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The eyes have it

Published:08 November 2003Publication History

ABSTRACT

This paper evaluates the impact of eye localization on face recognition accuracy. To investigate its importance, we present an eye perturbation sensitivity analysis, as well as empirical evidence that reinforces the notion that eye localization plays a key role in the accuracy of face recognition systems. In particular, correct measurement of eye separation is shown to be more important than correct eye location, highlighting the critical role of eye separation in the scaling and normalization of face images. Results suggest that significant gains in recognition accuracy may be achieved by focussing more effort on the eye localization stage of the face recognition process.

References

  1. Batur, Aziz U. and Flinchbaugh, Bruce E. (2001). Performance Analysis of Face Recognition Algorithms on TMS320C64x. Application Report, DSP Solutions R&D Center.Google ScholarGoogle Scholar
  2. Bolme, D. S., Beveridge, J. R., Teixeira, M. and Draper, B. A. (2003). The CSU Face Identification Evaluation System: Its Purpose, Features, and Structure. ICVS 2003: 304--313. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Brunelli, R. and Poggio, T. (1993). Face Recognition: Features vs. Templates. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(10):1042--1052. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Chellappa, R., Wilson, C. L., and Sirohey, S. (1995). Human and Machine Recognition of Faces: A Survey. Proc. of the IEEE, 83(5):705--740.Google ScholarGoogle ScholarCross RefCross Ref
  5. Heseltine, T., Pears, N. and Austin, J. (2002). Evaluation of Image Pre-processing Techniques for Eigenface Based Face Recognition. Tech. Report, Dept. of Comp. Science, Univ. of York.Google ScholarGoogle Scholar
  6. Hole, G. J., George, P. A., Eaves, K. and Rasek, (2002). A. Effects of Geometric Distortions on Face-recognition Performance. Perception 31(10):1221--1240.Google ScholarGoogle Scholar
  7. Huang, C. L. and Chen, C. W. (1992). Human facial feature extraction for face interpretation and recognition. Pattern Recognition, 25(12):1435--1444.Google ScholarGoogle ScholarCross RefCross Ref
  8. Micheals, R. J. and Boult, T. E. (Dec. 2001) Efficient Evaluation of Classification and Recognition Systems. Proc. of the IEEE Conf. on Comp. Vision and Patt. Rec. pp. 50--57.Google ScholarGoogle Scholar
  9. Mu, F., Li, H. Y., and Forchheimer, R. (1996). Automatic Extraction of Human Facial Features. Signal Processing: Image Comm. 8(4):309--326.Google ScholarGoogle ScholarCross RefCross Ref
  10. Okada, K., Steffens, J., Maurer, T., Hong, H., Neven, H. and von der Malsburg, C. (1998). The Bochum/USC Face Recognition System and How It Fared in the FERET Phase III Test. In Wechsler et al., eidtores, Face Recognition: From Theory to Applications, pp. 186--205.Google ScholarGoogle Scholar
  11. Penev, P. S. and Atick, J. J. (1996). Local feature analysis: A general statistical theory for object representation. Neural Systems, 7:477--500.Google ScholarGoogle ScholarCross RefCross Ref
  12. Phillips, P. J., Grother, P., Micheals, R. J., Blackburn, D. M., Tabassi, E., and Bone, M. (2003). Face Recognition Vendor Test 2002 (FRVT 2002). Technical Report NISTIR 6965, NIST.Google ScholarGoogle Scholar
  13. Phillips, P. J., Wechsler, H., Huang, J. S., and Rauss, P. J. (1998). The FERET Database and Evaluation Procedure for Face-Recognition Algorithms. Image & Vision Comp. 16(5):295--306.Google ScholarGoogle ScholarCross RefCross Ref
  14. Sim, T., Baker, S. and Bsat, M. (2002). The CMU Pose, Illumination and Expression (PIE) Database. In Proc. of the IEEE Int. Conference on Automatic Face and Gesture Recognition. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Stringa, L. (1993). Eyes detection for face recognition. Appl. Art. Intelligence, 7(4):365--382.Google ScholarGoogle ScholarCross RefCross Ref
  16. Takács, B. and Wechsler, H. (1997). Detection of Faces and Facial Landmarks Using Iconic Filter Banks. Pattern Recognition, 30(10):1623--1636.Google ScholarGoogle ScholarCross RefCross Ref
  17. Turk, M. A. and Pentland A. P. (1991). Face Recognition Using Eigenfaces. In Proc. of IEEE Conf. on Comp. Vision and Patt. Rec., pp. 586--591.Google ScholarGoogle ScholarCross RefCross Ref

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  1. The eyes have it

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        cover image ACM Conferences
        WBMA '03: Proceedings of the 2003 ACM SIGMM workshop on Biometrics methods and applications
        November 2003
        133 pages
        ISBN:1581137796
        DOI:10.1145/982507

        Copyright © 2003 ACM

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        • Published: 8 November 2003

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