A stereo camera based full body human motion capture system using a partitioned particle filter

In this paper, we propose a marker-less full body human motion capture system designed for humanoid robot applications. The system is based on a stereo camera, and therefore has strong portability. Tracking is implemented within the particle filter framework, and the high dimensionality problem is solved through partitioned sampling. Taking advantage of the stereo setup, we propose a depth cue which resolves the problem of missing depth information in monocular tracking. Three other cues, the edge cue, the color cue and the distance cue, are also integrated into the system to enhance the tracking performance. The system is tested using the publicly available CMU MOCAP database which also includes ground truth data, and this enables us to analyze the results quantitatively and compare the relative usefulness of different cues. The system is shown to be capable of tracking challenging videos accurately and robustly in near real-time.