Abstract
This paper presents a system to determine lighting effiects within face images. The theories of multivariate discriminant analysis and wavelet packets transform are utilised to develop the proposed system. An extensive set of face images of different poses, illuminated from different angles, are used to train the system. The performance of the proposed system is evaluated by conducting experiments on different test sets, and by comparing its results against those of some existing counterparts.
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References
B. K. P. Horn and M. J. Brooks, Eds., Shape from Shading, MIT Press, Cambridge, Mass., 1989.
Y. Moses and S. Ullman, “Limitation of non-model-based recognition schemes,” in Proc. European Conference on Computer Vision, G. Sandini, Ed., 1992, pp. 820–828.
R. Brunelli and T. Poggio, “Hyperbf networks for real object recognition,” in Proc. IJCAI, Sydney, Australia, 1991, pp. 1278–1284.
J. Buhmann, M. Lades, and F. Eeckman, “Asilicon retina for face recognition,”Tech. Rep. 8996-CS, Institute of informatik, University of Bonn, 1993.
D. Reisfeld and Y. Yeshurun, “Robust detection of facial features by generalised symmetry,” in Proc. International Conference on Pattern Recognition A, 1992, pp. 117–120.
Y. Adini, Y. Moses, and S. Ullman, “Face recognition: The problem of compensating for changes in illumination direction,” IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 721–732, July 1997.
P. Hallinan, “A low-dimensional representation of human faces for arbitrary lighting conditions,” in Proc. IEEE Conf. Computer Vision and Pattern Recognition, 1994, pp. 995–999.
R. Brunelli, “Estimation of pose and illumination direction for face processing,” Tech. Rep. TR-AI 1499, Massachusetts Institute of Technology, November 1994.
R. Brunelli and T. Poggio, “Face recognition: Features versus templates,” IEEE Transaction on Pattern Analysis and Machine Intelligence, vol. 15, no. 10, pp. 1042–1052, 1993.
P. N. Belhumeur, J. P. Hespanha, and D. J. Kriegman, “Eigenfaces vs. fisherfaces: Recognition using class specific linear projection,” IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 711–720, July 1997.
G. J. McLachlan, Discriminant Analysis and Statistical Pattern Recognition, Wiley, New York, 1992.
A. Z. Kouzani, F. He, and K. Sammut, “Towards invariant face recognition,” International Journal of Information Science, vol. 123, no. 1–2, pp. 75–101, 2000.
A. Hyvarinen, J. Karhunen, and E. Oja, Independent Component Analysis, John Wiley and Sons, 2001.
R. R. Coifman and M. V. Wickerhauser, “Entropy-based algorithms for best basis selection,” IEEE Trans. Infor. Theory, vol. 38, no. 2, pp. 713–718, March 1992.
D. L. Swets and J. J. Weng, “Shoslif-o: Shoslif for object recognition and image retrieval (phase ii),” Tech. Rep. CPS-95-39, Michigan State University, October 1995.
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© 2001 Springer-Verlag Berlin Heidelberg
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Kouzani, A.Z., Ong, S.H. (2001). Wavelet Packets for Lighting-Effects Determination. In: Tang, Y.Y., Yuen, P.C., Li, Ch., Wickerhauser, V. (eds) Wavelet Analysis and Its Applications. WAA 2001. Lecture Notes in Computer Science, vol 2251. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45333-4_24
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DOI: https://doi.org/10.1007/3-540-45333-4_24
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