智能交通系统中基于视频图像处理的车辆检测与跟踪方法综述

Review on Vehicle Detection and Tracking Techniques Based on Video Processing in Intelligent Transportation Systems

与传统的车辆检测器相比,基于视频图像处理与视觉技术的车辆检测器具有处理速度快、安装维护便捷且费用较低、可监视范围广、可获取更多种类的交通参数等诸多优点,因而近年来在智能交通系统(ITS)中得到了越来越广泛的应用。针对摄像头拍摄得到的交通序列图像,人们提出了很多视频图像处理和分析技术,其中最基本的研究领域就是交通场景中车辆对象的检测与跟踪。介绍了近年来提出的一些主要的车辆检测与跟踪技术,并根据核心处理方法(基于特征、区域或模型等)及处理域(空域、时域)的不同对这些技术进行了分类,同时分析比较了各种方法的优缺点。最后,说明了这一领域仍然存在的问题和对可能的研究方向进行了一定的预测。

Compared with traditional traffic detectors, the video sensor has lots of advantages such as fast response, easy installation and maintenance, the ability to monitor wide areas and obtain more kinds of traffic parameters, and as a result, it has been widely used in Intelligent Traffic System（ITS） in recent years. Up to now, a number of video processing and analyzing methods have been proposed for vehicle detection and tracking. In this paper, vehicle detection and tracking techniques are introduced and categorized based on their key processing techniques （feature, area or model） and processing domain （spatial or temporal）, the advantages and disadvantage of each method are also analyzed. Additionally, the problems that still exist and the trend of the research in this field in the future are indicated.