关键词: 智能视频监控, 密集人群, 异常事件检测, 全局光流图, 图像熵

Abstract: In the field of intelligent video surveillance, in order to improve the efficiency of abnormal event detection and the defects of present methods in poor real-time performance and applicability, this paper proposes a real-time and high efficiency method. This method firstly extracts the global optical flow value as the movement characters, and constructs the visualizing expression of global optical flow. Then the image entropy analysis is used to obtain the statistical parameter in normal conditions. Finally, the confidence interval in normal condition and the anomaly judgment formula are given, which can be used to detect the abnormal event. The experimental results show that, for the video size of 320×240, the average detection time can be as low as 0.031 s in each frame and the accuracy can reach above 96%. As a result, the method has high efficiency and good real-time.

Key words: intelligent video surveillance, dense crowd, abnormal event detection, global optical flow image, image entropy