We regret to inform you that you paper has not been accepted
as a PhD student:
as a post-doc:
as a professor:
We are pleased to inform you that your paper has been accepted
As a PhD student:
As a post doc:
As a professor:
by Nikolaj & Jilles
Abstract
We present Magic Finger, a small device worn on the fingertip, which supports always-available input. Magic Finger inverts the typical relationship between the finger and an interactive surface: with Magic Finger, we instrument the user’s finger itself, rather than the surface it is touching. Magic Finger senses touch through an optical mouse sensor, enabling any surface to act as a touch screen. Magic Finger also senses texture through a micro RGB camera, allowing contextual actions to be carried out based on the particular surface being touched. A technical evaluation shows that Magic Finger can accurately sense 32 textures with an accuracy of 98.9%. We explore the interaction design space enabled by Magic Finger, and implement a number of novel interaction techniques that leverage its unique capabilities.
Paper
Xing-Dong Yang, Tovi Grossman, Daniel Wigdor & George Fitzmaurice. (2012).
Magic Finger: Always-Available Input through Finger Instrumentation
UIST 2012 Conference Proceedings:
ACM Symposium on User Interface Software & Technology.
pp. 147 – 15 Download PDF
(Great Opportunity)
YOUR SKILLS
Passion for control, image processing, mathematics, machine learning, and abstract thinking. Apart from your curiosity, your communication skills and your ability to work in teams, you should meet the following requirements:
• Applicants for the PhD position: MSc or equivalent in Electrical, Mechanical Engineering, Computer Science, Physics or closely related field
• Excellent academic track record
• Very good English skills, written and spoken
• Control background
• State-of-the-art computer vision know-how
• Excellent C++ skills with several years of coding experience
• Ability to solve difficult vision problems and to push forward the development of the core control and image algorithms with your ideas
• Skill to analyze and improve algorithms
Experience in mobile robotics (with topics such as 2D/3D SLAM or tracking) and multi-robot control is a plus. Familiarity with libraries such as Qt, OpenCV, OpenGL and development tools including Matlab, Python, CMake, and Git would also be an advantage.
The candidate is expected to also participate in supervision of bachelor's and master's projects, and the general activities of the Lab.
DATES
- Evaluation of the candidates starts immediately but will continue until the position is filled
HOW TO APPLY
Please send a single PDF including (in the order) a short letter of motivation (half a page) and your CV (including publication list and a list of at least 3 references). For candidates holding a Masters' degree, please include your transcripts (BSc and MSc).
Send the above PDF to Prof. Dr. Davide Scaramuzza <scaramuzza (dot) applications (at) gmail (dot) com> quoting [PhD Application] or [Postdoc Application] in the subject.
Optionally, send in a copy of undergrad project reports, semester papers or anything else that shows your ability for scientific work and writing.
For questions, please contact Davide Scaramuzza using the same email address for the applications <scaramuzza (dot) applications (at) gmail (dot) com>
WHAT WE OFFER
We offer an exciting research opportunity at the forefront of one of the most dynamic engineering fields. You will have both one of the steepest personal learning experiences in your life as well as the opportunity to make an impact in the consumer-electronics market and in the computer vision and robotics communities.
You will be working in a very international team of highly motivated and skilled people. You will grow into a network of international robotics and computer vision professionals.
A Software Engineer or Postdoc position is a regular job with social benefits in Switzerland. You will get a very competitive salary and access to excellent facilities in one of the world's leading technical Robotics Labs. Zurich is regularly ranked among the top cities in the world for quality of life.
THE AILAB
- The Ailab counts about 30 people (PhD, Postdocs, and technicians) with more than 10 different nationalities, electronic and machine workshops, 3D printers, and a motion capture system
- Info about the Ailab can be found at http://ailab.ifi.uzh.ch/
- Information about our current computer vision and robotics past projects can be found at https://sites.google.com/site/scarabotix/
- The Ailab is located in the Department of Informatics of the University of Zurich http://www.ifi.uzh.ch/index.html
- Information about the University of Zurich can be found at http://www.uzh.ch/index_en.html
The Information and Software Engineering Group at the Institute of Software Technology and Interactive Systems at the Vienna University of Technology announces the availability of a 2-year post-doctoral position.
The position is associated to the MUCKE project, funded within the CHIST-ERA funding scheme of FP7, which fosters highly innovative and multidisciplinary collaborative projects in information and communication sciences and technologies. The project started in October 2012. Its main objective is to devise new and reliable knowledge extraction models designed for multilingual and multimodal data shared on social networks. More information on MUCKE: http://www.chistera.eu/projects/mucke
The main task of the post-doc is to investigate and propose new models for user and result-list credibility. The aim is to provide the user of a multimedia search system with a list of results from reliable sources, together with an estimation of how reliable each source is, as well as how reliable the entire set of results is. Such reliability is to be understood from two orthogonal perspectives: First, the topical relatedness of the results (i.e. relevance). Second, the likelihood that the result, although topically relevant, is also accurate.
