计算机工程与应用Issue(14)：186-190,5.DOI:10.3778/j.issn.1002-8331.1309-0102
基于PF的窗口自适应Mean-Shift跟踪算法
Mean-Shift tracking algorithm with adaptive window based on PF
张万绪 1姜卫琳 1张晓军1
作者信息
- 1. 西北大学 信息科学与技术学院，西安 710127
- 折叠
摘要
Abstract
The deficiency of Mean-Shift algorithm in the video tracking is that the bandwidth of kernel function is fixed, so the algorithm can’t have an effective tracking when distinct sale of the object changes. Aiming to this problem, a modi-fied method in this paper is proposed that is multi-scale space theory combined with Particle Filter(PF). The information in the tracking window is calculated by the multi-scale space theory. The information which is predicted and modified by the particle filter is introduced to get the proportion of the object area and the tracking algorithm is achieved to have adap-tive window ability. The experimental results show that the improved algorithm could track the target efficiently in the sce-narios that not only the object scale increases but the scale decreases as well.关键词
目标跟踪/Mean-Shift算法/多尺度信息度量/粒子滤波器Key words
target tracking/mean-shift algorithm/multi-scale information measures/particle filter分类
信息技术与安全科学引用本文复制引用
张万绪,姜卫琳,张晓军..基于PF的窗口自适应Mean-Shift跟踪算法[J].计算机工程与应用,2015,(14):186-190,5.
