Marker-less Human Motion Estimation using Articulated Deformable Model

This paper presents a novel whole body motion estimation method by fitting a deformable articulated model of the human body into the 3D reconstructed volume obtained from multiple video streams. The advantage of the proposed method is two fold: (1) combination of a robust estimator and ICP algorithm with Kd-tree search in pose and normal space make it possible to track complex and dynamic motion robustly against noise and interference between limb and torso, (2) the hierarchical estimation and backtrack re-estimation algorithm enable accurate estimation. The power to track challenging whole body motion in real environment is also presented.