基于视频的单车道车辆逆行检测方法

针对城市单车道车辆逆行违章检测问题,研究了基于视频的单车道车辆逆行违章自动检测方法。使用背景差分法进行车辆检测;用 Harris角点特征补充Mean-shift算法的颜色特征,提高车辆跟踪精度,以此得出被跟踪车辆的运动轨迹;通过计算机对运动轨迹进行分析,自动地判断其是否为逆行。从逆行检测正确率和计算量两方面进行了对比实验,实验结果表明,该方法对车辆逆行检测效果良好。车辆平均逆行识别率达到约87.55%,与对比方法基本相当;在计算时间方面,文中方法平均每帧计算时间比对比方法少约1956ms,更具快速性。 

Vehicle Retrograde Detection Method on Single Lane Based on Video

This paper proposed a vehicle retrograde detection method on urban single lane based on video .First , background subtraction was used for moving vehicle detection .Second ,Harris corner features were combined to comple-ment the color features of Mean-shift to improve tracking accuracy ,from which motion trajectory of a vehicle can be com-puted .Finally ,the computed motion trajectory was analyzed for vehicle retrograde determination .Comparative experi-ments were conducted to evaluate retrograde detection accuracy and computational complexity .Experiment results show that the proposed detection method works well for vehicle retrograde detection .The average recognition rate is about 87 . 55% ,which is similar to that of the comparative method .However ,the proposed method has 19 .56 ms less computation time than the compared method ,therefore ,with fast processing speed .