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An Elastic Basis for Spectral Shape Correspondence

Florine Hartwig, Josua Sassen, Omri Azencot, Martin Rumpf, Mirela Ben-Chen

2023Year
21Citations
8Top-tier citations

Abstract

Finding correspondences between shapes is a central task in geometry processing with applications such as texture or deformation transfer and shape interpolation. We develop a spectral method for finding correspondences between non-isometric shapes that aligns extrinsic features. For this, we propose a novel crease aware spectral basis, that is derived from the Hessian of an elastic thin shell energy. We incorporate this basis in a functional map framework and demonstrate the effectiveness of our approach for mapping non-isometric shapes such that prominent features are put in correspondence. Finally, we describe the necessary adaptations to the functional map framework for working with non-orthogonal basis functions, thus considerably widening the scope of future uses of spectral shape correspondence.

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