一种有效的车辆跟踪算法与异常车辆检测

An Effective Vehicle Tracking Method and Abnormal Vehicle Detection

交通监控视频中车辆检测、跟踪与车型判别是智能交通监控系统的重要组成部分。本文运用W4背景减除法和光流法相结合的技术进行车辆检测。利用区域滤波和空洞填充方法提高目标检测精度。采用质心距离约束和目标大小约束条件实现目标区域之间的匹配和车辆跟踪。最后,根据车辆的几何形状特征对助动车等异常车辆进行检测和标记。通过对高速公路实际视频的测试表明,本算法对机动车进行了有效的跟踪与标记,并对道路上助动车等异常车辆进行了有效的检测。

The detection and tracking of vehicle in traffic surveillance video is the important part of the intelligent transportation system. This paper proposes a vehicle detection method by combining the W4 background subtraction and optical flow method. Regional filtering and holes filling technologies are utilized to improve the accuracy of target detection. Moreover, the constraint conditions on centroid distance and target size are employed to attain the matching between target regions and the tracking of vehicles. Finally, by means of the characteristics of geometric shape, some abnormal vehicles such as motorcycles are detected and labeled. The test results on real video of highway show that the proposed algorithm can effectively track and label motor vehicle, as well as detecting abnormal vehicles such as motorcycles.