Image Classification Based On Bag Of Visual Graphs

dc.creatorSilva F.B.
dc.creatorGoldenstein S.
dc.creatorTabbone S.
dc.creatorDa S. Torres R.
dc.date2013
dc.date2015-06-25T19:14:11Z
dc.date2015-11-26T15:11:59Z
dc.date2015-06-25T19:14:11Z
dc.date2015-11-26T15:11:59Z
dc.date.accessioned2018-03-28T22:22:06Z
dc.date.available2018-03-28T22:22:06Z
dc.identifier9781479923410
dc.identifier2013 Ieee International Conference On Image Processing, Icip 2013 - Proceedings. , v. , n. , p. 4312 - 4316, 2013.
dc.identifier
dc.identifier10.1109/ICIP.2013.6738888
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-84897792022&partnerID=40&md5=8782109f53de07b5d0cc82d05c3ac66a
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/89035
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/89035
dc.identifier2-s2.0-84897792022
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1258279
dc.descriptionThis paper proposes the Bag of Visual Graphs (BoVG), a new approach to encode the spatial relationships of visual words through a codebook of visual-word arrangements, represented by graphs. This graph-based codebook defines a descriptor for image representations that not only considers the frequency of occurrence of visual words, but also their spatial relationships. Experiments demonstrate that BoVG yields high-accuracy scores in classification tasks on the traditional Caltech-101 and Caltech-256 datasets. © 2013 IEEE.
dc.description
dc.description
dc.description4312
dc.description4316
dc.descriptionThe Institute of Electrical and Electronics Engineers (IEEE) Signal Processing Society
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dc.languageen
dc.publisher
dc.relation2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings
dc.rightsfechado
dc.sourceScopus
dc.titleImage Classification Based On Bag Of Visual Graphs
dc.typeActas de congresos


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