Automatic visual dictionary generation through Optimum-Path Forest clustering

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dc.contributor.authorAfonso, L. [UNESP]
dc.contributor.authorPapa, J. [UNESP]
dc.contributor.authorPapa, L. [UNESP]
dc.contributor.authorMarana, Aparecido Nilceu [UNESP]
dc.contributor.authorRocha, Anderson
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversidade Estadual de Campinas (UNICAMP)
dc.date.accessioned2014-05-27T11:27:17Z
dc.date.available2014-05-27T11:27:17Z
dc.date.issued2012-12-01
dc.description.abstractImage categorization by means of bag of visual words has received increasing attention by the image processing and vision communities in the last years. In these approaches, each image is represented by invariant points of interest which are mapped to a Hilbert Space representing a visual dictionary which aims at comprising the most discriminative features in a set of images. Notwithstanding, the main problem of such approaches is to find a compact and representative dictionary. Finding such representative dictionary automatically with no user intervention is an even more difficult task. In this paper, we propose a method to automatically find such dictionary by employing a recent developed graph-based clustering algorithm called Optimum-Path Forest, which does not make any assumption about the visual dictionary's size and is more efficient and effective than the state-of-the-art techniques used for dictionary generation. © 2012 IEEE.en
dc.description.affiliationUniversidade Estadual Paulista (UNESP) Department of Computing
dc.description.affiliationUniversity of Campinas Institute of Computing
dc.description.affiliationUnespUniversidade Estadual Paulista (UNESP) Department of Computing
dc.format.extent1897-1900
dc.identifierhttp://dx.doi.org/10.1109/ICIP.2012.6467255
dc.identifier.citationProceedings - International Conference on Image Processing, ICIP, p. 1897-1900.
dc.identifier.doi10.1109/ICIP.2012.6467255
dc.identifier.issn1522-4880
dc.identifier.lattes6027713750942689
dc.identifier.scopus2-s2.0-84875818163
dc.identifier.urihttp://hdl.handle.net/11449/73809
dc.language.isoeng
dc.relation.ispartofProceedings - International Conference on Image Processing, ICIP
dc.relation.ispartofsjr0,257
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectAutomatic Visual Word Dictionary Calculation
dc.subjectBag-of-visual Words
dc.subjectClustering algorithms
dc.subjectOptimum-Path Forest
dc.subjectDiscriminative features
dc.subjectGraph-based clustering
dc.subjectImage Categorization
dc.subjectInvariant points
dc.subjectOptimum-path forests
dc.subjectState-of-the-art techniques
dc.subjectUser intervention
dc.subjectVision communities
dc.subjectVisual dictionaries
dc.subjectVisual word
dc.subjectForestry
dc.subjectImage processing
dc.subjectAlgorithms
dc.subjectImage Analysis
dc.titleAutomatic visual dictionary generation through Optimum-Path Forest clusteringen
dc.typeTrabalho apresentado em evento
dcterms.licensehttp://www.ieee.org/publications_standards/publications/rights/rights_policies.html
unesp.author.lattes6027713750942689[4]
unesp.author.orcid0000-0003-4861-7061[4]
unesp.campusUniversidade Estadual Paulista (Unesp), Faculdade de Ciências, Baurupt
unesp.departmentComputação - FCpt

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Bauru - FC - Faculdade de Ciências