A new resampling strategy about particle filter algorithm applied in Monte Carlo framework
In this paper we propose a new resampling strategy about particle filter algorithm for tracking object in video sequence. We incorporate the new resampling strategy and adaptive elliptical template with the classical particle filter algorithm. We apply enhanced algorithm to track selected object in a standard video and demonstrate its performance compared with the algorithm proposed by K. Nummiaro. Experimental results show that the proposed particle filter algorithm improves the efficiency of tracking system, while it is unfluctuating even if the surroundings of visual tracking are under heavy fog.
resampling particle filter monte carlo tracking
Gang Wu Zhenmin Tang
School of Computer Science & Technology Nanjing University of Science and Technology Nanjing, China
国际会议
长沙
英文
507-510
2009-10-10（万方平台首次上网日期，不代表论文的发表时间）