An Efficient Multi-Cue Fusion Based Sequential Monte Carlo Method for Image Sequence-Based Tracking

摘要：

This paper presents an efficient image sequence tracking method based on multiple cues fusion in the sequential monte carlo method. we combine backgroundweighted color histogram with edge histogram into sequential monte carlo algorithm for tracking. The color-based histogram is robust against noise and partial occlusion, but suffers from the presence of the confusing colors in the background. So, background-weighted color histogram is used to describe objects color feature. The edge feature may provide complementary information for tracking as well. Color histograms and edge histograms are used to model the object observations likelihoods function. These observations are used to obtain a posterior probability distribution for the location of the object in the sequence images based on sequential Monte Carlo method. The experiments on real image sequences have shown that the combination of color for tracking with other image feature can achieve more robust tracking.

关键词： Image sequence-based tracking sequential Monte Carlo method multi-cue fusion

作者: Guilan Feng

作者单位: College of Optical and Electronic Science, China Jilians University, Hangzhou 310018

会议类型: 国际会议

会议名称: 2011 International Conference on Electronics and Optoelectronics(2011电子学与光电子学国际会议 ICEOE 2011)

会议地点: 大连

会议语种:英文

页码: 51-55

在线出版日期: 2011-07-29（万方平台首次上网日期，不代表论文的发表时间）