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        3D Face Recognition : Benchmarking with Directional Signature

        Author
        Ramalingam, Sooda
        Attention
        2299/21987
        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.
        Publication date
        2014-01-27
        Published in
        IEEE Transactions on Systems, Man and Cybernetics, Part C: Applications & Reviews
        Published version
        https://doi.org/10.1109/SMC.2013.750
        Other links
        http://hdl.handle.net/2299/21987
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