Nonlinear discriminant principal component analysis for image classification and reconstruction

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dc.contributor.authorFILISBINO, T.
dc.contributor.authorGIRALDI, G.
dc.contributor.authorPlinio Thomaz Aquino Junior
dc.contributor.authorOrcidhttps://orcid.org/0000-0002-5100-7443
dc.date.accessioned2022-01-12T21:56:52Z
dc.date.available2022-01-12T21:56:52Z
dc.date.issued2018-12-13
dc.description.abstract© 2018 IEEE.In this paper we present a nonlinear version of the discriminant principal component analysis, named NDPCA, that is based on kernel support vector machines (KSVM) and the AdaBoost technique. Specifically, the problem of ranking principal components, computed from two-class databases, is addressed by applying the AdaBoost procedure in a nested loop: Each iteration of the inner loop boosts weak classifiers to a moderate one while the outer loop combines the moderate classifiers to build the global discriminant vector. In the proposed NDPCA, each weak learner is a linear classifier computed through a separating hyperplane defined by a KSVM decision boundary in the PCA space. We compare the proposed methodology with counterpart ones using facial expressions of the Radboud and Jaffe image databases. Our experimental results have shown that NDPCA outperforms the PCA in classification tasks. Also, it is competitive if compared with counterpart techniques given also suitable results for reconstruction.
dc.description.firstpage312
dc.description.lastpage317
dc.identifier.citationFILISBINO, T.; GIRALDI, G.; AQUINO JUNIOR, P. T. Nonlinear discriminant principal component analysis for image classification and reconstruction. Proceedings - 2018 Brazilian Conference on Intelligent Systems, BRACIS 2018, p. 312-317, dec. 2018.
dc.identifier.doi10.1109/BRACIS.2018.00061
dc.identifier.urihttps://repositorio.fei.edu.br/handle/FEI/3754
dc.relation.ispartofProceedings - 2018 Brazilian Conference on Intelligent Systems, BRACIS 2018
dc.rightsAcesso Restrito
dc.subject.otherlanguageAdaboost
dc.subject.otherlanguageDiscriminant Analysis
dc.subject.otherlanguageKSVM
dc.subject.otherlanguagePCA
dc.titleNonlinear discriminant principal component analysis for image classification and reconstruction
dc.typeArtigo de evento
fei.scopus.citations1
fei.scopus.eid2-s2.0-85060858273
fei.scopus.subjectClassification tasks
fei.scopus.subjectDiscriminant vectors
fei.scopus.subjectFacial Expressions
fei.scopus.subjectKSVM
fei.scopus.subjectLinear classifiers
fei.scopus.subjectNonlinear versions
fei.scopus.subjectPrincipal Components
fei.scopus.subjectSeparating hyperplane
fei.scopus.updated2024-07-01
fei.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85060858273&origin=inward
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