Infrared face recogniton by optimum-path forest

dc.contributorUniversidade Estadual Paulista (Unesp)
dc.contributorUniversidade Estadual de Campinas (UNICAMP)
dc.date.accessioned2014-05-27T11:24:03Z
dc.date.available2014-05-27T11:24:03Z
dc.date.created2014-05-27T11:24:03Z
dc.date.issued2009-12-01
dc.identifier2009 16th International Conference on Systems, Signals and Image Processing, IWSSIP 2009.
dc.identifierhttp://hdl.handle.net/11449/71296
dc.identifier10.1109/IWSSIP.2009.5367752
dc.identifier2-s2.0-77949520083
dc.identifier6027713750942689
dc.identifier9039182932747194
dc.description.abstractThis paper presents a novel, fast and accurate appearance-based method for infrared face recognition. By introducing the Optimum-Path Forest classifier, our objective is to get good recognition rates and effectively reduce the computational effort. The feature extraction procedure is carried out by PCA, and the results are compared to two other well known supervised learning classifiers; Artificial Neural Networks and Support Vector Machines. The achieved performance asserts the promise of the proposed framework. ©2009 IEEE.
dc.languageeng
dc.relation2009 16th International Conference on Systems, Signals and Image Processing, IWSSIP 2009
dc.rightsAcesso aberto
dc.sourceScopus
dc.subjectFace recognition
dc.subjectMLP
dc.subjectOPF
dc.subjectPCA
dc.subjectSVM
dc.subjectThermal infrared
dc.subjectAppearance-based methods
dc.subjectArtificial Neural Network
dc.subjectComputational effort
dc.subjectForest classifiers
dc.subjectInfrared face recognition
dc.subjectRecognition rates
dc.subjectAcoustic generators
dc.subjectClassifiers
dc.subjectFeature extraction
dc.subjectImaging systems
dc.subjectNeural networks
dc.subjectSupport vector machines
dc.titleInfrared face recogniton by optimum-path forest
dc.typeActas de congresos


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