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Spectral Geometry Processing with Manifold Harmonics

Identifieur interne : 004733 ( Hal/Corpus ); précédent : 004732; suivant : 004734

Spectral Geometry Processing with Manifold Harmonics

Auteurs : Bruno Vallet ; Bruno Lévy

Source :

RBID : Hal:inria-00331894

Abstract

We present an explicit method to compute a generalization of the Fourier Transform on a mesh. It is well known that the eigenfunctions of the Laplace Beltrami operator (Manifold Harmonics) define a function basis allowing for such a transform. However, computing even just a few eigenvectors is out of reach for meshes with more than a few thousand vertices, and storing these eigenvectors is prohibitive for large meshes. To overcome these limitations, we propose a band-by-band spectrum computation algorithm and an out-of-core implementation that can compute thousands of eigenvectors for meshes with up to a million vertices. We also propose a limited-memory filtering algorithm, that does not need to store the eigenvectors. Using this latter algorithm, specific frequency bands can be filtered, without needing to compute the entire spectrum. Finally, we demonstrate some applications of our method to interactive convolution geometry filtering. These technical achievements are supported by a solid yet simple theoretic framework based on Discrete Exterior Calculus (DEC). In particular, the issues of symmetry and discretization of the operator are considered with great care.

Url:
DOI: 10.1111/j.1467-8659.2008.01122.x

Links to Exploration step

Hal:inria-00331894

Le document en format XML

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<div type="abstract" xml:lang="en">We present an explicit method to compute a generalization of the Fourier Transform on a mesh. It is well known that the eigenfunctions of the Laplace Beltrami operator (Manifold Harmonics) define a function basis allowing for such a transform. However, computing even just a few eigenvectors is out of reach for meshes with more than a few thousand vertices, and storing these eigenvectors is prohibitive for large meshes. To overcome these limitations, we propose a band-by-band spectrum computation algorithm and an out-of-core implementation that can compute thousands of eigenvectors for meshes with up to a million vertices. We also propose a limited-memory filtering algorithm, that does not need to store the eigenvectors. Using this latter algorithm, specific frequency bands can be filtered, without needing to compute the entire spectrum. Finally, we demonstrate some applications of our method to interactive convolution geometry filtering. These technical achievements are supported by a solid yet simple theoretic framework based on Discrete Exterior Calculus (DEC). In particular, the issues of symmetry and discretization of the operator are considered with great care.</div>
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<forename>Nicolas</forename>
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<title xml:lang="en">Spectral Geometry Processing with Manifold Harmonics</title>
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<forename type="first">Bruno</forename>
<surname>Vallet</surname>
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<persName>
<forename type="first">Bruno</forename>
<surname>Lévy</surname>
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<idno type="idHal">bruno-levy</idno>
<idno type="halAuthorId">136961</idno>
<idno type="arXiv">http://arxiv.org/a/brlevy</idno>
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<idno type="halJournalId" status="VALID">12023</idno>
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<title level="j">Computer Graphics Forum</title>
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<biblScope unit="volume">27</biblScope>
<biblScope unit="issue">2</biblScope>
<biblScope unit="pp">251-260</biblScope>
<date type="datePub">2008</date>
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<abstract xml:lang="en">We present an explicit method to compute a generalization of the Fourier Transform on a mesh. It is well known that the eigenfunctions of the Laplace Beltrami operator (Manifold Harmonics) define a function basis allowing for such a transform. However, computing even just a few eigenvectors is out of reach for meshes with more than a few thousand vertices, and storing these eigenvectors is prohibitive for large meshes. To overcome these limitations, we propose a band-by-band spectrum computation algorithm and an out-of-core implementation that can compute thousands of eigenvectors for meshes with up to a million vertices. We also propose a limited-memory filtering algorithm, that does not need to store the eigenvectors. Using this latter algorithm, specific frequency bands can be filtered, without needing to compute the entire spectrum. Finally, we demonstrate some applications of our method to interactive convolution geometry filtering. These technical achievements are supported by a solid yet simple theoretic framework based on Discrete Exterior Calculus (DEC). In particular, the issues of symmetry and discretization of the operator are considered with great care.</abstract>
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