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Computing a high-dimensional euclidean embedding from an arbitrary smooth riemannian metric

Abstract : This article presents a new method to compute a self-intersection free high-dimensional Euclidean embedding (SIFHDE) for surfaces and volumes equipped with an arbitrary Riemannian metric. It is already known that given a high-dimensional (high-d) embedding, one can easily compute an anisotropic Voronoi diagram by back-mapping it to 3D space. We show here how to solve the inverse problem, i.e., given an input metric, compute a smooth intersection-free high-d embedding of the input such that the pullback metric of the embedding matches the input metric. Our numerical solution mechanism matches the deformation gradient of the 3D → higher-d mapping with the given Riemannian metric. We demonstrate applications of the method, by being used to construct anisotropic Restricted Voronoi Diagram (RVD) and anisotropic meshing, that are otherwise extremely difficult to compute. In the SIFHDE-space constructed by our algorithm, difficult 3D anisotropic computations are replaced with simple Euclidean computations, resulting in an isotropic RVD and its dual mesh on this high-d embedding. The results are compared with the state-ofthe-art in anisotropic surface and volume meshings using several examples and evaluation metrics.
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Contributor : Bruno Levy <>
Submitted on : Friday, April 30, 2021 - 11:22:58 PM
Last modification on : Tuesday, May 4, 2021 - 3:32:55 AM


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Zichun Zhong, Wenping Wang, Bruno Lévy, Jing Hua, Xiaohu Guo. Computing a high-dimensional euclidean embedding from an arbitrary smooth riemannian metric. ACM Transactions on Graphics, Association for Computing Machinery, 2018, 37 (4), pp.1-16. ⟨10.1145/3197517.3201369⟩. ⟨hal-03214192⟩



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