Hybrid Functional Maps for Crease-Aware Non-Isometric Shape Matching

arXiv:2312.03678v2 Announce Type: replace
Abstract: Non-isometric shape correspondence remains a fundamental challenge in computer vision. Traditional methods using Laplace-Beltrami operator (LBO) eigenmodes face limitations in characterizing high-frequency extrinsic shape changes like bending and creases. We propose a novel approach of combining the non-orthogonal extrinsic basis of eigenfunctions of the elastic thin-shell hessian with the intrinsic ones of the LBO, creating a hybrid spectral space in which we construct functional maps. To this end, we present a theoretical framework to effectively …

abstract arxiv challenge computer computer vision cs.cv elastic face functional hybrid limitations maps novel shell type vision