University of Hertfordshire

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3D Face Recognition: Benchmarking with Directional Signature

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Original languageEnglish
Number of pages7
JournalIEEE Transactions on Systems, Man and Cybernetics, Part C: Applications & Reviews
DOIs
Publication statusPublished - 27 Jan 2014

Abstract

In 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.

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