Face Recognition: Would Going Back to Functional Nature Be a Good Idea?

  • Noslen Hernández
  • Yoanna Martínez-Díaz
  • Dania Porro-Muñoz
  • Heydi Méndez-Vázquez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7441)


Traditional appearance-based methods for face recognition represent raw face images of size u ×v as vectors in a u×v-dimensional space. However in practice, this space can be too large to perform classification. For that reason, dimensionality reduction techniques are usually employed. Most of those traditional approaches do not take advantage of the spatial correlation of pixels in the image, considering them as independent. In this paper, we proposed a new representation of face images that takes into account the smoothness and continuity of the face image and at the same time deals with the dimensionality of the problem. This representation is based on Functional Data Analysis so, each face image is represented by a function and a recognition algorithm for functional spaces is formulated. The experiments on the AT&T and Yale B facial databases show the effectiveness of the proposed method.


Face recognition functional data analysis biometrics 


  1. 1.
    Jain, A.K., Li, S.Z.: Handbook of Face Recognition. Springer-Verlag New York, Inc., Secaucus (2005)Google Scholar
  2. 2.
    Zhao, W., Chellappa, R., Phillips, P.J., Rosenfeld, A.: Face recognition: A literature survey. ACM Comput. Surv. 35, 399–458 (2003)CrossRefGoogle Scholar
  3. 3.
    Jafri, R., Arabnia, H.R.: A survey of face recognition techniques. Journal of Information Processing Systems 5(2) (2009)Google Scholar
  4. 4.
    Turk, M., Pentland, A.: Eigenfaces for recognition. J. Cognitive Neuroscience 3(1), 71–86 (1991)CrossRefGoogle Scholar
  5. 5.
    Belhumeur, P.N., Hespanha, J.P., Kriegman, D.J.: Eigenfaces vs. Fisherfaces: recognition using class specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence 19(7), 711–720 (1997)CrossRefGoogle Scholar
  6. 6.
    Yuen, P.: Face representation using independent component analysis. Pattern Recognition 35(6), 1247–1257 (2002)MathSciNetzbMATHCrossRefGoogle Scholar
  7. 7.
    Wright, J., Yang, A.Y., Ganesh, A., Sastry, S.S., Ma, Y.: Robust face recognition via sparse representation. IEEE Trans. Pattern Anal. Mach. Intell. 31(2), 210–227 (2009)CrossRefGoogle Scholar
  8. 8.
    Ramsay, J., Silverman, B.: Functional data analysis. Springer series in statistics. Springer (2005)Google Scholar
  9. 9.
    Ferraty, F., Vieu, P.: Nonparametric Functional Data Analysis: Theory and Practice. Springer Series in Statistics. Springer-Verlag New York, Inc., Secaucus (2006)zbMATHGoogle Scholar
  10. 10.
    Naseem, I., Togneri, R., Bennamoun, M.: Linear regression for face recognition. IEEE Trans. Pattern Anal. Mach. Intell. 32(11), 2106–2112 (2010)CrossRefGoogle Scholar
  11. 11.
    Basri, R., Jacobs, D.W.: Lambertian reflectance and linear subspaces. IEEE Transactions on Pattern Analysis and Machine Intelligence 25, 218–233 (2003)CrossRefGoogle Scholar
  12. 12.
    Samaria, F.S., Harter, A.C.: Parameterisation of a stochastic model for human face identification. In: Second IEEE Workshop Applications of Computer Vision (1994)Google Scholar
  13. 13.
    Lee, K.-C., Ho, J., Kriegman, D.J.: Acquiring linear subspaces for face recognition under variable lighting. IEEE Transactions on Pattern Analysis and Machine Intelligence 27(5), 684–698 (2005)CrossRefGoogle Scholar
  14. 14.
    Yang, J., Zhang, D., Frangi, A.F., Yang, J.-y.: Two-dimensional pca: A new approach to appearance-based face representation and recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 26, 131–137 (2004)CrossRefGoogle Scholar
  15. 15.
    Jiang, X., Mandal, B., Kot, A.: Eigenfeature regularization and extraction in face recognition. IEEE Trans. Pattern Anal. Mach. Intell. 30(3), 383–394 (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Noslen Hernández
    • 1
  • Yoanna Martínez-Díaz
    • 1
  • Dania Porro-Muñoz
    • 1
  • Heydi Méndez-Vázquez
    • 1
  1. 1.Advanced Technologies Application CenterHavanaCuba

Personalised recommendations