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Showing posts with label CBIR. Show all posts
Showing posts with label CBIR. Show all posts

Monday, November 8, 2010

MediaEval Benchmarking Initiative

MediaEval LogoMediaEval is a benchmarking initiative dedicated to evaluating new algorithms for multimedia access and retrieval. MediaEval focuses on speech, language and contextual aspects of video (geographical and social context). Typical tasks include, predicting tags for video, both user-assigned tags (Tagging Task) and geo-tags (Placing Task). We are daring enough to tackle "subjective" aspects of video (Affect Task).


How can I get involved?
MediaEval is an open initiative, meaning that any interested research group is free to signup and participate. Signup for MediaEval 2011 will open in early Spring 2011 on this website. Groups sign up for one or more tasks, they then receive task definitions, data sets and supporting resources, which they use to develop their algorithms. At the end of the summer, groups submit their results and in the fall they attend the MediaEval workshop. More information on MediaEval is available on theFAQ page (see also Why Participate?)


Which tasks will be offered in 2011?
The task offering in 2011 will be finalized on the basis of participant interest, assessed, as last year, via a survey. At this time, we anticipate that we will run a Tagging Task and Placing Task (see MediaEval 2010 for descriptions of the form these tasks took in 2010). We also anticipate offering an additional task involving ad hoc video retrieval and one involving violence detection. Please watch this page for additional information to appear at the beginning of 2011 or contact the organizers for information on the current status of plans.


Beyond plain sight?
We are interested in pushing video retrieval research beyond the pictorial content of video. In other words, we want to get past what we see in "plain sight" when watching a video and instead also analyze video content in terms of its overall subject matter (what it is actually about) and the effect that it has on viewers. This goal is consistent with our emphasis on speech, language and context features (geographical and social context).


There's a MediaEval trailer?
Yes. In the MediaEval 2010 Affect Task, we analyzed a travelogue series created by Bill Bowles, filmmaker and traveling video blogger. We were looking for elements that could be used to automatically predict whether, overall, a general audience would find a particular episode engaging or boring. Bill attended the MediaEval 2010 workshop in Pisa, listened to our findings and created a travelogue episode for us. In this video, Bill tells the story of MediaEval in his own words...and makes conscious use of some of the predictors we found to correlate with viewer engagement.

http://www.multimediaeval.org/

Wednesday, January 7, 2009

Private Content Based Image Retrieval

For content level access, very often database needs the query as a sample image. However, the image may contain private information and hence the user does not wish to reveal the image to the database. Private Content Based Image Retrieval (PCBIR) deals with retrieving similar images from an image database without revealing the content of the query image – not even to the database server. We propose algorithms for PCBIR, when the database is indexed using hierarchical index structure or hash based indexing scheme. Experiments are conducted on real datasets with popular features and state of the art data structures. It is observed that specialty and subjectivity of image retrieval (unlike SQL queries to a relational database) enables in computationally efficient yet private solutions.
Author: Shashank J, Kowshik P, Kannan Srinathan and C.V. Jawahar
Download Tha Paper (TR)