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Growing Least Squares for the Analysis of Manifolds in Scale-Space

hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
hal.structure.identifierMelting the frontiers between Light, Shape and Matter [MANAO]
dc.contributor.authorMELLADO, Nicolas
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
hal.structure.identifierMelting the frontiers between Light, Shape and Matter [MANAO]
hal.structure.identifierLaboratoire Photonique, Numérique et Nanosciences [LP2N]
dc.contributor.authorGUENNEBAUD, Gaël
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
hal.structure.identifierMelting the frontiers between Light, Shape and Matter [MANAO]
hal.structure.identifierLaboratoire Photonique, Numérique et Nanosciences [LP2N]
dc.contributor.authorBARLA, Pascal
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
hal.structure.identifierMelting the frontiers between Light, Shape and Matter [MANAO]
dc.contributor.authorREUTER, Patrick
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
hal.structure.identifierMelting the frontiers between Light, Shape and Matter [MANAO]
dc.contributor.authorSCHLICK, Christophe
dc.date.accessioned2023-05-12T11:01:28Z
dc.date.available2023-05-12T11:01:28Z
dc.date.issued2012-07-18
dc.identifier.issn0167-7055
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/182046
dc.description.abstractEnWe present a novel approach to the multi-scale analysis of point-sampled manifolds of co-dimension 1. It is based on a variant of Moving Least Squares, whereby the evolution of a geometric descriptor at increasing scales is used to locate pertinent locations in scale-space, hence the name "Growing Least Squares". Compared to existing scale-space analysis methods, our approach is the first to provide a continuous solution in space and scale dimensions, without requiring any parametrization, connectivity or uniform sampling. An important implication is that we identify multiple pertinent scales for any point on a manifold, a property that had not yet been demonstrated in the literature. In practice, our approach exhibits an improved robustness to change of input, and is easily implemented in a parallel fashion on the GPU. We compare our method to state-of-the-art scale-space analysis techniques and illustrate its practical relevance in a few application scenarios.
dc.description.sponsorshipSemi-automatique 3D Acquisition et Réassemblage du Patrimoine - ANR-09-CORD-0019
dc.language.isoen
dc.publisherWiley
dc.title.enGrowing Least Squares for the Analysis of Manifolds in Scale-Space
dc.typeArticle de revue
dc.identifier.doi10.1111/j.1467-8659.2012.03174.x
dc.subject.halInformatique [cs]/Géométrie algorithmique [cs.CG]
dc.subject.halInformatique [cs]/Multimédia [cs.MM]
dc.description.sponsorshipEuropeVirtual Museum Transnational Network
bordeaux.journalComputer Graphics Forum
bordeaux.page1691-1701
bordeaux.volume31
bordeaux.hal.laboratoriesLaboratoire Photonique, Numérique et Nanosciences (LP2N) - UMR 5298*
bordeaux.issue5
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-00713678
hal.version1
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-00713678v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Computer%20Graphics%20Forum&rft.date=2012-07-18&rft.volume=31&rft.issue=5&rft.spage=1691-1701&rft.epage=1691-1701&rft.eissn=0167-7055&rft.issn=0167-7055&rft.au=MELLADO,%20Nicolas&GUENNEBAUD,%20Ga%C3%ABl&BARLA,%20Pascal&REUTER,%20Patrick&SCHLICK,%20Christophe&rft.genre=article


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