基于MCMC粒子滤波和MeanShift的运动目标跟踪方法研究
首发时间:2017-04-27
摘要:目前,很多跟踪方法已经被提出,并得到了一定的应用。常见的跟踪算法包括卡尔曼滤波、MeanShift方法、粒子滤波法等。本文通过改进的目标跟踪算法实现运动目标的跟踪。利用MCMC粒子滤波的鲁棒性和Mean Shift的快速收敛性,再结合改进的最近邻数据关联方法,实现多运动目标快速准确的跟踪。并对交叉路口视频中的车辆进行跟踪测试,实验结果表明本文算法能够有效地实现多运动目标跟踪。
关键词: 图像处理 MCMC粒子滤波 Mean Shift 目标跟踪
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Research on Moving Target Tracking based on MCMC Particle Filter and Mean Shift
Abstract:Many methods for tracking targets have been put forwarded, and practically applied. Common tracking algorithms contain Kalman filter, Mean shift algorithm and particle filter. The proposed tracking targets algorithm absorbs the rapid convergence of Mean Shift and the efficiency of MCMC particle filter for moving targets tracking. And we apply a nearest neighbor data association for multi-targets tracking. In the end, we experiment multi-vehicle tracking with the proposed algorithm in an intersection video from UAV. Results show that our approach performs well.
Keywords: image processing MCMC particle filter Mean Shift target tracking
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