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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/129416
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dc.contributor.authorPereira, Danillo R.-
dc.contributor.authorDelpiano, José-
dc.contributor.authorPapa, João P.-
dc.date.accessioned2015-10-21T21:03:08Z-
dc.date.accessioned2016-10-25T21:09:08Z-
dc.date.available2015-10-21T21:03:08Z-
dc.date.available2016-10-25T21:09:08Z-
dc.date.issued2015-05-09-
dc.identifierhttp://jivp.eurasipjournals.com/content/2015/1/11-
dc.identifier.citationEurasip Journal On Image And Video Processing. Cham: Springer International Publishing Ag, v. 2015, n. 11, p. 1-10, 2015.-
dc.identifier.issn1687-5281-
dc.identifier.urihttp://hdl.handle.net/11449/129416-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/129416-
dc.description.abstractOptical flow methods are accurate algorithms for estimating the displacement and velocity fields of objects in a wide variety of applications, being their performance dependent on the configuration of a set of parameters. Since there is a lack of research that aims to automatically tune such parameters, in this work, we have proposed an optimization-based framework for such task based on social-spider optimization, harmony search, particle swarm optimization, and Nelder-Mead algorithm. The proposed framework employed the well-known large displacement optical flow (LDOF) approach as a basis algorithm over the Middlebury and Sintel public datasets, with promising results considering the baseline proposed by the authors of LDOF.en
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
dc.description.sponsorshipUniversidad de los Andes FAI-
dc.format.extent1-10-
dc.language.isoeng-
dc.publisherSpringer-
dc.sourceWeb of Science-
dc.subjectOptimization methodsen
dc.subjectEvolutionary algorithmsen
dc.subjectOptical flow methodsen
dc.titleOn the optical flow model selection through metaheuristicsen
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionUniversidade dos Andes-
dc.description.affiliationUniversity of the Andes, Mons. Álvaro del Portillo, Santiago 12445, Chile-
dc.description.affiliationUnespSão Paulo State University, Av. Eng. Luiz Edmundo Carrijo Coube, Departamento de Computação, 14-01, Bauru 17033-360, SP, Brazil-
dc.description.sponsorshipIdFAPESP: 2013/20387-7-
dc.description.sponsorshipIdFAPESP: 2014/16250-9-
dc.description.sponsorshipIdCNPq: 303182/2011-3-
dc.description.sponsorshipIdCNPq: 470571/2013-6-
dc.description.sponsorshipIdCNPq: 306166/2014-3-
dc.description.sponsorshipIdUniversidad de los Andes FAI: 05/2013-
dc.identifier.doihttp://dx.doi.org/10.1186/s13640-015-0066-5-
dc.identifier.wosWOS:000354709700001-
dc.rights.accessRightsAcesso aberto-
dc.identifier.fileWOS000354709700001.pdf-
dc.relation.ispartofEurasip Journal On Image And Video Processing-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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