基于隐马尔科夫度量场模型的车辆检测和跟踪  

Detection and Tracking of Vehicles Based on Hidden Markov Measure Field Model

作　　者：何毅[1] 杨新[1] 

机构地区：[1]上海交通大学电子信息与电气工程学院,上海200240

出　　处：《上海交通大学学报》2008年第2期270-273,共4页Journal of Shanghai Jiaotong University

基　　金：国家自然科学基金(60572154)资助项目

摘　　要：针对多目标检测和跟踪过程中常发生的合并和分裂现象,提出一种对不同运动目标假设不同的运动模型,并基于隐马尔科夫度量场(HMMF)的检测和跟踪算法.为了更准确地估计目标的运动参数,还提出了一种简单有效的单目相机标定算法.仿真结果表明,文中算法对遮挡不敏感,即使在发生遮挡、合并或分裂情况时也能很好地跟踪运动目标.This paper presented a detecting and tracking muhiple motion objects method. The method designs dissimilar motion models for different objects which often merge and split each other in the surveillance video. The method based on hidden Markov measure field（HMMF） is robust for lost information. A simple and efficient calibration of monocular camera was also presented to get more accurate motion parameters. The simulation results show that the algorithm can successfully track objects even if the occlusion happens.

关 键 词：车辆检测 车辆跟踪 隐马尔科夫度量场 单目相机标定 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]