基于颜色和LBP多特征的mean shift的跟踪算法  

Mean shift target tracking based on color and LBP features

作　　者：李菊[1,2] 余烨[1] 戴欢[2] 李克清[2] 苏勇刚[2] 曹明伟[1] 

机构地区：[1]合肥工业大学计算机与信息学院,安徽合肥230009 [2]常熟理工学院计算机科学与工程学院,江苏常熟215500

出　　处：《合肥工业大学学报（自然科学版）》2014年第5期578-581,共4页Journal of Hefei University of Technology：Natural Science

基　　金：国家自然科学青年基金资助项目(61300186);高等学校博士学科点专项科研基金资助项目(20120111110003);江苏省科技计划资助项目(BE2011376);苏州市科技计划资助项目(SGZ2010206;SYND201002);江苏省高校自然科学研究面上资助项目(13KJB510001)

摘　　要：mean shift目标跟踪使用任一个单独特征都很难对大幅度的光照、背景变化和车辆大范围运动具有强鲁棒性,如单一的颜色特征对光照较为敏感,光照突变容易导致目标丢失。当背景颜色和目标颜色相近时也易造成目标丢失,因此利用目标的单一特征信息往往很难实现鲁棒的目标跟踪。文章提出基于颜色和LBP多特征mean shift跟踪方法,使跟踪结果不再过分依赖某一特征,增强了对背景变化、目标大范围运动的鲁棒性。In mean shift target tracking,if a separate feature is used,it is very difficult to achieve strong robustness to substantial illumination,background changes or vehicle movement in large range.For example,the color feature is sensitive to light,so the light mutation easily leads to the target losing. When the background color and the target color are similar,the target is also easily lost.So it is often difficult to achieve robust target tracking by using single target feature information.In this paper,the mean shift tracking approach based on color and local binary pattern（LBP）features is proposed, which makes the tracking results no longer rely too much on one feature,and can enhance the robustness to background changes and large-range motion.

关 键 词：局部二值模式 直方图 巴氏距离 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]