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Proceedings Paper

Automatic event recognition and anomaly detection with attribute grammar by learning scene semantics
Author(s): Lin Qi; Zhenyu Yao; Li Li
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Paper Abstract

In this paper we present a novel framework for automatic event recognition and abnormal behavior detection with attribute grammar by learning scene semantics. This framework combines learning scene semantics by trajectory analysis and constructing attribute grammar-based event representation. The scene and event information is learned automatically. Abnormal behaviors that disobey scene semantics or event grammars rules are detected. By this method, an approach to understanding video scenes is achieved. Further more, with this prior knowledge, the accuracy of abnormal event detection is increased.

Paper Details

Date Published: 15 November 2007
PDF: 7 pages
Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67864Y (15 November 2007); doi: 10.1117/12.752712
Show Author Affiliations
Lin Qi, Ocean Univ. of China (China)
Zhenyu Yao, Lotus Hill Institute for Computer Vision and Information Science (China)
Li Li, Ocean Univ. of China (China)


Published in SPIE Proceedings Vol. 6786:
MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition

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