%0 Journal Article
%T Particle Filter and Mean Shift Tracking Method Based on Multi-feature Fusion<br>基于多特征融合的均值迁移粒子滤波跟踪算法
%A Li Yuan-zheng Lu Zhao-yang Gao Quan-xue Li Jing
%A <br>李远征
%A 卢朝阳
%A 高全学
%A 李静
%J 电子与信息学报
%D 2010
%I 
%X Object tracking by using single color feature results in a poor performance in robustness. To solve this problem, an object tracking method based on multi-features fusion is presented. The proposed method uses the color and texture features extracted by Local Binary Pattern(LBP) to present the interested target, performs a feature fusion in mean-shift and particle filter algorithms, and efficiently avoids the unstable problems via using single color feature for representation. The two common used fusion rules are used,thus overcoming the degeneracy problem and resulting in low computational cost. Experimental results indicate the proposed method is more robust to present object and has good performance in complex scene.
%K Object tracking
%K Multi-feature fusion
%K Particle filter
%K Mean shift
%K Local Binary Pattern(LBP)<br>目标跟踪
%K 多特征融合
%K 粒子滤波
%K 均值迁移
%K 局部二值模式
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=EFC0377B03BD8D0EF4BBB548AC5F739A&aid=7ED0F9F9D06F113F6123F9B315589339&yid=140ECF96957D60B2&vid=9971A5E270697F23&iid=0B39A22176CE99FB&sid=34D9E20AD82A0D72&eid=BFB86B6ED3A99B9D&journal_id=1009-5896&journal_name=电子与信息学报&referenced_num=3&reference_num=14