基于立方体模型和EKF的运动汽车跟踪算法研究  

Research on moving vehicles tracking algorithm based on cube model and EKF

作　　者：曹洁[1] 王伟[1] 

机构地区：[1]兰州理工大学电气工程与信息工程学院,兰州730050

出　　处：《计算机工程与应用》2010年第22期236-238,241,共4页Computer Engineering and Applications

基　　金：甘肃省自然科学基金No.0710RJZA060~~

摘　　要：针对固定摄像机、大范围复杂交通场景,提出了一种运动汽车的实时跟踪算法。根据汽车的刚体特性,采用立方体模型与运动汽车图像进行匹配的算法,避免三维重建的难题,能较为直观地得到运动汽车的形体信息。结合车辆的非线性运动特征引入EKF算法,准确地预测车辆的相关参数信息,减少目标跟踪过程中的搜索时间,从而能够实时准确地跟踪运动汽车目标。通过真实交通视频仿真实验,该算法具有较好的跟踪能力和抗干扰性能。This paper presents a real-time monitoring of moving vehicles detection and tracking algorithm under wide range complex transportation scenes with a fixed camera.According to the rigid body characteristic of vehicles, uses the cube mod- el matching with the moving cars image, avoids the three dimensional reconstruction problem,and obtains the physique infor- mation of moving cars intuitively.Combined with the non-linear motion characteristic of vehicles, the paper introduces the EKF algorithm, it can approximately forecast the related parameter information of the target, and reduce the search time of the target tracking,therefore it can track the object with real-time and accurately.Through the real transportation video simula- tion experiment,the algorithm has a good tracking ability and anti-disturbing capability.

关 键 词：立方体模型 扩展卡尔曼滤波(EKF) 运动汽车 跟踪算法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]