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dc.contributor.convenorMagdy Bayoumi
dc.contributor.authorKanan, Hamidreza Rashidy
dc.contributor.authorGao, Yongsheng
dc.contributor.editorLina Karam and Thrasos Pappas
dc.date.accessioned2017-05-03T14:13:04Z
dc.date.available2017-05-03T14:13:04Z
dc.date.issued2009
dc.date.modified2010-06-03T09:26:01Z
dc.identifier.isbn978-1-4244-5653-6
dc.identifier.issn1522-4880
dc.identifier.refurihttp://www.icip2009.org/
dc.identifier.doi10.1109/ICIP.2009.5413903
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.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.format.extent543201 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.language.isoeng
dc.publisherIEEE
dc.publisher.placeLos Alamitos, CA
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofconferencename16th IEEE International Conference on Image Processing
dc.relation.ispartofconferencetitle2009 16TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-6
dc.relation.ispartofdatefrom2009-11-07
dc.relation.ispartofdateto2009-11-10
dc.relation.ispartoflocationCairo, EGYPT
dc.relation.ispartofpagefrom3309
dc.relation.ispartofpageto+
dc.rights.retentionY
dc.subject.fieldofresearchComputer Vision
dc.subject.fieldofresearchPattern Recognition and Data Mining
dc.subject.fieldofresearchcode080104
dc.subject.fieldofresearchcode080109
dc.titleRecognition of Expression Variant Faces from One Sample Image per Enrolled Subject
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.rights.copyright© 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.
gro.date.issued2009
gro.hasfulltextFull Text
gro.griffith.authorGao, Yongsheng


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    Contains papers delivered by Griffith authors at national and international conferences.

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