In this paper, we describe a system for automatic and interactive content-based retrieval of video that integrates features, models, and semantics. The novelty of the approach lie...
John R. Smith, Savitha Srinivasan, Arnon Amir, San...
With the explosion of multimedia data especially that of video data, requirement of efficient video retrieval has becoming more and more important. Years of TREC Video Retrieval Ev...
Statistical modeling for content based retrieval is examined in the context of recent TREC Video benchmark exercise. The TREC Video exercise can be viewed as a test bed for evalua...
Milind R. Naphade, Sankar Basu, John R. Smith, Chi...
The TREC Video Retrieval Evaluation (TRECVid) is an international benchmarking activity to encourage research in video information retrieval by providing a large test collection, ...
The variety of features available to represent multimedia data constitutes a rich pool of information. However, the plethora of data poses a challenge in terms of feature selectio...