Abstract
Linear Discriminant Analysis (LDA) is widely known feature extraction technique that aims at creating a feature set of enhanced discriminatory power. It was addressed by many researchers and proved to be especially successful approach in face recognition. The authors introduced a novel approach Dual LDA (DLDA) and proposed an efficient SVD-based implementation controlled by two parameters. In this paper DLDA is analyzed from the feature space reduction point of view and the role of the parameters is explained. The comparative experiments conducted on facial database consisting of nearly 2000 individuals show superiority of this approach over class of feature selection methods that choose the features one by one relying on classic statistical measures.
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References
Belheumeur, P.N., Hespahna, J.P., Kriegman, D.J.: Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection. IEEE Trans. on PAMI 19, 711–720 (1997)
Bober, M.: Description of MPEG-7 Visual Core Experiments. ISO/IEC JTC1/SC29/WG11, report N749 (2002)
Bailly-Bailliere, E., Bengio, S., Bimbot, F., Hamouz, M., Kittler, J., Mariethoz, J., Matas, J., Messer, K., Popovici, V., Poree, F., Ruiz, B., Thiran, J.P.: The BANCA database and evaluation protocol. Audio- and Video-Based Biometric Person Authentication. In: Kittler, J., Nixon, M.S. (eds.) AVBPA 2003. LNCS, vol. 2688, pp. 625–638. Springer, Heidelberg (2003)
Cevikalp, H., Neamtu, M., Wilkes, M., Barkana, A.: Discriminative Common Vectors for Face Recognition. IEEE Trans. on PAMI 27, 4–13 (2005)
Chen, L.-F., Liao, H.-Y.M., Ko, M.-T., Lin, J.-C., Yu, G.-J.: A New LDA-based Face Recognition System Which Can Solve the Small Sample Size Problem. Pattern Recog. 33, 1713–1726 (2000)
Devijver, P.A., Kittler, J.: Pattern Recognition: A Statistical Approach. Prentice Hall, Englewood Cliffs (1982)
Fukunaga, K.: Introduction to Statistical Pattern Recognition. Academic Press, London (1972)
Golub, G.H., Van Loan, C.F.: Matrix Computations. The John Hopkins University Press (1993)
Liu, K., Yang, J.-Y., Liu, X.: An Efficient Algorithm for Foley-Sammon Optimal Set of Discriminant Vectors by Algebraic Method. Int’l. J. of Pattern Recog. and Artif. Intell. 6, 817–829 (1992)
Messer, K., Matas, J., Kittler, J., Luettin, J., Maitre, G.: XM2VTSbd: The Extended M2VTS Database. In: Proc. 2nd Conf. on Audio and Video-base Biometric Personal Verification, Springer, Heidelberg (1999)
Philips, P.J., Wechsler, H., Huang, J., Rauss, P.: The FERET database and evaluation procedure for face recognition algorithms. Image and Vision Computing J. 16, 295–306 (1998)
Swets, D.L., Weng, J.: Using Discriminant Eigenfeatures for Image Retrieval. IEEE Trans. on PAMI 18, 831–837 (1996)
Xu, Q., Kamel, M.S., Salama, M.M.A.: Significance test for feature subset selection on image recognition. In: Campilho, A.C., Kamel, M.S. (eds.) ICIAR 2004. LNCS, vol. 3211, pp. 244–252. Springer, Heidelberg (2004)
Yu, H., Yang, J.: A Direct LDA Algorithm for High Dimensional Data - with Application to Face Recognition. Pattern Recog. 34, 2067–2070 (2001)
Call for Proposals for Face Recognition Technology. ISO/IEC JTC1/SC29/WG11, report N3676 (2000)
Skarbek, W., Kucharski, K., Bober, M.: Face recognition by fisher and scatter linear discriminant analysis. In: Petkov, N., Westenberg, M.A. (eds.) CAIP 2003. LNCS, vol. 2756, pp. 638–645. Springer, Heidelberg (2003)
Skarbek, W., Kucharski, K., Bober, M.: Dual LDA for Face Recognition. Fundamenta Informaticae 61, 303–334 (2004)
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Kucharski, K., Skarbek, W., Bober, M. (2005). Feature Space Reduction for Face Recognition with Dual Linear Discriminant Analysis. In: Gagalowicz, A., Philips, W. (eds) Computer Analysis of Images and Patterns. CAIP 2005. Lecture Notes in Computer Science, vol 3691. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11556121_72
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DOI: https://doi.org/10.1007/11556121_72
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