计算机技术与发展2017，Vol.27Issue(2)：106-109,4.DOI:10.3969/j.issn.1673-629X.2017.02.024
基于改进的均值漂移算法的运动汽车跟踪
Moving Vehicle Tracking Based on Improved Mean Shift
摘要
Abstract
The intelligent video surveillance system effectively solves the problem of real-time tracking of vehicles in transportation field.According to vehicle characteristics,a new algorithm combined of Mean Shift and particle filter is proposed to track the target.The algorithm takes the HSV color histogram as the core to establish the target model of moving vehicle,using the Bhattacharyya distance to measure the similarity between particle region and the target model and updating the particle weights according to the similarity.After that,Mean Shift is used to duster offset particles whose candidate region is closer to real target location through the observation model and re -estimation.Experimental results show that the algorithm has strong real-time performance and robustness,and can achieve the stable tracking of interest moving vehicles.关键词
均值漂移/粒子滤波/采样/目标跟踪Key words
Mean Shift/particle filter/sampling/target tracking分类
信息技术与安全科学引用本文复制引用
雷飞,孟晓琼,吕露,黄涛..基于改进的均值漂移算法的运动汽车跟踪[J].计算机技术与发展,2017,27(2):106-109,4.基金项目
北京市教育科技计划面上项目(KM201210005003) （KM201210005003）
