Reconstruct 3D human motion from monocular video using motion library

In this paper, we present a new approach to reconstruct 3D human motion from video clips with the assistance of a precaputred motion library. Given a monocular video clip recording of one person performing some kind of locomotion and a motion library consisting of similar motions, we can infer the 3D motion from the video clip. We segment the video clip into segments with fixed length, and by using a shape matching method we can find out from the motion library several candidate motion sequences for every video segment, then from these sequences a coarse motion clip is generated by performing a continuity test on the boundaries of these candidate sequences. We propose a pose deformation algorithm to refine the coarse motion. To guarantee the naturalness of the recovered motion, we apply a motion splicing algorithm to the motion clip. We tested the approach using synthetic and real sports videos. The experimental results show the effectiveness of this approach.