Classification with Emotional Faces via a Robust Sparse Classifier

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dc.authoridBattini Sonmez, Elena/0000-0003-0090-984X|Varlı, Songül/0000-0002-1786-6869
dc.authorwosidAlbayrak, Songül/G-5329-2011
dc.authorwosidBattini Sonmez, Elena/AAZ-6358-2021
dc.authorwosidVarlı, Songül/AAZ-4672-2020
dc.contributor.authorSonmez, Elena Battini
dc.contributor.authorSankur, Bulent
dc.contributor.authorAlbayrak, Songul
dc.date.accessioned2024-07-18T20:51:02Z
dc.date.available2024-07-18T20:51:02Z
dc.date.issued2012
dc.departmentİstanbul Bilgi Üniversitesien_US
dc.description3rd International Conference on Image Processing Theory, Tools and Applications (IPTA) -- OCT 15-18, 2012 -- Istanbul, TURKEYen_US
dc.description.abstractWe consider the problem of emotion recognition in faces as well as subject identification in the presence of emotional facial expressions. We propose alternative solutions for this identification and recognition problems using the idea of sparsity, in terms of Sparse Representation based Classifier (SRC) paradigm. In both cases, the problem is formulated as finding the most parsimonious set of representatives from a training set, which will best reconstruct the test image. For emotion classification, we considered the six fundamental states and the SRC performance was compared with that of the Active Appearance Model (AAM) algorithm [1]. For face recognition displaying various emotions, in order to test the robustness of SRC, we considered gallery faces of subjects having one or more expression variety while the probe faces had a different expression. We experimented with both the whole faces or faces observed with multiple blocks. The SRC algorithm, while not demanding any training, performed surprisingly well in both emotion identification across subjects and subject identification across emotions.en_US
dc.description.sponsorshipIEEE,Univ Evry Val Essonne (UEVE),Istanbul Aydin Universitesi (IAU),Univ Evry Val Essonne, Inst Technologie (IUT),Informat Biol Integrat & Complex Syst Lab (IBISC),Montpellier Lab Informat Robot & Microelectron (LIRMM),Multidisciplinary Inst Res Syst Engn Mech & Energet (PRISME),Natl Centre Sci Res (CNRS),European Assoc Signal Processing (EURASIP),IEEE France Secten_US
dc.identifier.endpage349en_US
dc.identifier.isbn978-1-4673-2585-1
dc.identifier.isbn978-1-4673-2583-7
dc.identifier.issn2154-512X
dc.identifier.scopus2-s2.0-84875854340en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage344en_US
dc.identifier.urihttps://hdl.handle.net/11411/8367
dc.identifier.wosWOS:000317076900059en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2012 3rd International Conference on Image Processing Theory, Tools and Applicationsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectClassificationen_US
dc.subjectEmotionen_US
dc.subjectSparsityen_US
dc.titleClassification with Emotional Faces via a Robust Sparse Classifieren_US
dc.typeConference Objecten_US

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