Automatic 3D face recognition using fourier descriptors.
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ELYAN, E. and UGAIL, H., 2009. Automatic 3D face recognition using fourier descriptors. In: H. UGAIL, R.S.R. QAHWAJI, R.A. EARNSHAW and P.J. WILLIS, eds. CYBERWORLDS 2009 : Proceedings of the 2009 International Conference on CYBERWORLDS ; CW 2009. 7-11 September 2009. Los Alamitos, CA: IEEE Computer Society. pp. 246-252.
3D face recognition is attracting more attention due to the recent development in 3D facial data acquisition techniques. It is strongly believed that 3D Face recognition systems could overcome the inherent problems of 2D face recognition such as facial pose variation, illumination, and variant facial expression. In this paper we present a novel technique for 3D face recognition system using a set of parameters representing the central region of the face. These parameters are essentially vertical and cross sectional profiles and are extracted automatically without any prior knowledge or assumption about the image pose or orientation. In addition, these profiles are stored in terms of their Fourier Coefficients in order to minimize the size of input data. Our approach is validated and verified against two different datasets of 3D images covers enough systematic and pose variation. High recognition rate was achieved.