Robust Motion Tracking in Video Sequences Using Particle Filter

摘要

A robust motion tracking algorithm based on color and motion information was presented. Color is an effective feature in visual object tracking because of its robustness against rotation and scale variation. Nevertheless, the color of an object may change with varying illuminations, different image capture devices and different visual positions. Here, the color and motion information were fused in our visual tracking applications. Particle filter was employed as the essential framework because of its capacity of dealing with Non-linear/Non-Gaussian models by randomly sampling in state space. A particle filter can generate several hypotheses simultaneously in state space by randomly sampling and evaluate the states by weighing them respectively. The similarity between prediction data and observation information depends on the integration of Bhattacharyya distance and spatial Euclidean distance. Experimental results show the effectiveness of the proposed approach.