Dynamic Human Surface Reconstruction Using a Single Kinect

This paper presents a system for robust dynamic human surface reconstruction using a single Kinect. The single Kinect provides a self-occluded and noisy RGBD data. Thus it is challenging to track the whole human surface robustly. To overcome both incompleteness and data noise, we adopt a template to confine the shape in the un-seen part, and propose a two-stage tracking pipeline. The first stage tracks the articulated motion of the human, which improves robustness of tracking by introducing more constraints between the surface points. The second stage tracks movements of non-articulated motion. For long sequences, we stabilize the human surface in the un-seen part by directly warping the surface from the first frame to the current frame according to sequentially tracked correspondences, preventing surface from collapsing caused by error accumulation. We demonstrate our method by several real captured RGBD data, containing complex human motion. The reconstruction results show the effectiveness and robustness of our method.