Abstract
As face recognition research matures and products are deployed, the performance of such systems is being scrutinized by many constituencies. Performance factors of strong practical interest include the elapsed time between a subject’s enrollment and subsequent acquisition of an unidentified face image, and the number of images of each subject available. In this paper, a long-term image acquisition project currently underway is described and data from the pilot study is examined. Experimental results suggest that (a) recognition performance is substantially poorer when unknown images are acquired on a different day from the enrolled images, (b) degradation in performance does not follow a simple predictable pattern with time between known and unknown image acquisition, and (c) performance figures quoted in the literature based on known and unknown image sets acquired on the same day may have little practical value.
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References
P.J. Phillips, H. Moon, S.A. Rizvi, and P.J. Rauss. The FERET Evaluation Methodology for Face-Recognition Algorithms. IEEE Trans. on PAMI 20, 10 (Oct 2000), 1090–1104.
A.J. O’Toole, T. Vetter, H. Volz, and E.M. Slater, Three dimensional caricatures of human heads: distinctiveness and the perception of facial age, Perception 26, 719–732.
W.S. Yambor, B.A. Draper and J.R. Beveridge, Analyzing PCA-based Face Recognition Algorithms: Eigenvector Selection and Distance Measures, Proc. 2nd Workshop on Empirical Evaluation in Computer Vision, Dublin, Ireland, July 1, 2000.
R. Chellappa, C.L. Wilson, and S. Sirohey, Human and Machine Recognition of Faces: A Survey, Proc. IEEE 83(5), 705–740, May 1995.
D.A. Socolinsky, L.B. Wolff, J.D. Neuheisel, and C.K. Eveland, Illumination Invariant Face Recognition Using Thermal Infrared Imagery, Proc. CVPR 2001, vol. I, 527–534, December 2001.
V. Blanz, S. Romdhani and T. Vetter, Face identification across different poses and illuminations with a 3D morphable model, Proc. 5 th IEEE Int. Conf. Automatic Face and Gesture Recognition, 202–207, 2002.
D.M. Blackburn, J.M. Bone and P.J. Phillips, FRVT 2000 results. http://www.frvt.org/FRVT2000.
P. J. Phillips, P. Grother, R. Micheals, D. M. Blackburn, E. Tabassi, J. M. Bone, “Face Recognition Vendor Test 2002: Evaluation Report”, NISTIR 6965, 2003, http://www.frvt.org.
H. Moon and P.J. Phillips, Computational and performance aspects of PCA-based face recognition algorithms, Perception 30:303–321, 2001.
J. Matas, M. Hamouz, K. Jonsson, J. Kittler, Y. Li, C. Kotropoulos, A. Tefas, I. Pitas, T. Tan, H. Yan, F. Smeraldi, J. Bigun, N. Capdevielle, W. Gerstner, S. Ben-Yacoub, Y. Abdeljaoued, E. Mayoraz, Comparison of face verification results on the XM2VTS database, Proc. ICPR 2000, Barcelona, v. 4, p. 4858–4863, Sept. 2000.
T. Sim, S. Baker, and M. Bsat, The CMU Pose, Illumination, and Expression (PIE) Database, Proceedings of the IEEE International Conference on Automatic Face and Gesture Recognition, pp. 46–51, May 2002.
E. Marszalec, B. Martinkauppi, M. Soriano, M. Pietikäinen (2000), A physicsbased face database for color research, Journal of Electronic Imaging Vol. 9 No. 1 pp. 32–38.
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Flynn, P.J., Bowyer, K.W., Phillips, P.J. (2003). Assessment of Time Dependency in Face Recognition: An Initial Study. 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_6
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DOI: https://doi.org/10.1007/3-540-44887-X_6
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