Journal of Zhejiang University SCIENCE A
(Monthly)

2006   Vol. 7   Suppl. II   p. 193-197

A retrospective event detection method in news video

Ling Jian^†1,2, Lian Yi-Qun², Zhuang Yue-Ting¹

(¹Institute of Artificial Intelligence, Zhejiang University, Hangzhou 310027, China)
(²Department of Electronic Information, Zhejiang Institute of Media and Communication, Hangzhou 310018, China)
^†E-mail: lingjian@zjut.edu.cn
Received Jan. 10, 2006 revision accepted May 8, 2006

Abstract: In this work we present a probabilistic learning approach to model video news story for retrospective event detection (RED). In this approach, both content and time information on a news video is utilized to transcribe the news story into terms, which are divided into classes by their semantics. Then a probabilistic model, composed of sub-models corresponding to the semantic classes respectively, is proposed. The model’s parameters are estimated by EM algorithm. Experiments showed that the proposed approach has better detection resolution.

Key words: Semantic class, EM algorithm, Retrospective news event detection, Maximum likelihood
doi:10.1631/jzus.2006.AS0193             CLC number: TP391

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