On the Relevance of Facial Expressions for Biometric Recognition

  • Marcos Faundez-Zanuy
  • Joan Fabregas
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5042)


Biometric face recognition presents a wide range of variability sources, such as make up, illumination, pose, facial expression, etc. In this paper we use the Japanese Female Facial Expression Database (JAFFE) in order to evaluate the influence of facial expression in biometric recognition rates. In our experiments we used a nearest neighbor classifier with different number of training samples, different error criteria, and several feature extractions. Our experimental results reveal that some facial expressions produce a recognition rate drop, but the optimal length of the feature extracted vectors is the same with the presence of facial expressions than with neutral faces.


Facial Expression Face Recognition Discrete Cosine Transform Mean Absolute Difference Biometric System 
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  1. 1.
    Ekman, P., Friesen, W.V., Ellsworth, P.: What emotion categories or dimensions can observes judge from facial behavior? In: Ekman, P. (ed.) Emotions in the Human Face, pp. 39–55. Cambridge University Press, London (1982)Google Scholar
  2. 2.
    Ekman, P.: Cross-cultural studies of facial expression. In: Ekman, P. (ed.) Darwin and Facial Expression, pp. 169–222. Academic Press Inc., London (1973)Google Scholar
  3. 3.
    Lyons, M., Akamatsu, S., Kamachi, M., Gyoba, J.: Coding Facial Expressions with Gabor Wavelets. In: Third IEEE International Conference on Automatic Face and Gesture Recognition, pp. 200–205 (April 1998)Google Scholar
  4. 4.
    Ekman, P., Friesen, W.: Constants Across Cultures in the Face and Emotion. Journal of Personality and Social Psychology 17(2), 124–129 (1971)CrossRefGoogle Scholar
  5. 5.
    Li, S.Z., Jain, A.K.: Handbook of face recognition. Springer, Heidelberg (2006)zbMATHGoogle Scholar
  6. 6.
    Faundez-Zanuy, M.: Biometric security technology. IEEE Aerospace and Electronic Systems Magazine 21(6), 15–26 (2006)CrossRefGoogle Scholar
  7. 7.
    Faundez-Zanuy, M.: Face Recognition in a Transformed Domain. In: IEEE Proceedings 37th Annual International Carnahan Conference On Security Tecnology, pp. 290–297 (2003)Google Scholar
  8. 8.
    Gibson, J.D.: Digital compression for multimedia, principles and standards. Morgan Kaufmann, San Francisco (1998)Google Scholar
  9. 9.
    Jain, A.K.: Fundamentals of digital image processing. Prentice Hall, Englewood Cliffs (1989)zbMATHGoogle Scholar
  10. 10.
    Faundez-Zanuy, M., Roure, J., Espinosa-Duró, V., Ortega, J.A.: An efficient face verification method in a transform domain. Pattern recognition letters 28(7), 854–858 (2007)CrossRefGoogle Scholar
  11. 11.
    Martinez, A.M.: Recognizing Imprecisely Localized, Partially Occluded, and Expres-sion Variant Faces from a Single Sample per Class. IEEE Transaction On Pattern Analysis and Machine Intelligence 24(6), 748–763 (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Marcos Faundez-Zanuy
    • 1
  • Joan Fabregas
    • 1
  1. 1.Escola Universitària Politècnica de Mataró (Adscrita a la UPC)MATARO (BARCELONA)Spain

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