Group-valued regularization framework for motion segmentation of dynamic non-rigid shapes

21Citations
Citations of this article
13Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Understanding of articulated shape motion plays an important role in many applications in the mechanical engineering, movie industry, graphics, and vision communities. In this paper, we study motion-based segmentation of articulated 3D shapes into rigid parts. We pose the problem as finding a group-valued map between the shapes describing the motion, forcing it to favor piecewise rigid motions. Our computation follows the spirit of the Ambrosio-Tortorelli scheme for Mumford-Shah segmentation, with a diffusion component suited for the group nature of the motion model. Experimental results demonstrate the effectiveness of the proposed method in non-rigid motion segmentation. © 2012 Springer-Verlag.

Cite

CITATION STYLE

APA

Rosman, G., Bronstein, M. M., Bronstein, A. M., Wolf, A., & Kimmel, R. (2012). Group-valued regularization framework for motion segmentation of dynamic non-rigid shapes. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6667 LNCS, pp. 725–736). https://doi.org/10.1007/978-3-642-24785-9_61

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free