Partial Functional Correspondence
Computer Vision and Pattern Recognition
2015-12-23 v2
Abstract
In this paper, we propose a method for computing partial functional correspondence between non-rigid shapes. We use perturbation analysis to show how removal of shape parts changes the Laplace-Beltrami eigenfunctions, and exploit it as a prior on the spectral representation of the correspondence. Corresponding parts are optimization variables in our problem and are used to weight the functional correspondence; we are looking for the largest and most regular (in the Mumford-Shah sense) parts that minimize correspondence distortion. We show that our approach can cope with very challenging correspondence settings.
Cite
@article{arxiv.1506.05274,
title = {Partial Functional Correspondence},
author = {Emanuele Rodolà and Luca Cosmo and Michael M. Bronstein and Andrea Torsello and Daniel Cremers},
journal= {arXiv preprint arXiv:1506.05274},
year = {2015}
}