A Multi-Feature Fusion Tracking Method Based on Mean Shift and Particle Filter

Abstract

In order to improve the robustness of visual tracking in complex environments, a novel multi-feature fusion tracking method based on mean shift and particle filter is proposed. In the proposed method, the color and shape information are adaptively fused to represent the target observation, and incorporating mean shift method into particle filter method. The method can overcome the degeneracy problem of particle. Experimental results demonstrate that this method can improve stability and accuracy of tracking.