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dc.contributor.authorHajati, F
dc.contributor.authorLucas, C
dc.contributor.authorGao, Y
dc.contributor.editorJian Zhang, Chunhua Shen, Glenn Geers, Qiang Wu
dc.date.accessioned2017-05-03T12:55:50Z
dc.date.available2017-05-03T12:55:50Z
dc.date.issued2010
dc.date.modified2011-06-02T05:07:31Z
dc.identifier.isbn9780769542713
dc.identifier.refurihttp://dicta2010.conference.nicta.com.au/
dc.identifier.doi10.1109/DICTA.2010.116
dc.identifier.urihttp://hdl.handle.net/10072/39002
dc.description.abstractIn this paper, a new method for face localization in color images, which is based on co-evolutionary systems, is introduced. The proposed method uses a co-evolutionary system to locate the eyes in a face image. The used coevolutionary system involves two genetic algorithm models. The first GA model searches for a solution in the given environment, and the second GA model searches for useful genetic information in the first GA model. In the next step, by using the location of eyes in image the parameters of face's bounding ellipse (center, orientation, major and minor axis) are computed. To evaluate and compare the proposed method with other methods, high order Pseudo Zernike Moments (PZM) are utilized to produce feature vectors and a Radial Basis Function (RBF) neural network is used as the classifier. Simulation results indicate that the speed and accuracy of the new system using the proposed face localization method which uses a co-evolutionary approach is higher than the system proposed in [10]. Keywords-face localization; genetic algorithm; coevolutionary
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.format.extent605429 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.language.isoeng
dc.publisherIEEE
dc.publisher.placeUnited States
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofconferencename2010 Digital Image Computing: Techniques and Applications (DICTA 2010)
dc.relation.ispartofconferencetitleProceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010
dc.relation.ispartofdatefrom2010-12-01
dc.relation.ispartofdateto2010-12-03
dc.relation.ispartoflocationSydney, Australia
dc.relation.ispartofpagefrom522
dc.relation.ispartofpageto527
dc.rights.retentionY
dc.subject.fieldofresearchcode280208
dc.subject.fieldofresearchcode280207
dc.titleFace Localization using an Effective Co-Evolutionary Genetic Algorithm
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.facultyGriffith Sciences, Griffith School of Engineering
gro.rights.copyright© 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
gro.date.issued2010
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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