Google acquires PittPatt

2 computer vision PhD places at Edinburgh

Do we need an alternative to peer-reviewed journals?

Lightsaber + Kinect + robotic arm = JediBot

What Caricatures Can Teach Us About Facial Recognition

New Version of img(Rummager)

TsoKaDo

If You’re Happy and You Know It - Facebook will detect it

Multimodal Image Retrieval: ImageCLEF and beyond

Kevin Karsch, Varsha Hedau, David Forsyth, Derek Hoiem
To be presented at SIGGRAPH Asia 2011

Zinal, Valais - Switzerland
23 - 27 January 2012