关键词: 视频监控序列, 目标跟踪, 时空上下文, 异常分析, 稀疏重构算法

Abstract: In order to identify abnormal behavior in the video surveillance, first of all, it tracks the pedestrian, and then analyzes the trajectory to determine whether there is abnormal behavior. In the pedestrian tracking, the Kalman filter and spatial-temporal context algorithm are combined together, which can effectively avoid the shelter problem in complicated background. In the analysis of abnormal behavior, the trajectory is classified according to the shape to get the normal trajectory scenario set. It analyzes the trajectory by optimized sparse reconstruction algorithm and distinguishes normal or abnormal according to the reconstruction residual. The experimental results show that the proposed method has higher recognition rate compared with the original method.

Key words: video monitoring sequence, target tracking, spatial-temporal context, abnormal analysis, sparse reconstruction algorithm