Abstract

The task of estimating complex non-rigid 3D motion through a monocular camera is of increasing interest to thewider scientific community. Assuming one has the 2D pointtracks of the non-rigid object in question, the vision com-munity refers to this problem as Non-Rigid Structure fromMotion (NRSfM). In this paper we make two contributions. First, we demonstrate empirically that the current state of the art approach to NRSfM (i.e. Dai et al. [5]) exhibits poor reconstruction performance on complex motion (i.e motions involving a sequence of primitive actions such as walk, sit and stand involving a human object). Second, we propose that this limitation can be circumvented by modeling com-plex motion as a union of subspaces. This does not naturally occur in Dai et al.’s approach which instead makes a less compact summation of subspaces assumption. Experiments on both synthetic and real videos illustrate the benefits of our approach for the complex nonrigid motion analysis.