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dc.contributor.authorRamalingam, Sooda
dc.identifier.citationRamalingam , S 2014 , ' 3D Face Recognition : Benchmarking with Directional Signature ' , IEEE Transactions on Systems, Man and Cybernetics, Part C: Applications & Reviews .
dc.identifier.otherPURE: 1179258
dc.identifier.otherPURE UUID: 5c583178-9c32-4edc-ab12-06e203592995
dc.description© 2014 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.
dc.description.abstractIn this paper, the author presents a work on i) range data and ii) stereo-vision system based disparity map profiling that are used as signatures for 3D face recognition. The signatures capture the intensity variations along a line at sample points on a face in any particular direction. The directional signatures and some of their combinations are compared to study the variability in recognition performances. Two 3D face image datasets namely, a local student database captured with a stereo vision system and the FRGC v1 range dataset are used for performance evaluation.en
dc.relation.ispartofIEEE Transactions on Systems, Man and Cybernetics, Part C: Applications & Reviews
dc.title3D Face Recognition : Benchmarking with Directional Signatureen
dc.contributor.institutionSchool of Engineering and Technology
dc.contributor.institutionScience & Technology Research Institute
dc.contributor.institutionDigital Media Processing and Biometrics
dc.contributor.institutionCentre for Engineering Research
dc.contributor.institutionSmart Electronics Devices and Networks
dc.description.statusPeer reviewed
rioxxterms.typeJournal Article/Review

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