Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/11754
Campo DC Valoridioma
dc.contributor.authorAlvarez, Luisen_US
dc.contributor.authorWeickert, Joachimen_US
dc.contributor.authorSánchez, Javieren_US
dc.contributor.otherAlvarez, Luis-
dc.contributor.otherSanchez, Javier-
dc.date.accessioned2014-05-23T08:10:26Z
dc.date.accessioned2018-03-15T14:34:41Z-
dc.date.available2014-05-23T08:10:26Z
dc.date.available2018-03-15T14:34:41Z-
dc.date.issued2000en_US
dc.identifier.issn0920-5691en_US
dc.identifier.urihttp://hdl.handle.net/10553/11754-
dc.description.abstractIn this paper we show that a classic optical flow technique by Nagel and Enkelmann can be regarded as an early anisotropic diffusion method with a diffusion tensor. We introduce three improvements into the model formulation that avoid inconsistencies caused by centering the brightness term and the smoothness term in different images use a linear scale-space focusing strategy from coarse to fine scales for avoiding convergence to physically irrelevant local minima, and create an energy functional that is invariant under linear brightness changes.  Applying a gradient descent method to the resulting energy functional leads to a system of diffusion-reaction equations. We prove that this system has a unique solution under realistic assumptions on the initial data, and we present an efficient linear implicit numerical scheme in detail. Our method creates flow fields with 100% density over the entire image domain, it is robust under a large range of parameter variations, and it can recover displacement fields that are far beyond the typical one-pixel limits which are characteristic for many differential methods for determining optical flow. We show that it performs better than the classic optical flow methods with 100%  density that are evaluated by Barron et al. (1994). Our software is available from the Internet.en_US
dc.languageengen_US
dc.relation.ispartofInternational Journal of Computer Visionen_US
dc.rightsby-nc-ndes
dc.sourceInternational Journal of Computer Vision [ISSN 0920-5691], v. 39, p. 41-56en_US
dc.subject220990 Tratamiento digital. Imágenesen_US
dc.subject120601 Construcción de algoritmosen_US
dc.subject120602 Ecuaciones diferencialesen_US
dc.subject120326 Simulaciónen_US
dc.subject.otherImage sequencesen_US
dc.subject.otherOptical flowen_US
dc.subject.otherDiferential methodsen_US
dc.subject.otherAnisotropic difusionen_US
dc.subject.otherLinear scale- spaceen_US
dc.subject.otherRegularizationen_US
dc.subject.otherFinite diference methodsen_US
dc.subject.otherPerformance evaluationen_US
dc.titleReliable estimation of dense optical flow fields with large displacementsen_US
dc.typeinfo:eu-repo/semantics/Articleen_US
dc.typeArticleen_US
dc.identifier.doi10.1023/A:1008170101536
dc.identifier.scopus0034245682-
dc.identifier.isi000089241300003-
dcterms.isPartOfInternational Journal Of Computer Vision
dcterms.sourceInternational Journal Of Computer Vision[ISSN 0920-5691],v. 39 (1), p. 41-56
dc.contributor.authorscopusid55640159000-
dc.contributor.authorscopusid7004916957-
dc.contributor.authorscopusid22735426600-
dc.identifier.absysnet538085-
dc.identifier.crisid1413;-;2648
dc.description.lastpage56-
dc.description.firstpage41-
dc.relation.volume39-
dc.rights.accessrightsinfo:eu-repo/semantics/openAccesses
dc.type2Artículoen_US
dc.identifier.wosWOS:000089241300003-
dc.contributor.daisngid478566-
dc.contributor.daisngid100055-
dc.contributor.daisngid1335721-
dc.identifier.investigatorRIDA-9190-2009-
dc.identifier.investigatorRIDA-7009-2011-
dc.identifier.external1413;-;2648-
dc.identifier.external1413;-;2648-
dc.identifier.externalWOS:000089241300003-
dc.identifier.external1413;-;2648-
dc.identifier.externalWOS:000089241300003-
dc.utils.revisionen_US
dc.contributor.wosstandardWOS:Alvarez, L
dc.contributor.wosstandardWOS:Weickert, J
dc.contributor.wosstandardWOS:Sanchez, J
dc.date.coverdateAgosto 2000
dc.identifier.ulpgces
dc.description.jcr1,835
dc.description.jcrqQ1
dc.description.scieSCIE
item.fulltextCon texto completo-
item.grantfulltextopen-
crisitem.author.deptGIR Modelos Matemáticos-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.deptGIR IUCES: Centro de Tecnologías de la Imagen-
crisitem.author.deptIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.orcid0000-0002-6953-9587-
crisitem.author.orcid0000-0001-8514-4350-
crisitem.author.parentorgDepartamento de Informática y Sistemas-
crisitem.author.parentorgIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.fullNameÁlvarez León, Luis Miguel-
crisitem.author.fullNameSánchez Pérez, Javier-
Colección:Artículos
miniatura
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