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CLC number: TP391
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 0000-00-00
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A retrospective event detection method in news video
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Ling Jian, Lian Yi-Qun, Zhuang Yue-Ting. A retrospective event detection method in news video[J]. Journal of Zhejiang University Science A, 2006, 7(101): 193-197.
@article{title="A retrospective event detection method in news video",
author="Ling Jian, Lian Yi-Qun, Zhuang Yue-Ting",
journal="Journal of Zhejiang University Science A",
volume="7",
number="101",
pages="193-197",
year="2006",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2006.AS0193"
}
%0 Journal Article
%T A retrospective event detection method in news video
%A Ling Jian
%A Lian Yi-Qun
%A Zhuang Yue-Ting
%J Journal of Zhejiang University SCIENCE A
%V 7
%N 101
%P 193-197
%@ 1673-565X
%D 2006
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2006.AS0193
TY - JOUR
T1 - A retrospective event detection method in news video
A1 - Ling Jian
A1 - Lian Yi-Qun
A1 - Zhuang Yue-Ting
J0 - Journal of Zhejiang University Science A
VL - 7
IS - 101
SP - 193
EP - 197
%@ 1673-565X
Y1 - 2006
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2006.AS0193
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.
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