Abstract:

In video surveillance scenes, the abnormal events, such as a sudden run, the crowd abnormal aggregation phenomenon, are studied. A corner motion history image strategy is used for behavior recognition. Firstly, the corner extraction algorithm is used as scene corner extraction. Secondly, through time accumulated, the corner historical image is constructed. And all corners are divided into static and dynamic corner point. Finally, through the dynamic corner analysis, the abnormal behavior is under analysis and recognition. The new algorithm makes full use of image information, overcomes the illumination effect, and enhances the abnormal behavior detection and recognition accuracy. Through the real scene experiments show that the new algorithm can be used for different scenes. It can get accurate detection for abnormal behavior, and the detection speed meets the needs of practical application.

Key words: corner detection;motion history image (MHI);abnormal behavior;slide window