Fast and Robust RGB-D Multiple Human Tracking Based on Part Model for Mobile Robots

Abstract

In this paper, we address the problem of multiple human tracking for mobile robots and proposed a fast and robust RGB-D multiple human tracking approach based on part model. Firstly, a simplified deformable part model method is used for fast human detection using RGB-D information. Then the partial occlusion is detected with depth information. Finally, part model and partial occlusion information are combined into data association process and an on-line appearance classification method with dynamic occlusion handling is proposed for robust tracking. The performance of the proposed method is evaluated on the public dataset, and experiment results have demonstrated the effectiveness of the proposed method.