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dc.contributor.authorGao, Yongshengen_US
dc.contributor.authorQi, Yutaoen_US
dc.contributor.editorDr.Robert S Ledleyen_US
dc.date.accessioned2017-05-03T14:13:10Z
dc.date.available2017-05-03T14:13:10Z
dc.date.issued2005en_US
dc.identifier.issn00313203en_US
dc.identifier.doi10.1016/j.patcog.2004.12.006en_US
dc.identifier.urihttp://hdl.handle.net/10072/4293
dc.description.abstractIn this paper, we introduce a novel visual similarity measuring technique to retrieve face images in photo album databases for law enforcement. Though much work is being done on face similarity matching techniques, little attention is given to the design of face matching schemes suitable for visual retrieval in single model databases where accuracy, robustness to scale and environmental changes, and computational efficiency are three important issues to be considered. This paper presents a robust face retrieval approach using structural and spatial point correspondence in which the directional corner points (DCPs) are generated for efficient face coding and retrieval. A complete investigation on the proposed method is conducted, which covers face retrieval under controlled/ideal condition, scale variations, environmental changes and subject actions. The system performance is compared with the performance of the eigenface method. It is an attractive finding that the proposed DCP retrieval technique has performed superior to the eigenface method in most of the comparison experiments. This research demonstrates that the proposed DCP approach provides a new way, which is both robust to scale and environmental changes, and efficient in computation, for retrieving human faces in single model databases.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_US
dc.languageEnglishen_US
dc.language.isoen_US
dc.publisherElsevier / Pergamonen_US
dc.publisher.placeUKen_US
dc.relation.ispartofstudentpublicationNen_US
dc.relation.ispartofpagefrom1009en_US
dc.relation.ispartofpageto1020en_US
dc.relation.ispartofjournalPattern Recognitionen_US
dc.relation.ispartofvolume38en_US
dc.rights.retentionYen_US
dc.subject.fieldofresearchcode280207en_US
dc.titleRobust Visual Similarity Retrieval in Single Model Face 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.date.issued2015-05-06T21:37:12Z
gro.hasfulltextNo Full Text


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