Show simple item record

dc.contributor.authorZhao, Sanqiangen_US
dc.contributor.authorGao, Yongshengen_US
dc.contributor.editorGang Qian (ed)en_US
dc.date.accessioned2017-05-03T14:13:02Z
dc.date.available2017-05-03T14:13:02Z
dc.date.issued2008en_US
dc.date.modified2009-04-27T06:48:33Z
dc.identifier.refurihttp://www.icip08.org/default.aspen_AU
dc.identifier.doi10.1109/ICIP.2008.4712092en_AU
dc.identifier.urihttp://hdl.handle.net/10072/22703
dc.description.abstractGabor wavelet related feature extraction and classification is an important topic in image analysis and pattern recognition. Gabor features can be used either holistically or analytically. While holistic approaches involve significant computational complexity, existing analytic approaches require explicit correspondence of predefined feature points for classification. Different from these approaches, this paper presents a new analytic Gabor method for face recognition. The proposed method attaches Gabor features on a set of shape-driven sparse points to describe both geometric and textural information. Neither the number nor the correspondence of these points is needed. A variant of Hausdorff distance is employed to recognize faces. The experiments performed on AR database demonstrated that the proposed algorithm is effective to identify individuals in various circumstances, such as under expression and illumination changes.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_AU
dc.format.extent267046 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglishen_US
dc.language.isoen_AU
dc.publisherIEEEen_US
dc.publisher.placeUSAen_US
dc.relation.ispartofstudentpublicationYen_AU
dc.relation.ispartofconferencenameThe IEEE International Conference on Image Processing (ICIP) 2008en_US
dc.relation.ispartofconferencetitleThe IEEE International Conference on Image Processing (ICIP)en_US
dc.relation.ispartofdatefrom2008-10-12en_US
dc.relation.ispartofdateto2008-10-15en_US
dc.relation.ispartoflocationSan Diego, California, U.S.Aen_US
dc.rights.retentionYen_AU
dc.subject.fieldofresearchcode280207en_US
dc.subject.fieldofresearchcode280208en_US
dc.titleSignificant Jet Point for Facial Image Representation and Recognitionen_US
dc.typeConference outputen_US
dc.type.descriptionE1 - Conference Publications (HERDC)en_US
dc.type.codeE - Conference Publicationsen_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


Files in this item

This item appears in the following Collection(s)

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

Show simple item record