Temporal shot clustering analysis for video concept detection

Authors:
Dayong Ding;Le Chen;Bo Zhang
Affiliations:
Department of Computer Science and Technology, Tsinghua University, Beijing, P.R. China;Department of Computer Science and Technology, Tsinghua University, Beijing, P.R. China;Department of Computer Science and Technology, Tsinghua University, Beijing, P.R. China
Venue:
ECIR'05 Proceedings of the 27th European conference on Advances in Information Retrieval Research
Year:
2005

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ECIR'05 Proceedings of the 27th European conference on Advances in Information Retrieval Research

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Abstract

The phenomenon that conceptually related shots appear together in videos is called temporal shot clustering. This phenomenon is a useful cue for video concept detection, which is one of basic steps in content-based video indexing and retrieval. We propose a method, called temporal shot clustering analysis, to improve results of video concept detection by exploiting the temporal shot clustering phenomenon. Two other methods are compared with temporal shot clustering analysis on the TRECVID 2003 dataset. Experiments showed that temporal shot clustering is of much benefit for video concept detection, and that temporal shot clustering method outperforms the other methods.