An adaptive weight values updating mean shift tracking algorithm
Traditional mean shift tracking algorithm set weight value of pixels according to the distance between pixel and center of model. But it is obviously unreasonable during the tracking of asymmetric or non-rigid object, such as human. In this paper, a novel adaptive weight values updating mean shift tracking algorithm is proposed, weight value of every pixel is updated according to variation of motion state calculated by a group of Kalman filters. In this paper, this method is applied in human motion tracking, the result of experiment based on supervision video show that it has advantage on reliability and robustness.
mean shift Kalman filter template update human motion tracking
Guo Sen Lui Wei Lu Xin Liang YongSen
ShenZhen institute of information technology,ShenZhen,518029
国际会议
2009 IEEE International Conference on Information and Automation(2009年 IEEE信息与自动化国际学术会议)
珠海、澳门
英文
790-794
2009-06-22（万方平台首次上网日期，不代表论文的发表时间）