Date of Original Version
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Abstract or Description
The task of estimating complex non-rigid 3D motion through a monocular camera is of increasing interest to the wider scientific community. Assuming one has the 2D point tracks of the non-rigid object in question, the vision community refers to this problem as Non-Rigid Structure from Motion (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. ) 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 complex motion as aunion 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.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2014, 1542-1549.