Localized Manifold Harmonics for Spectral Shape Analysis

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dc.contributor.authorMelzi, Simoneen_US
dc.contributor.authorRodolĂ , Emanueleen_US
dc.contributor.authorCastellani, Umbertoen_US
dc.contributor.authorBronstein, Michael M.en_US
dc.contributor.editorJakob Andreas Bærentzen and Klaus Hildebrandten_US
dc.date.accessioned2017-07-02T17:44:41Z
dc.date.available2017-07-02T17:44:41Z
dc.date.issued2017
dc.description.abstractThe use of Laplacian eigenfunctions is ubiquitous in a wide range of computer graphics and geometry processing applications. In particular, Laplacian eigenbases allow generalizing the classical Fourier analysis to manifolds. A key drawback of such bases is their inherently global nature, as the Laplacian eigenfunctions carry geometric and topological structure of the entire manifold. In this paper, we introduce a new framework for local spectral shape analysis. We show how to efficiently construct localized orthogonal bases by solving an optimization problem that in turn can be posed as the eigendecomposition of a new operator obtained by a modification of the standard Laplacian. We study the theoretical and computational aspects of the proposed framework and showcase our new construction on the classical problems of shape approximation and correspondence.en_US
dc.description.sectionheadersPosters
dc.description.seriesinformationSymposium on Geometry Processing 2017- Posters
dc.identifier.doi10.2312/sgp.20171203
dc.identifier.isbn978-3-03868-047-5
dc.identifier.issn1727-8384
dc.identifier.pages5-6
dc.identifier.urihttps://doi.org/10.2312/sgp.20171203
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/sgp20171203
dc.publisherThe Eurographics Associationen_US
dc.subjectComputing methodologies
dc.subject
dc.subject> Shape analysis
dc.titleLocalized Manifold Harmonics for Spectral Shape Analysisen_US
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