A scalable re-ranking method for content-based image retrieval

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dc.contributor.authorGuimaraes Pedronette, Daniel Carlos [UNESP]
dc.contributor.authorAlmeida, Jurandy
dc.contributor.authorTorres, Ricardo da S.
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionUniversidade Estadual de Campinas (UNICAMP)
dc.date.accessioned2014-12-03T13:11:26Z
dc.date.available2014-12-03T13:11:26Z
dc.date.issued2014-05-01
dc.description.abstractContent-based Image Retrieval (CBIR) systems consider only a pairwise analysis, i.e., they measure the similarity between pairs of images, ignoring the rich information encoded in the relations among several images. However, the user perception usually considers the query specification and responses in a given context. In this scenario, re-ranking methods have been proposed to exploit the contextual information and, hence, improve the effectiveness of CBIR systems. Besides the effectiveness, the usefulness of those systems in real-world applications also depends on the efficiency and scalability of the retrieval process, imposing a great challenge to the re-ranking approaches, once they usually require the computation of distances among all the images of a given collection. In this paper, we present a novel approach for the re-ranking problem. It relies on the similarity of top-k lists produced by efficient indexing structures, instead of using distance information from the entire collection. Extensive experiments were conducted on a large image collection, using several indexing structures. Results from a rigorous experimental protocol show that the proposed method can obtain significant effectiveness gains (up to 12.19% better) and, at the same time, improve considerably the efficiency (up to 73.11% faster). In addition, our technique scales up very well, which makes it suitable for large collections. (C) 2014 Elsevier Inc. All rights reserved.en
dc.description.affiliationUniv Estadual Paulista UNESP, Dept Stat Appl Math & Comp, BR-13506900 Rio Claro, SP, Brazil
dc.description.affiliationFed Univ Sao Paulo UNIFESP, Inst Sci & Technol, BR-12231280 Sao Jose Dos Campos, SP, Brazil
dc.description.affiliationUniv Campinas UNICAMP, RECOD Lab, IC, BR-13083852 Campinas, SP, Brazil
dc.description.affiliationUnespUniv Estadual Paulista UNESP, Dept Stat Appl Math & Comp, BR-13506900 Rio Claro, SP, Brazil
dc.description.sponsorshipAMD
dc.description.sponsorshipMicrosoft Research
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.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipIdFAPESP: 07/52015-0
dc.description.sponsorshipIdFAPESP: 09/05951-8
dc.description.sponsorshipIdFAPESP: 09/18438-7
dc.description.sponsorshipIdFAPESP: 11/11171-5
dc.description.sponsorshipIdFAPESP: 13/08645-0
dc.description.sponsorshipIdCNPq: 306580/2012-8
dc.description.sponsorshipIdCNPq: 484254/2012-0
dc.format.extent91-104
dc.identifierhttp://dx.doi.org/10.1016/j.ins.2013.12.030
dc.identifier.citationInformation Sciences. New York: Elsevier Science Inc, v. 265, p. 91-104, 2014.
dc.identifier.doi10.1016/j.ins.2013.12.030
dc.identifier.issn0020-0255
dc.identifier.urihttp://hdl.handle.net/11449/113143
dc.identifier.wosWOS:000333502600007
dc.language.isoeng
dc.publisherElsevier B.V.
dc.relation.ispartofInformation Sciences
dc.relation.ispartofjcr4.305
dc.relation.ispartofsjr1,635
dc.rights.accessRightsAcesso restrito
dc.sourceWeb of Science
dc.subjectContent-based image retrievalen
dc.subjectRe-ranking methodsen
dc.subjectIndexing structuresen
dc.titleA scalable re-ranking method for content-based image retrievalen
dc.typeArtigo
dcterms.licensehttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dcterms.rightsHolderElsevier B.V.
unesp.campusUniversidade Estadual Paulista (Unesp), Instituto de Geociências e Ciências Exatas, Rio Claropt

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