Image Sequences Based Traffic Incident Detection for Signaled Intersections Using HMM

摘要：

For an intelligent transportation system (ITS), traffic incident detection is one of the most important issues, especially for urban area which is full of signaled intersections. In this paper, we propose a novel traffic incident detection method based on the image signal processing and hidden Markov model (HMM) classifier. First, a traffic surveillance system was set up at a typical intersection of china, traffic videos were recorded and image sequences were extracted for image database forming. Second, compressed features were generated through several image processing steps, image difference with FFT was used to improve the recognition rate. Finally, HMM was used for classification of traffic signal logics (East-West, West-East, South-North, North-South) and accident of crash, the total correct rate is 74％ and incident recognition rate is 84％. We believe, with more types of incident adding to the database, our detection algorithm could serve well for the traffic surveillance system.

关键词： ITS Incident Detection HMM Intersection

作者: Yuexian ZOU Guangyi SHI Hang SHI Yiyan WANG

作者单位: School of Computer & Information Engineering, Shenzhen Graduate School of Peking University

会议类型: 国际会议

会议名称: 2009 Ninth International Conference on Hybrid Intelligent Systems(第九届混合智能系统国际会议 HIS 2009)

会议地点: 沈阳

会议语种:英文

页码: 1-5

在线出版日期: 2009-08-12（万方平台首次上网日期，不代表论文的发表时间）