Abstract: In traditional Mean shift algorithm ,color histogram is usually used as the features vectors. And the dissimilarity between the referenced targets and the target candidates is expressed by the metric derived from the Bhattacharyya coefficients .The traditional mean shift procedure is used to find the real position of the object through looking for the regional minimum of the distance function iteratively .But there exists some limits because loss of space distribution .To overcome this problem ,the method based on correlation between kernel density estimation of tracking region is proposed. Furthermore, some experiments manifest it can improve accuracy and robustness of this tracking algorithm.

Key words: object tracking, Mean shift, kernel density estimation, kernel density correlation