3D Face Recognition: Benchmarking with Directional Signature

Sooda Ramalingam

doi:10.1109/SMC.2013.750

3D Face Recognition: Benchmarking with Directional Signature

Sooda Ramalingam

Centre for Engineering Research

Research output: Contribution to journal › Article › peer-review

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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 language	English
Number of pages	7
Journal	IEEE Transactions on Systems, Man and Cybernetics, Part C: Applications & Reviews
DOIs	https://doi.org/10.1109/SMC.2013.750
Publication status	Published - 27 Jan 2014

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10.1109/SMC.2013.750

S Ramalingam 4
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3D Face Recognition: Benchmarking with Directional Signature

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