Remarks on markerless human motion capture using multiple images of 3D articulated human CG model

This paper proposes markerless human motion capture using a 3D articulated computer generated (CG) model of the human body. The method of estimating human body posture is based on 2D matching between human silhouettes extracted from camera images and model silhouettes projected onto the corresponding camera planes in virtual space. Candidates for human model silhouette are generated using a Monte Carlo filter-based algorithm, and the normalised core-weighted XOR distance is introduced to calculate the likelihood rate between silhouettes. Experimental results show the feasibility and effectiveness of the proposed method for achieving markerless human motion capture.