Show simple item record

dc.contributor.authorHajati, Farshiden_US
dc.contributor.authorA. Raie, Abolghasemen_US
dc.contributor.authorGao, Yongshengen_US
dc.date.accessioned2017-05-03T15:01:11Z
dc.date.available2017-05-03T15:01:11Z
dc.date.issued2011en_US
dc.date.modified2013-05-30T04:42:56Z
dc.identifier.issn09168532en_US
dc.identifier.doi10.1587/transinf.E94.D.1488en_US
dc.identifier.urihttp://hdl.handle.net/10072/43286
dc.description.abstractFor the 3D face recognition numerous methods have been proposed, but little attention has been given to the local-based representation for the texture map of the 3D models. In this paper, we propose a novel 3D face recognition approach based on locally extracted Geodesic Pseudo Zernike Moment Array (GPZMA) of the texture map when only one exemplar per person is available. In the proposed method, the function of the PZM is controlled by the geodesic deformations to tackle the problem of face recognition under the expression and pose variations. The feasibility and effectiveness investigation for the proposed method is conducted through a wide range of experiments using publicly available BU-3DFE and Bosphorus databases including samples with different expression and pose variations. The performance of the proposed method is compared with the performance of three state-of-the-art benchmark approaches. The encouraging experimental results demonstrate that the proposed method achieves much higher accuracy than the benchmarks in single-model databases.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_US
dc.languageEnglishen_US
dc.language.isoen_US
dc.publisherThe Institute of Electronics, Information and Communication Engineersen_US
dc.publisher.placeJapanen_US
dc.relation.ispartofstudentpublicationYen_US
dc.relation.ispartofpagefrom1488en_US
dc.relation.ispartofpageto1496en_US
dc.relation.ispartofissue7en_US
dc.relation.ispartofjournalIEICE Transactions on Information and Systemsen_US
dc.relation.ispartofvolumeE94-Den_US
dc.rights.retentionYen_US
dc.subject.fieldofresearchComputer Visionen_US
dc.subject.fieldofresearchPattern Recognition and Data Miningen_US
dc.subject.fieldofresearchcode080104en_US
dc.subject.fieldofresearchcode080109en_US
dc.title3D Face Recognition using Geodesic PZM Array from a Single Model per Personen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Peer Reviewed (HERDC)en_US
dc.type.codeC - Journal Articlesen_US
gro.rights.copyrightSelf-archiving of the author-manuscript version is not yet supported by this journal. Please refer to the journal link for access to the definitive, published version or contact the authors for more information.en_US
gro.date.issued2011
gro.hasfulltextNo Full Text


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

  • Journal articles
    Contains articles published by Griffith authors in scholarly journals.

Show simple item record