A New Tracking method based on Mean-SIFT and Particle Filter

摘要：

In order to solve the multi-target tracking problems in video sequence, this paper presents a algorithm integration Mean-Shift(MS) and particle filter(PF) called KMSPPF to tracking multi-target. The algorithm uses the K-means clustering results as the optimal input to the Particle Filter ,Mean Shift follows by resampling and then particles converge to the true state of the target, thus overcomes the traditional particle filter degradation and lessen the time of computing; it can also solve the problem of target occlusion. The experimental results show that the algorithm can reduce the computational cost while tracking multi-target, and ensure the performance simultaneously.

关键词： Mean Shift ParticleFilter traking

作者: Chuanwei Xiao

作者单位: College of Information Science and Technology Qingdao University of Science and Technology Qingdao, P.R.China

会议类型: 国际会议

会议名称: 2010 3rd International Conference on Advanced Computer Theory and Engineering(2010年第三届先进计算机理论与工程国际会议 ICACTE 2010)

会议地点: 成都

会议语种:英文

页码: 1-4

在线出版日期: 2010-08-20（万方平台首次上网日期，不代表论文的发表时间）