Assessment of Time Dependency in Face Recognition: An Initial Study
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.
KeywordsFace Recognition Face Image Face Recognition System Automatic Face Gallery Image
Unable to display preview. Download preview PDF.
- 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.Google Scholar
- 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.Google Scholar
- 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.Google Scholar
- R. Chellappa, C.L. Wilson, and S. Sirohey, Human and Machine Recognition of Faces: A Survey, Proc. IEEE 83(5), 705–740, May 1995.Google Scholar
- 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.Google Scholar
- 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.Google Scholar
- 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.
- 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.Google Scholar
- 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.Google Scholar