复杂背景下车辆跟踪的改进算法及逆行检测  

The Improved Algorithm for Vehicle Tracking and Retrograde Motion Detection under the Complicated Background

作　　者：郭锋[1] 王秉政[1] 杨晨晖[2] 

机构地区：[1]郑州轻工业学院计算机与通信工程学院,河南郑州450002 [2]厦门大学信息科学与技术学院,福建厦门361005

出　　处：《图学学报》2013年第4期150-153,共4页Journal of Graphics

摘　　要：针对复杂背景下车辆跟踪准确率低的情况,提出了一种改进的算法,采用多边形车辆跟踪窗口和更准确的预测搜索区域,进行多特征匹配车辆的跟踪算法,并应用于道路的车辆逆行检测。实验结果表明,该算法在满足实时性和稳定性的前提下,提高了车辆跟踪的准确率。To solve the problem of low vehicle tracking accuracy of traditional algorithms in complex background, an improved method is proposed in this paper. It exploits vehicle tracking polygon window and more exact prediction of search area to realize multiple feature matching vehicle tracking, which is applied to detect vehicles retrograde motion. The experimental results show that the algorithm has higher vehicle tracking accuracy while satisfying the need of real-time and stability requirement than traditional ones.

关 键 词：车辆跟踪 多特征匹配 复杂背景 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]