Robust Tracking Method by Mean-Shift Using Spatiograms and Particle-Filter

Abstract

In this paper, we proposed the real time robust tracking method which combined mean-shift using the spatiograms with the particle-filter, and the proposed method can continue to track non-rigid objects with a temporal occlusion. The proposed method is using a tracker representing the center of the object and samples. At first the tracker tracks the object by using the Mean-Shift algorithm based on the spatiograms. Then, to avoid to be trapped by occlusion, the true target position is searched by using the particle-filter. The proposed method needs only small number of samples so that the computational cost can be reduced largely. We conducted experiments in order to compare the proposed method with the conventional Mean-Shift. As a result, the proposed method was more effective than the conventional method, when the object moved rotation or moved rapidly and a temporal occlusion occurred.