Using contextual spaces for image re-ranking and rank aggregation

dc.creatorPedronette, DCG
dc.creatorTorres, RD
dc.creatorCalumby, RT
dc.date2014
dc.dateAPR
dc.date2014-07-30T19:07:32Z
dc.date2015-11-26T17:50:48Z
dc.date2014-07-30T19:07:32Z
dc.date2015-11-26T17:50:48Z
dc.date.accessioned2018-03-29T00:34:06Z
dc.date.available2018-03-29T00:34:06Z
dc.identifierMultimedia Tools And Applications. Springer, v. 69, n. 3, n. 689, n. 716, 2014.
dc.identifier1380-7501
dc.identifier1573-7721
dc.identifierWOS:000333209300007
dc.identifier10.1007/s11042-012-1115-z
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/73060
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/73060
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1289792
dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionThis article presents two novel re-ranking approaches that take into account contextual information defined by the K-Nearest Neighbours (KNN) of a query image for improving the effectiveness of CBIR systems. The main contributions of this article are the definition of the concept of contextual spaces for encoding contextual information of images; the definition of two new re-ranking algorithms that exploit contextual information encoded in contextual spaces; and the evaluation of the proposed algorithms in several CBIR tasks related to the combination of image descriptors; combination of visual and textual descriptors; and combination of post-processing (re-ranking) methods. We conducted a large evaluation protocol involving visual descriptors (considering shape, color, and texture) and textual descriptors, various datasets, and comparisons with other post-processing methods. Experimental results demonstrate the effectiveness of our approaches.
dc.description69
dc.description3
dc.description689
dc.description716
dc.descriptionAMD
dc.descriptionFAEPEX [2007/-52015-0, 2009/-18438-7]
dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionDGA/-UNICAMP
dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionFAEPEX [2007/-52015-0, 2009/-18438-7]
dc.languageen
dc.publisherSpringer
dc.publisherDordrecht
dc.publisherHolanda
dc.relationMultimedia Tools And Applications
dc.relationMultimed. Tools Appl.
dc.rightsfechado
dc.rightshttp://www.springer.com/open+access/authors+rights?SGWID=0-176704-12-683201-0
dc.sourceWeb of Science
dc.subjectContent-based image retrieval
dc.subjectRe-ranking
dc.subjectRank aggregation
dc.subjectContextual information
dc.subjectMultimodal retrieval
dc.subjectShape Retrieval
dc.subjectClassification
dc.subjectTransduction
dc.subjectCorrelograms
dc.subjectRecognition
dc.subjectInformation
dc.subjectSimilarity
dc.subjectDescriptor
dc.subjectDistance
dc.titleUsing contextual spaces for image re-ranking and rank aggregation
dc.typeArtículos de revistas


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