Non-Rigid Structure-From-Motion With Uniqueness Constraint and Low Rank Matrix Fitting Factorization

Abstract

Non-rigid structure-from-motion is one of the difficult and challenging problems in computer vision, especially when the only input available is 2D correspondences in monocular video sequence. This paper proposed a new constraint based framework for underconstrained non-rigid structure-from-motion problem to constrain the space of solution. The proposed method is based on a point trajectory approach with an additional uniqueness constraint applied to shape coefficients to reduce the basis required to construct the non-rigid 3D shape. A framework for occluded and incomplete measured data is also proposed using low rank matrix fitting which is a robust factorization scheme for the matrix completion problem. This method offers not only new theoretical insight, but also a practical, everyday solution, to non-rigid structure-from-motion. The proposed method is positively compared to the state-of-the-art in non-rigid structure-from-motion, providing improved results on high-frequency deformations of both articulated and simpler deformable shapes.