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dc.contributor.authorZhang, Paulen_US
dc.contributor.authorGao, Yongshengen_US
dc.contributor.authorK. H. Leung, Mayloren_US
dc.contributor.editorPierre Moulin (Editor-in-Chief)en_US
dc.date.accessioned2017-04-24T11:52:53Z
dc.date.available2017-04-24T11:52:53Z
dc.date.issued2008en_US
dc.date.modified2009-05-12T06:39:02Z
dc.identifier.issn15566013en_US
dc.identifier.doi10.1109/TIFS.2008.2004286en_AU
dc.identifier.urihttp://hdl.handle.net/10072/22882
dc.description.abstractMug shot photography has been used to identify criminals by the police for more than a century. However, the common scenario of face recognition using frontal and side-view mug shots as gallery remains largely uninvestigated in computerized face recognition across pose. This paper presents a novel appearance-based approach using frontal and sideface images to handle pose variations in face recognition, which has great potential in forensic and security applications involving police mugshot databases. Virtual views in different poses are generated in two steps: 1) shape modelling and 2) texture synthesis. In the shape modelling step, a multilevel variation minimization approach is applied to generate personalized 3-D face shapes. In the texture synthesis step, face surface properties are analyzed and virtual views in arbitrary viewing conditions are rendered, taking diffuse and specular reflections into account. Appearance-based face recognition is performed with the augmentation of synthesized virtual views covering possible viewing angles to recognize probe views in arbitrary conditions. The encouraging experimental results demonstrated that the proposed approach by using frontal and side-view images is a feasible and effective solution to recognizing rotated faces, which can lead to a better and practical use of existing forensic databases in computerized human face-recognition applications.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_AU
dc.format.extent3676092 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglishen_US
dc.language.isoen_AU
dc.publisherIEEEen_US
dc.publisher.placeUnited Statesen_US
dc.publisher.urihttp://ieeexplore.ieee.org/servlet/opac?punumber=10206en_AU
dc.relation.ispartofstudentpublicationYen_AU
dc.relation.ispartofpagefrom684en_US
dc.relation.ispartofpageto697en_US
dc.relation.ispartofissue4en_US
dc.relation.ispartofjournalIEEE Transactions on Information Forensics and Securityen_US
dc.relation.ispartofvolume3en_US
dc.rights.retentionYen_AU
dc.subject.fieldofresearchcode280207en_US
dc.subject.fieldofresearchcode280203en_US
dc.subject.fieldofresearchcode280208en_US
dc.titleRecognizing Rotated Faces From Frontal and Side Views: An Approach Toward Effective Use of Mugshot Databasesen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Peer Reviewed (HERDC)en_US
dc.type.codeC - Journal Articlesen_US
gro.facultyGriffith Sciences, Griffith School of Engineeringen_US
gro.rights.copyrightCopyright 2008 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.issued2008
gro.hasfulltextFull Text


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