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hal.structure.identifierTechnische Universität Munchen - Technical University Munich - Université Technique de Munich [TUM]
dc.contributor.authorQUÉAU, Yvain
hal.structure.identifierReal Expression Artificial Life [IRIT-REVA]
dc.contributor.authorDUROU, Jean-Denis
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
hal.structure.identifierInstitut universitaire de France [IUF]
dc.contributor.authorAUJOL, Jean-François
dc.date.accessioned2024-04-04T03:01:12Z
dc.date.available2024-04-04T03:01:12Z
dc.date.issued2018-05
dc.identifier.issn0924-9907
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/192879
dc.description.abstractEnThe need for an efficient method of integration of a dense normal field is inspired by several computer vision tasks, such as shape-from-shading, photometric stereo, deflectometry. Inspired by edge-preserving methods from image processing, we study in this paper several variational approaches for normal integration, with a focus on non-rectangular domains, free boundary and depth discontinuities. We first introduce a new discretization for quadratic integration, which is designed to ensure both fast recovery and the ability to handle non-rectangular domains with a free boundary. Yet, with this solver, discontinuous surfaces can be handled only if the scene is first segmented into pieces without discontinuity. Hence, we then discuss several discontinuity-preserving strategies. Those inspired, respectively, by the Mumford-Shah segmentation method and by anisotropic diffusion, are shown to be the most effective for recovering discontinuities.
dc.language.isoen
dc.publisherSpringer Verlag
dc.subject.enintegration
dc.subject.en3D-reconstruction
dc.subject.ennormal field
dc.subject.engradient field
dc.subject.envariational methods
dc.subject.enphotometric stereo
dc.subject.enshape-from-shading
dc.title.enVariational Methods for Normal Integration
dc.typeArticle de revue
dc.identifier.doi10.1007/s10851-017-0777-6
dc.subject.halInformatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
bordeaux.journalJournal of Mathematical Imaging and Vision
bordeaux.page609-632
bordeaux.volume60
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.issue4
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-02118476
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02118476v1
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