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ZJUS-A
Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2006, Vol. 7 Issue (Supplement 2): 193-197    DOI: 10.1631/jzus.2006.AS0193
Original Paper     
A retrospective event detection method in news video
Ling Jian, Lian Yi-Qun, Zhuang Yue-Ting
Institute of Artificial Intelligence, Zhejiang University, Hangzhou 310027, China; Department of Electronic Information, Zhejiang Institute of Media and Communication, Hangzhou 310018, China
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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     
Received: 10 January 2006     
CLC:  TP391  
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Cite this article:

Ling Jian, Lian Yi-Qun, Zhuang Yue-Ting. A retrospective event detection method in news video. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2006, 7(Supplement 2): 193-197.

URL:

http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.2006.AS0193     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2006/V7/ISupplement 2/193

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