To approach this task, the post-doc must have strong mathematical background (preferably including statistics), as well as a fundamental understanding of Information Retrieval. Applicants with experience in NLP and/or Computer Logic will be favored.
The position is available from November 2012 and is open until filled.
For further information, please send an expression of interest to lupu@ifs.tuwien.ac.at, attaching a CV.
== About our Group ==
The working group Information and Software Engineering is part of the Institute of Software Technology and Interactive Systems.
It covers the design and development of software and information systems in research and education.
The other groups cover E-Commerce, Business Informatics, and Interactive Media Systems.
Both theoretical and engineering-like approaches to problem solving have equal balance in our research and educational work - leading to "real world problem solving".
The Group is situated in downtown Vienna, in an environment which brings together all aspects of student and academic life. The post-doc will be part of the Information Management & Processing lab, which consists of researchers in text and music information retrieval, as well as in multimedia processing. The working language is English. A more detailed description of the IMP lab is available at http://ifs.tuwien.ac.at/~imp/
http://jivp.eurasipjournals.com/sites/10235/pdf/H9111_A4_2.pdf
Deadline for submissions: January 15th, 2013
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This special issue aims at reporting on the most recent approaches and tools for the identification, interpretation and description of animal and insect behaviour in image sequences. It specially focuses
on the interactions between (i) computer vision theories and methods, (ii) artificial intelligence techniques for the high-level analysis of animal and insect behaviours and (iii) multimedia semantics methods for indexing and retrieval of animal and insect behaviour detected in images and videos.
With the widespread use of video imaging devices, the study of the behaviour by exploiting visual data has become very popular. The visual information gathered from image sequences is extremely useful to understand the behaviour of the different objects in the scene, as well as how they interact each other or with the surrounding environment. However, whilst a large number of video analysis techniques have been developed specifically for investigating events and behaviours in human-centered applications, very little attention
has been paid to the understanding of other live organisms, such as animals and insects, although huge amount of video data are continuously recorded; e.g. the EcoGrid project or the wide range of nest cams continuously monitor, respectively, underwater reef and birds nests (there exist also variants focusing on wolves, badgers,
foxes etc.). Moreover, the few existing approaches deal only with controlled environments (e.g. labs, cages, etc.)and as such they cannot be used in real-life applications.
The automated analysis of video data in real-life environments poses several challenges for computer vision researchers because of the uncontrolled scene conditions and the nature of the targets to be analysed whose 3D motion tends to be erratic, with sudden direction and speed variations, and appearance and non-rigid shape
can undergo quick changes. Computer Vision tools able to analyse those complex environments are of great interest to biologists in their striving towards analyzing the natural environment, promoting its preservation, and understanding the behaviour and interactions of the living organisms (in- sects, animals, etc.) that are
part of it.
We invite authors to contribute high quality papers that will stimulate the research community on the use image and video analysis methods to be applied in real-life environments for animal and insect behaviour monitoring and understanding.
Potential topics include, but are not limited to:
- Living organism detection, tracking, classification and recognition in image sequences
- Animals and Insects dynamic shape analysis
- Visual surveillance and Event Detection in Ecological Applications
- Stereo Vision and Structure from motion of living organisms
- Event and Activity Recognition in Ecological Videostreams
- Animal and insect behaviour analysis and articulated models
- Animal and insect motion and trajectory analysis
- High-level behaviour recognition and understanding
- Semantic Region Identification in animal and insect populated scenarios
- Categorization and Natural Scene Understanding
- Natural Scene and Object-Scene Interaction Understanding
- Ontologies and semantic annotation of animal and insect motion in video content
Submission Instructions
Submissions to the special issue must include new, unpublished, original research.
Papers must be original and have not been published or submitted elsewhere. All
papers must be written in English. The submissions will be reviewed in a double-blind
procedure by at least three reviewers. The papers must contain no information identifying
the author(s) or their organization(s).
Before submission authors should carefully read over the Instructions for Authors, which are located at
jivp.eurasipjournals.com/authors/instructions.
Prospective authors should submit an electronic copy of their complete manuscript through the SpringerOpen
submission system at jivp.eurasipjournals.com/manuscript according to the submission schedule.
They should choose the correct Special Issue in the 'sections' box upon submitting. In addition, they should
specify the manuscript as a submission to the 'Special Issue on Animal and Insect Behaviour Understanding in
Image Sequences' in the cover letter. All submissions will undergo initial screening by the Editors for
fit to the theme of the Special Issue and prospects for successfully negotiating the review process.
Important Dates
15 Jan 2013: Manuscript submission due
15 April 2013: Acceptance/Revision notification
30 May 2013: Revised manuscript due
30 July 2013: Final acceptance notication
15 August 2013: Final manuscript due:
September 2013: Tentative publication
