Hybrid Functional Maps for Crease-Aware Non-Isometric Shape Matching
Lennart Bastian, Yizheng Xie, Nassir Navab, Zorah Lähner
Abstract
Laplace-Beltrami Eigenbasis Elastic Eigenbasis Hybrid Functional Map We propose a novel approach of hybridizing the eigenbases originating from different operators for mapping between function spaces in deformable shape correspondence. While the Laplace-Beltrami operator (LBO) eigenbasis is robust to coarse isometric deformations, it fails to encapsulate extrinsic characteristics between shapes. In contrast, elastic basis functions [21] align with high curvature details but lack the robustness for coarse isometric matching. The proposed hybrid basis can be used as a drop-in replacement for the LBO basis functions in modern functional map pipelines, improving performance in near-isometric, non-isometric, and topologically noisy settings.
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