高速公路中的行车道检测和车辆跟踪

提出了一种有效的高速公路检测和多车辆跟踪视觉系统.该系统主要模块包括道路检测、基于二维模型的车辆跟踪器(近距离车辆的矩形模型和远距离车辆的U形模型)、启发式车辆检测、系统协调器.在系统中,跟踪器的动态产生和终止优化了系统的计算资源.另外,系统利用鲁棒性估计技术提高了道路检测的性能.车辆的跟踪是采用三参数状态空间的多边形拟合技术来实现的.本文采用了PETS2001提供的图像序列测试了系统有效性,在Pentium Ⅲ 450MHz PC 上系统的处理速度为平均每帧12毫秒.

Lane Detection and Car Tracking on the Highway

An efficient vision system is proposed for lane detection and multiple car tracking on the highway. The main modules of the system are: lane detection, separate 2-D model-based trackers (rectangular model for passing car and U-shape model for distant car), heuristic car detection, and a process coordinator. In the system, the dynamical creation and termination of tracking processes optimizes the amount of spent computational resources. Lane detection performance is improved by robust estimation technique. And car tracking is realized by a polygon fitting approach in three-parameter state space. The system is successfully tested with the image sequence from PETS2001 and the average processing time per frame is 12ms on a Pentium Ⅲ 450MHz PC.