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DC Field | Value | Language |
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dc.contributor.author | Pereira, Danillo R. | - |
dc.contributor.author | Delpiano, José | - |
dc.contributor.author | Papa, João P. | - |
dc.date.accessioned | 2015-10-21T21:03:08Z | - |
dc.date.accessioned | 2016-10-25T21:09:08Z | - |
dc.date.available | 2015-10-21T21:03:08Z | - |
dc.date.available | 2016-10-25T21:09:08Z | - |
dc.date.issued | 2015-05-09 | - |
dc.identifier | http://jivp.eurasipjournals.com/content/2015/1/11 | - |
dc.identifier.citation | Eurasip Journal On Image And Video Processing. Cham: Springer International Publishing Ag, v. 2015, n. 11, p. 1-10, 2015. | - |
dc.identifier.issn | 1687-5281 | - |
dc.identifier.uri | http://hdl.handle.net/11449/129416 | - |
dc.identifier.uri | http://acervodigital.unesp.br/handle/11449/129416 | - |
dc.description.abstract | Optical 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.sponsorship | Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) | - |
dc.description.sponsorship | Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) | - |
dc.description.sponsorship | Universidad de los Andes FAI | - |
dc.format.extent | 1-10 | - |
dc.language.iso | eng | - |
dc.publisher | Springer | - |
dc.source | Web of Science | - |
dc.subject | Optimization methods | en |
dc.subject | Evolutionary algorithms | en |
dc.subject | Optical flow methods | en |
dc.title | On the optical flow model selection through metaheuristics | en |
dc.type | outro | - |
dc.contributor.institution | Universidade Estadual Paulista (UNESP) | - |
dc.contributor.institution | Universidade dos Andes | - |
dc.description.affiliation | University of the Andes, Mons. Álvaro del Portillo, Santiago 12445, Chile | - |
dc.description.affiliationUnesp | São Paulo State University, Av. Eng. Luiz Edmundo Carrijo Coube, Departamento de Computação, 14-01, Bauru 17033-360, SP, Brazil | - |
dc.description.sponsorshipId | FAPESP: 2013/20387-7 | - |
dc.description.sponsorshipId | FAPESP: 2014/16250-9 | - |
dc.description.sponsorshipId | CNPq: 303182/2011-3 | - |
dc.description.sponsorshipId | CNPq: 470571/2013-6 | - |
dc.description.sponsorshipId | CNPq: 306166/2014-3 | - |
dc.description.sponsorshipId | Universidad de los Andes FAI: 05/2013 | - |
dc.identifier.doi | http://dx.doi.org/10.1186/s13640-015-0066-5 | - |
dc.identifier.wos | WOS:000354709700001 | - |
dc.rights.accessRights | Acesso aberto | - |
dc.identifier.file | WOS000354709700001.pdf | - |
dc.relation.ispartof | Eurasip Journal On Image And Video Processing | - |
Appears in Collections: | Artigos, TCCs, Teses e Dissertações da Unesp |
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