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dc.contributor.convenorMagdy Bayoumien_AU
dc.contributor.authorKanan, Hamidreza Rashidyen_US
dc.contributor.authorGao, Yongshengen_US
dc.contributor.editorLina Karam and Thrasos Pappasen_US
dc.date.accessioned2017-04-24T11:28:15Z
dc.date.available2017-04-24T11:28:15Z
dc.date.issued2009en_US
dc.date.modified2010-06-03T09:26:01Z
dc.identifier.refurihttp://www.icip2009.org/en_AU
dc.identifier.doi10.1109/ICIP.2009.5413903en_AU
dc.identifier.urihttp://hdl.handle.net/10072/30007
dc.description.abstractDespite remarkable progress on face recognition, little attention has been given to robustly recognize expression variant faces from a single sample image per person. One way to deal with the recognition of faces under above conditions is by using local statistical approaches which appear to be more robust against variations in facial expression. In this paper, we propose a new weighted matching method based on our recent work of AWPPZMA to recognize expression variant faces when only one exemplar image per enrolled subject is available. The proposed weighting method gives more significance to those parts of the face with facial expression variations that change less compared to neutral face image and less significance to those parts that change more. In this contribution, we use the difference between local area in the input face and its corresponding local area in the neutral face image as a measure of observable structure changes. The encouraging experimental results demonstrate that the proposed method provides a new solution to the problem of robustly recognizing expression variant faces in single model databases.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_AU
dc.format.extent543201 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglishen_US
dc.language.isoen_AU
dc.publisherIEEEen_US
dc.publisher.placeLos Alamitos, CAen_US
dc.relation.ispartofstudentpublicationNen_AU
dc.relation.ispartofconferencename2009 IEEE International Conference on Image Processing (ICIP 2009)en_US
dc.relation.ispartofconferencetitleProceedings of the 2009 IEEE International Conference on Image Processing (ICIP 2009)en_US
dc.relation.ispartofdatefrom2009-11-07en_US
dc.relation.ispartofdateto2009-11-10en_US
dc.relation.ispartoflocationCairo, Egypten_US
dc.rights.retentionYen_AU
dc.subject.fieldofresearchComputer Visionen_US
dc.subject.fieldofresearchPattern Recognition and Data Miningen_US
dc.subject.fieldofresearchcode080104en_US
dc.subject.fieldofresearchcode080109en_US
dc.titleRecognition of Expression Variant Faces from One Sample Image per Enrolled Subjecten_US
dc.typeConference outputen_US
dc.type.descriptionE1 - Conference Publications (HERDC)en_US
dc.type.codeE - Conference Publicationsen_US
gro.rights.copyrightCopyright 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_AU
gro.date.issued2009
gro.hasfulltextFull Text


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