Encyclopedia of Biometrics

2009 Edition
| Editors: Stan Z. Li, Anil Jain

Face Recognition, Overview

  • Aleix M. Martinez
Reference work entry
DOI: https://doi.org/10.1007/978-0-387-73003-5_84



Face recognition is the science which involves the understanding of how the faces are recognized by biological systems and how this can be emulated by computer systems. Biological systems employ different types of visual sensors (i.e., eyes), which have been designed by nature to suit a certain environment where the agent lives. Similarly, computer systems employ different visual devices to capture and process faces as best indicated by each particular application. These sensors can be video cameras (e.g., a camcorder), infrared cameras, or among others, 3D scans. The essay reviews some of the most advanced computational approaches for face recognition defined till date.


Many types of biometrics exist for identifying a person or verifying that a given individual is what he or she claims to be. Some of the biometrics result in quite reliable recognition and verification, but most are either...

This is a preview of subscription content, log in to check access.


  1. 1.
    Jain, A.K.: Technology: Biometric recognition. Nature 449, 38–40 (2007)CrossRefGoogle Scholar
  2. 2.
    Teoh, A.B.J., Ngo, D., Goh, A.: Personalised cryptographic key generation based on facehashing. Comput. Secur. 23(7), 606–614 (2004)CrossRefGoogle Scholar
  3. 3.
    Martinez, A.M.: Recognizing imprecisely localized, partially occluded and expression variant faces from a single sample per class. IEEE Trans. Pattern Anal. Mach. Intell. 24(6), 748–763 (2002)CrossRefGoogle Scholar
  4. 4.
    M. Yang, D.J., Kriegman, N.A.: Detecting faces in images: A survey. IEEE Trans. Pattern Anal. Mach. Intell. 24, 34–58 (2002)CrossRefGoogle Scholar
  5. 5.
    Zhao, W., Chellappa, R., Phillips, P.J., Rosenfeld, A.: Face recognition: A literature survey. ACM Comput. Surv. 35, 399–458 (2003)CrossRefGoogle Scholar
  6. 6.
    Gross, R., Matthews, I., Baker, S.: Appearance-based face recognition and lightfields. IEEE Trans. Pattern Anal. Mach. Intell. 26(4), 449–465 (2004)CrossRefGoogle Scholar
  7. 7.
    Cootes, T., Edwards, G., Taylor, C.: Active appearance models. IEEE Trans. Pattern Anal. Mach. Intell. 23(6), 681–685 (2001)CrossRefGoogle Scholar
  8. 8.
    Ding, L., Martinez, A.: Precise detailed detection of faces and facial features. In: Proceedings of IEEE Computer Vision and Pattern Recognition, Anchorage, AK, 23 June 2008Google Scholar
  9. 9.
    Sirovich, L., Kirby, M.: A lowdimensional procedure for the characterization of human faces. J. Opt. Soc. Am. A 4(3), 519–524 (1986)CrossRefGoogle Scholar
  10. 10.
    Turk, M., Pentland, A.: Eigenfaces for recognition. J. Cogn. Neurosci. 3(1), 71–86 (1991)CrossRefGoogle Scholar
  11. 11.
    Neth, D., Martinez, A.M.: Emotion perception in emotionless face images suggests a normbased representation. J. Vis. 9(1), 1–11 (2009)CrossRefGoogle Scholar
  12. 12.
    Zebrowitz, L.A.: Reading faces: window to the soul? Westview Press, Boulder, CO (1997)Google Scholar
  13. 13.
    Chang, K.I., Bowyer, K.W., Flynn, P.J.: An evaluation of multimodal 2d + 3d face biometrics. IEEE Trans. Pattern Anal. Mach. Intell. 27(4), 619–624 (2005)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Aleix M. Martinez
    • 1
  1. 1.Department of Electrical and Computer EngineeringOhio State UniversityColumbusUSA