交通监控系统中运动目标分类和跟踪研究

文章讲述了交通监控系统中应用视频图像流来跟踪运动目标并对目标进行分类的具体过程和原则.基于目标检测提出了双差分的目标检测算法,目标分类应用到了连续时间限制和最大可能性估计的原则,目标跟踪则结合检测到的运动目标图像和当前模板进行相关匹配.实验结果表明,该过程能够很好地探测和分类目标,去除背景信息的干扰,并能够在运动目标部分被遮挡、外观改变和运动停止等情况下连续地跟踪目标.

This paper describes the detailed process and the principles for tracking and classifying targets in video streams of the Vision-Based Traffic Monitoring System. Based on object detection, it brings forward a double-difference algorithm, the principle of temporal consistency and maximum likelihood estimation are employed to target classification, and the tracking process combines the template with the current motion regions so as to obtain correlation matching. The experimental results identify that this process can robustly track and classify targets of interest, reject background clutter, and continually track objects over large distances despite occlusions, appearance change, and cessation of the target motion.