Concept representation based video indexing

Authors:
Meng Wang;Yan Song;Xian-Sheng Hua
Affiliations:
Microsoft Research Asia, Hefei, China;Univeristy of Science and Technology of China, Hefei, China;Microsoft Research Asia, Hefei, China
Venue:
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Year:
2009

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Abstract

This poster introduces a novel concept-based video indexing approach. It is developed based on a rich set of base concepts, of which the models are available. Then, for a given concept with several labeled samples, we combine the base concepts to fit it and its model can thus be obtained accordingly. Empirical results demonstrate that this method can achieve great performance even with very limited labeled data. We have compared different representation approaches including both sparse and non-sparse methods. Our conclusion is that the sparse method will lead to much better performance.