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Wavelet-Based 2-Parameter Regularized Discriminant Analysis for Face Recognition

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Audio- and Video-Based Biometric Person Authentication (AVBPA 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2688))

Abstract

This paper addresses the small-size problem in Fisher Discriminant Analysis. We propose to use wavelet transform for preliminary dimensionality reduction and use a two-parameter regularization scheme for the within-class scatter matrix. The novelty of the proposed method comes from: (1) Wavelet transform with linear computation complexity is used to carry out the preliminary dimensionality reduction instead of employing a principal component analysis. The wavelet filtering also acts as smoothing out noise. (2) An optimal solution is found in the full space instead of a sub-optimal solution in a restricted subspace. (3) Detailed analysis for the contribution of the eigenvectors of the within-class scatter matrix to the overall classification performance is carried out. (4) An enhanced algorithm is developed and applied to face recognition. The recognition accuracy (rank 1) for the Olivetti database using only three images of each person as training set is 96.7859%. The experimental results show that the proposed algorithm could further improve the recognition performance.

search of this author is partly supported by NSF of China, NSF of GuangDong and ZAAC.

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References

  1. P.N. Belhumeur, J.P. Hespanha, D. J. Kriegman, Eigenfaces vs. Fisherfaces: recognition using class specific linear projection, IEEE Trans. Pattern Anal. Mach. Intell., Vol. 19 (7) (1997), 711–720.

    Article  Google Scholar 

  2. R. Chellappa, C. Wilson, S. Sirohey, Human and machine recognition of faces: a survey, Proc. IEEE, Vol. 83 (5) (1995) 705–740.

    Google Scholar 

  3. D.Q. Dai and P.C. Yuen, Regularized discriminant analysis and its applications to face recognition, Pattern Recognition, Vol. 36 (2003), 845–847

    Article  MATH  Google Scholar 

  4. I. Daubechies, Ten lectures on wavelets, CBMS-NSF Regional Conf. Series in Appl. Math., Vol. 61, SIAM Philadelphia, PA, 1992.

    Google Scholar 

  5. K. Etemad and R. Chellappa. Discriminant analysis for recognition of human face images. J. Opt. Soc. Am. A, 14(1997)1724–1733.

    Article  Google Scholar 

  6. W. J. Krzanowski, P. Jonathan, W.V. McCarthy and M.R. Thomas, Discriminant analysis with singular covariance matrices: methods and applications to spectroscopic data, Appl. Statist., Vol. 44(1995), 101–115.

    Article  MATH  Google Scholar 

  7. P. J. Phillips, H. Moon, S.A. Rizvi and P. J. Rauss, The FERET evaluation methodology for face-recognition algorithms, IEEE Trans. Pattern Anal. Mach. Intell., Vol. 22(10)(2000), 1090–1104.

    Article  Google Scholar 

  8. L. Sirovich and M. Kirby, Application of the Karhunen-Loeve procedure for the characterization of human faces, IEEE Trans. Pattern Anal. Mach. Intell., Vol. 12(1990), 103–108.

    Article  Google Scholar 

  9. D. Swets, J. Weng, Using discriminant eigenfeatures for image retrieval, IEEE Trans. Pattern Anal. Mach. Intell., Vol. 18 (8) (1996), 831–836.

    Article  Google Scholar 

  10. M. Turk and A. Pentland, Eigenfaces for recognition, Journal of Cognitive Neuroscience, Vol. 3(1)(1991)72–86.

    Article  Google Scholar 

  11. H. Yu and J. Yang, A direct LDA algorithm for high-dimensional data-with application to face recognition, Pattern Recognition, Vol. 34(2001), 2067–2070.

    Article  MATH  Google Scholar 

  12. W. Zhao, R. Chellappa and P. J. Phillips, Subspace linear discriminant analysis for face recognition, Center for Automation Research, University of Maryland, College Park, Technical Report CAR-TR-914, 1999.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Center for Computer Vision, Faculty of Mathematics and Computing, Zhongshan University, 510275, Guangzhou, China

    Dao-Qing Dai

  2. Department of Computer Science, Hong Kong Baptist University, Hong Kong

    P. C. Yuen

Authors
  1. Dao-Qing Dai
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  2. P. C. Yuen
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Editor information

Editors and Affiliations

  1. Center for Vision, Speech and Signal Proc., University of Surrey, GU2 7XH, Guildford, Surrey, UK

    Josef Kittler

  2. Department of Electronics and Computer Science, University of Southampton, SO17 1BJ, Southampton, UK

    Mark S. Nixon

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© 2003 Springer-Verlag Berlin Heidelberg

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Dai, DQ., Yuen, P.C. (2003). Wavelet-Based 2-Parameter Regularized Discriminant Analysis for Face Recognition. In: Kittler, J., Nixon, M.S. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2003. Lecture Notes in Computer Science, vol 2688. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44887-X_17

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  • DOI: https://doi.org/10.1007/3-540-44887-X_17

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40302-9

  • Online ISBN: 978-3-540-44887-7

  • eBook Packages: Springer Book Archive

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