Motion capture data recovery using skeleton constrained singular value thresholding

Abstract

Motion capture data could be missing due to imperfections during the acquisition process. Singular Value Thresholding is an effective method to recover missing motion capture data. However, its effectiveness decreases significantly when markers are missing for longer periods of time. To alleviate this problem, we utilize the fact that human bones are rigid to constrain inter-marker distances of specific sets of markers. We extend the Singular Value Thresholding method for mocap recovery to include skeleton constraints. On average, our proposed method improves on the Singular Value Thresholding method by 40%, and performs 4% better than a recent state of the art method at up to 11 times faster computation time.