第18卷第1期
2010年1月文章编号
1004-924X(2010)01-0234-06
光学精密工程
Optics and Precision Engineering
Vol.18No.1
Jan.2010
鲁棒的基于改进Mean-shift的目标跟踪
薛陈1.2，朱明1，陈爱华1.2
（1.中国科学院长春光学精密机械与物理研究所，吉林长春130033；
2.中国科学院研究生院，北京100039）
摘要：为了克服传统Mean-shift算法在跟踪运动目标时由于背景像素造成的定位偏差和由于遮挡造成的跟踪失效，提出了相应的改进措施。其一，根据初始赖目标和背景在颜色分布上的差异，建立对数似然图(log-likelihood image)，筛选出目标中与背景可区分性好的颜色特征建立目标模型，并以同样的方法在后续赖建立候选模型，从雨有效地减小背景像索的影响。另外，将候选区域划分为若干重叠的子块，分别利用Mean-shift算法对各个子块进行选代，以与目标区域相应子块最为匹配的子块的所在位置对整个目标重新定位，由此很好地实现了目标部分迹挡情况下的稳定跟踪。当目标被严重遮挡时，则采用简单的线性预测，估计下一赖目标可能出现的位置。实验结果表明；提出的改进算法可以准确地进行目标跟踪，对部分遮挡和严重遮挡都有较强的鲁棒性。
关键词：目标跟踪；Mean-shift;对数似然图；速档
中图分类号：TP301.6;TP391
文献标识码：A
RobustobjecttrackingbasedonimprovedMean-shiftalgorithm
XUEChen'-2,ZHUMing',CHENAi-hua'-2
(l.ChangchunInstituteof Optics，FineMechanics andPhysics， ChineseAcademyofSciences，Changchun130033，China;
2.GraduateUniversityofChineseAcademyof Sciences,Beijing100039,China)
Abstract: To overcome the shortcomings of the traditional Mean-shift algorithm for object tracking such as the localization error caused by background pixels and the tracking failure from the object occlusion, an im proved Mean-shift algorithm is proposed. Firstly, according to the difference of color distribution between the object and the background in the initial frame, a log-likelihood image is set up to select the discriminative color features for object modeling, and then the candidate modeling is established by the same way. By above oper ation,the effect of background pixels on the image has reduced greatly, Secondly, the whole candidate region is separated into several overlapped fragments, and every fragment is iterated by the Mean-shift. Then, the ob ject localization is reset by the location of fragment in the candidate region, which matches mostly to the corre sponding fragment in the object region. Experimental results show that the fragment based on the Mean-shift is very robust to partial occlusion. Furthermore, when object is severely occluded, the linear prediction can be used to estimate the probable location of the object in the next frame, These results prove that the tracking using
收稿日期：2008-12-08；修订日期：2009-01-16.
基金项目：国家863高技术研究发展计划资助项目（No.2005AA778032）