3D Face Recognition: Feature Extraction Based on Directional Signatures from Range Data and Disparity Maps

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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.
Original languageEnglish
Title of host publication2013 IEEE International Conference on Systems, Man, and Cybernetics
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages4397-4402
Number of pages6
ISBN (Electronic)9781479906529
DOIs
Publication statusE-pub ahead of print - 27 Jan 2014

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