计算机应用研究2011，Vol.28Issue(8)：3155-3158,4.DOI:10.3969/j.issn.1001-3695.2011.08.099
基于多特征融合的头部跟踪方法研究
Head tracking method based on multi-feature fusion
摘要
Abstract
In order to effectively solve the poor performance of head tracking,this paper proposed a new method based fusing measurements of head by using D-S evidence theory. It used Mean-Shift algorithm to produce more effective particles that approached the real posterior distribution in the framework of particle filter. The proposed method used the color and distance to maximum gradient point ( DMG) features as the observation model,and efficiently avoided the unstable problems via using single color feature in the illumination of mutation,posture change, greater distance and similar background. Experiment results indicate the proposed method is more robust to present object and has good performance in complex scene.关键词
头部跟踪/多特征融合/粒子滤波/最大梯度距离测量Key words
head tracking/ multi-feature fusion/ particle filter/ distance to maximum gradient point (DMC)分类
信息技术与安全科学引用本文复制引用
曹洁,李伟..基于多特征融合的头部跟踪方法研究[J].计算机应用研究,2011,28(8):3155-3158,4.基金项目
甘肃省自然科学基金资助项目(10101RJZA046) （10101RJZA046）
甘肃省教育厅研究生导师基金资助项目(0914ZTB003) （0914ZTB003）
甘肃省财政厅资助项目(0914ZTB148) （0914ZTB148）
