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dc.contributor.authorRustamov, Raif M.en_US
dc.contributor.editorAlexander Belyaev and Michael Garlanden_US
dc.date.accessioned2014-01-29T09:43:15Z
dc.date.available2014-01-29T09:43:15Z
dc.date.issued2007en_US
dc.identifier.isbn978-3-905673-46-3en_US
dc.identifier.issn1727-8384en_US
dc.identifier.urihttp://dx.doi.org/10.2312/SGP/SGP07/225-233en_US
dc.description.abstractA deformation invariant representation of surfaces, the GPS embedding, is introduced using the eigenvalues and eigenfunctions of the Laplace-Beltrami differential operator. Notably, since the definition of the GPS embedding completely avoids the use of geodesic distances, and is based on objects of global character, the obtained representation is robust to local topology changes. The GPS embedding captures enough information to handle various shape processing tasks as shape classification, segmentation, and correspondence. To demonstrate the practical relevance of the GPS embedding, we introduce a deformation invariant shape descriptor called G2-distributions, and demonstrate their discriminative power, invariance under natural deformations, and robustness.en_US
dc.publisherThe Eurographics Associationen_US
dc.titleLaplace-Beltrami Eigenfunctions for Deformation Invariant Shape Representationen_US
dc.description.seriesinformationGeometry Processingen_US


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