Distributed Color-Based Particle Filter for Target Tracking in Camera Network

Abstract

Color-based particle filters have appeared in some literatures. However, there are still some important drawback in tracking targets, such as illumination changes, occlusion and low tracking accuracy. To solve these problems, in this paper, we propose a distributed color-based particle filter (DCPF) for target tracking, which can track targets accurately in a large-scale camera network with less data transmission and less computation. Compared with the previous algorithms, the algorithm proposed in this paper has two obvious advantages. First, the DCPF framework merges color features into the target’s state to obtain better robustness. Second, it considers the situation where the target is disappear in some cameras because of limited field of view (FoV). Convincing results are confirmed that the performance analysis of the proposed algorithm in this paper is very close to the centralized particle filter method.