Using Local Features Based Face Experts in Multimodal Biometrics Identification Systems

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dc.contributor.authorToygar, Oensen
dc.contributor.authorErguen, Cem
dc.contributor.authorAltincay, Hakan
dc.date.accessioned2026-02-06T18:28:22Z
dc.date.issued2010
dc.departmentDoğu Akdeniz Üniversitesi
dc.description5th International Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control -- SEP 02-04, 2009 -- Famagusta, CYPRUS
dc.description.abstractUsing local features generally provides higher accuracies compared to a global feature vector in face identification. In this study, taking into account the fact that better multimodal systems generally include individually good experts, multimodal identification using speech and local feature based face experts is studied. Both spPCA and mPCA are considered for this purpose. Experiments on XM2VTS and BANCA databases have shown that the local features based face experts not only provide better individual accuracies but also boost the performance of the multimodal identification system.
dc.identifier.endpage151
dc.identifier.isbn978-1-4244-3429-9
dc.identifier.orcid0000-0001-7402-9058
dc.identifier.scopusqualityN/A
dc.identifier.startpage148
dc.identifier.urihttps://hdl.handle.net/11129/10882
dc.identifier.wosWOS:000287219100038
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.language.isoen
dc.publisherIEEE
dc.relation.ispartof2009 Fifth International Conference on Soft Computing, Computing With Words and Perceptions in System Analysis, Decision and Control
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20260204
dc.titleUsing Local Features Based Face Experts in Multimodal Biometrics Identification Systems
dc.typeConference Object

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