智能视频分析的车辆异常行为检测方法

针对目前车辆异常行为检测中的检测实时性问题,提出了一种基于智能视频分析技术的车辆异常行为检测方法。车辆出现异常行为时车辆位置变化、速度变化及运动方向变化较大。通过背景差分法检测运动车辆,并采用均值漂移算法跟踪运动车辆,获取车辆位置、速度、运动方向等车辆异常行为判别参数,对3种判别参数的状态函数加权融合检测车辆行为。为验证该算法的有效性,将对真实交通场景中采集的交通视频进行车辆运行状态检测实验。实验结果证明该算法能及时有效地检测出交通场景中的车辆异常行为。

A vehicle abnormal behavior detection method based on intelligent video analysis

In this paper, an intelligent-video-analysis-based vehicle abnormal behavior detection method was presented to handle the real-time problem in vehicle abnormal behavior detection. When vehicle abnormal behavior occurs, vehicle position, velocity and moving direction change rapidly. To extract the changes of the three parameters mentioned above, the background subtraction approach was adapted to detect vehicles. Furthermore the meanshift algorithm was utilized to track the detected vehicles. Vehicle behavior decision can be concluded by weight fusion of the three parameters. To verify the proposed method, experiments on real videos were operated. Experimental results demonstrate that the proposed method can detect vehicle abnormal behavior effectively in real traffic scene.