Discrete Laplace–Beltrami operators for shape analysis and segmentation |
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| Authors: | Martin Reuter Silvia Biasotti Daniela Giorgi Giuseppe Patan Michela Spagnuolo |
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| Affiliation: | aMassachusetts Institute of Technology, Cambridge, MA, USA;bA.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA;cIstituto di Matematica Applicata e Tecnologie Informatiche - Consiglio Nazionale delle Ricerche, Genova, Italy |
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| Abstract: | Shape analysis plays a pivotal role in a large number of applications, ranging from traditional geometry processing to more recent 3D content management. In this scenario, spectral methods are extremely promising as they provide a natural library of tools for shape analysis, intrinsically defined by the shape itself. In particular, the eigenfunctions of the Laplace–Beltrami operator yield a set of real-valued functions that provide interesting insights in the structure and morphology of the shape. In this paper, we first analyze different discretizations of the Laplace–Beltrami operator (geometric Laplacians, linear and cubic FEM operators) in terms of the correctness of their eigenfunctions with respect to the continuous case. We then present the family of segmentations induced by the nodal sets of the eigenfunctions, discussing its meaningfulness for shape understanding. |
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| Keywords: | Laplace– Beltrami operator Eigenfunctions Nodal sets Nodal domains Shape analysis Shape segmentation |
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