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Proceedings Paper

Bayesian-network-based soccer video event detection and retrieval
Author(s): Xinghua Sun; Guoying Jin; Mei Huang; Guangyou Xu
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Paper Abstract

This paper presents an event based soccer video retrieval method, where the scoring even is detected based on Bayesian network from six kinds of cue information including gate, face, audio, texture, caption and text. The topology within the Bayesian network is predefined by hand according to the domain knowledge and the probability distributions are learned in the case of the known structure and full observability. The resulting event probability from the Bayesian network is used as the feature vector to perform the video retrieval. Experiments show that the true and false detection rations for the scoring event are about 90% and 16.67% respectively, and that the video retrieval result based on event is superior to that based on low-level features in the human visual perception.

Paper Details

Date Published: 25 September 2003
PDF: 6 pages
Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); doi: 10.1117/12.538784
Show Author Affiliations
Xinghua Sun, Tsinghua Univ. (China)
Guoying Jin, Tsinghua Univ. (China)
Mei Huang, Tsinghua Univ. (China)
Guangyou Xu, Tsinghua Univ. (China)

Published in SPIE Proceedings Vol. 5286:
Third International Symposium on Multispectral Image Processing and Pattern Recognition
Hanqing Lu; Tianxu Zhang, Editor(s)

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