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dc.contributor.authorAlmeida, João Dallyson Sousa de-
dc.contributor.authorSilva, Aristófanes Corrêa-
dc.contributor.authorPaiva, Anselmo Cardoso-
dc.date.accessioned2010-10-14T14:01:14Z-
dc.date.available2010-10-14T14:01:14Z-
dc.date.issued2010-
dc.identifier.citationAlmeida, João Dallyson Sousa de ; Silva, Aristófanes Corrêa; Paiva, Anselmo Cardoso. Automatic Eye Detection Using Semivariogram Function and Support Vector Machine. In: 17th International Conference on Systems, Signals and Image Processing (IWSSIP 2010), 2010, Rio de Janeiro. 17th International Conference on Systems, Signals and Image Processing. Niterói : EdUFF - Editora da Universidade Federal Fluminense, 2010. p. 174-177.pt_BR
dc.identifier.urihttp://gurupi.ufma.br:8080/jspui/1/305-
dc.descriptionTambém disponível em: http://www.ic.uff.br/iwssip2010/Proceedings/nav/papers/paper_56.pdfpt_BR
dc.description.abstractSeveral computational systems which depend on the precise location of the eyes have been developed in the last decades. Aware of this need, we propose a method for automatic detection of eyes in images of human faces using semivariogram functions and support vector machines. Patterns of eyes region and other areas of the face are represented through the semivariogram function to precisely distinguish the region of the eyes. The method was tested in the ORL human face database, which contains 400 images grouped in 40 persons, each having 10 different expressions. The detection obtained results of sensitivity of 84.6%, specificity of 93.4% and accuracy of 88.45%.pt_BR
dc.language.isoen_USpt_BR
dc.subjectAutomatic eye detectionpt_BR
dc.subjectsemivariogram functionpt_BR
dc.subjectsupport vector machine (SVM)pt_BR
dc.titleAutomatic Eye Detection Using Semivariogram Function and Support Vector Machinept_BR
dc.typeapresentaçãopt_BR
Aparece nas coleções:Mestrado em Engenharia de Eletricidade/Trabalhos Apresentados em Eventos Cientificos

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