Efficient Deformable Shape Correspondence via Kernel Matching
Authored by Matthias Vestner, Zorah Lähner, Amit Boyarski, Or Litany, Ron Slossberg, Tal Remez, Emanuele Rodolà, Alex M. Bronstein, Michael M. Bronsteins, Ron Kimmel, Daniel Cremers
Published in International Conference on 3D Vision (3DV) 2017
Abstract
We present a method to match three dimensional shapes under non-isometric deformations, topology changes and partiality. We formulate the problem as matching between a set of pair-wise and point-wise descriptors, imposing a continuity prior on the mapping, and propose a projected descent optimization procedure inspired by difference of convex functions (DC) programming.
Resources
Bibtex
@inproceedings{ vestner2017kernel,
author = { Matthias Vestner and Zorah Lähner and Amit Boyarski and Or Litany and Ron Slossberg and Tal Remez and Emanuele Rodolà and Alex M. Bronstein and Michael M. Bronsteins and Ron Kimmel and Daniel Cremers },
title = { Efficient Deformable Shape Correspondence via Kernel Matching },
booktitle = { International Conference on 3D Vision (3DV) },
year = { 2017 },
}