Crowd Event Detection Based on Motion Vector Intersection Points

摘要：

This paper presents an event detection approach in crowd surveillance videos based on motion vector intersection points. It contains three steps: firstly,to extract the local motion vectors by feature tracking. Secondly,to select appropriate pairs of motion vectors and calculate three types of intersection points which represent the spatial character of crowd event. And the final step is to obtain the intersection point clusters by density based clustering,and then to detect the events by searching the most possible candidate and voting. Experimental results show that the presented approach can effectively detect the concurrent events of different densities and within different ranges controlled by parameters. The results also show that the proposed approach is robust to illumination,shadows and noise from event itself.

关键词： Crowd Scene Surveillance Video Event Detection Motion Vector Intersection Point

作者: Guohui Li Jun Chen Boliang Sun Haozhe Liang

作者单位: Key Laboratory of Information System Engineering,National University of Defense Technology,Changsha 410073,China

会议类型: 国际会议

会议名称: 2011 International Conference on Opto-Electronics Engineering and Information Science(2011光电电子工程与信息科学国际会议 ICOEIS 2011)

会议地点: 西安

会议语种:英文

页码: 2630-2634

在线出版日期: 2011-12-23（万方平台首次上网日期，不代表论文的发表时间）