Automatic event recognition and anomaly detection with attribute grammar by learning scene semantics

被引:0
|
作者
Qi, Lin [1 ]
Yao, Zhenyu [2 ]
Li, Li [1 ]
Dong, Junyu [1 ]
机构
[1] Ocean Univ China, Dept Comp Sci, Beijing, Peoples R China
[2] Lotus Hill Inst Comp Vis & Informat Sci, Beijing, Peoples R China
关键词
scene semantics; attribute grammar; event recognition; abnormal behavior detection;
D O I
10.1117/12.752712
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
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.
引用
收藏
页数:7
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