A regression-based approach to recover human pose from voxel data

This paper deals with human body pose recovery from multiple cameras, which is a key task in monitoring of human activity. This regression-based approach relies on a 3D description of a body voxel reconstruction, combined with a decomposition of the estimation, which allows to recover a wide range of poses using synthetic training data. The precision of the proposed shape descriptor is quantitatively evaluated on synthetic data for a ground truth comparison, while the effectiveness of the whole system is qualitatively demonstrated on various real sequences.