dc.contributorUniversidade Estadual Paulista (UNESP)
dc.creatorAfonso, Luis Cláudio Súgi
dc.creatorPapa, João Paulo
dc.creatorPapa, Luciene Patrici
dc.creatorMarana, Aparecido Nilceu
dc.creatorRocha, Anderson
dc.creator
dc.date2015-03-18T15:56:37Z
dc.date2016-10-25T20:35:51Z
dc.date2015-03-18T15:56:37Z
dc.date2016-10-25T20:35:51Z
dc.date2012-01-01
dc.date.accessioned2017-04-06T07:19:53Z
dc.date.available2017-04-06T07:19:53Z
dc.identifier2012 Ieee International Conference On Image Processing (icip 2012). New York: Ieee, p. 1897-1900, 2012.
dc.identifier1522-4880
dc.identifierhttp://hdl.handle.net/11449/117646
dc.identifierhttp://acervodigital.unesp.br/handle/11449/117646
dc.identifierWOS:000319334901236
dc.identifierhttp://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6467255
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/928293
dc.descriptionImage 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.
dc.languageeng
dc.publisherIeee
dc.relation2012 Ieee International Conference On Image Processing (icip 2012)
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectOptimum-Path Forest
dc.subjectClustering algorithms
dc.subjectBag-of-visual Words
dc.subjectAutomatic Visual Word Dictionary Calculation
dc.titleAutomatic visual dictionary generation through optimum-path forest clusteringautomatic visual dictionary generation through optimum-path forest clustering
dc.typeOtro


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