中文摘要：

基于视频的车辆跟踪在交通监控领域有着重要的实用价值．为了有效地跟踪视频车辆，文中首先提出了一种结合虚拟检测线的统计背景提取方法，然后运用背景差法提取运动车辆信息，再在运动车辆区域运用SUSAN（Smallest Univalue Segment Assimilating Nucleus）算法提取车辆角点特征，在此基础上运用强化学习进行车辆跟踪，充分发挥了强化学习搜索效率高的特性．实验结果表明：文中方法跟踪情况稳定，跟踪准确率比较高，可以获得很好的跟踪效果．

英文摘要：

As the video vehicle tracking is of great importance to the traffic monitoring, a statistical background extraction method combined with the virtual detection line is p video vehicles. Then, the background difference method is employed to extract the information of moving vehicles, and the SUSAN algorithm is adopted to extract the comer feature in the moving vehicle region. Moreover, the reinforcement learning theory with high searching efficiency is applied to the video vehicle tracking. Experimental results show that the proposed method helps to obtain satisfying tracking results due to its good stability and high tracking accuracy.