A motion tracking method based on Kalman filter combined with mean-shift

Abstract

In this paper, it proposes an object tracking algorithm based-on the Kalman filter combined with the mean-shift algorithm. It can predict the object motion more accurate with Kalman filter, including position and velocity. And the adjacent locations of the predicted point are defined as the search window. In the search window, the position of object is fixed on by mean-shift. The experiment results show that this algorithm can make full use of the prediction function of Kalman filter, improve the search speed, and achieve a more accurate tracking even the color is similar, and also solve the problem of shelter to some extent.