Object tracking by the mean-shift of regional color distribution combined with the particle-filter algorithms

This paper presents a method for tracking a person in a video sequence in real time. In this method, the profile of color distribution characterises target's feature. It is invariant for rotation and scale changes. It is also robust to non-rigidity and partial occlusion of the target. We employ the mean-shift algorithm to track the target and to reduce the computational cost. Moreover, we incorporate the particle-filter into it to cope with a temporal occlusion of the target, and largely reduce the computational cost of the original particle-filter. Experiments show the availability of this method.