Factors that influence algorithm performance in the Face Recognition Grand Challenge

Computer Vision and Image Understanding

Volumn 113, Issue 6, 2009, Pages 750-762

  Beveridge, J Ross ^a   Givens, Geof H ^b   Phillips, P Jonathon ^c   Draper, Bruce A ^a  

^a Department of Computer Science   (United States)

^b Veterinary Dentistry and Oral Surgery   (United States)

^c NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY   (United States)

Author keywords

Face recognition; Performance analysis; Statistical modeling; Subject covariates

Indexed keywords

ALGORITHM PERFORMANCE; FACE RECOGNITION ALGORITHMS; FACE RECOGNITION GRAND CHALLENGES; MIXED-EFFECT MODELS; PERFORMANCE ANALYSIS; SPECIFIC EFFECTS; STATISTICAL MODELING; STATISTICAL STUDIES; SUBJECT COVARIATES; VERIFICATION SYSTEMS;

ALGORITHMS; IMAGE RESOLUTION; PROBABILITY DENSITY FUNCTION;

FACE RECOGNITION;

EID: 64049110476     PISSN: 10773142     EISSN: 1090235X     Source Type: Journal    
DOI: 10.1016/j.cviu.2008.12.007     Document Type: Article

References (31)

1. Zhao W., Chellappa R., Rosenfeld A., and Phillips P.J. Face recognition: a literature survey. ACM Computer Surveys 35 (2003) 399-458
2. P.J. Phillips, E. Newton, Meta-analysis of face recognition algorithms, in: Proceedings of the 5th International Conference on Automatic Face and Gesture Recognition, 2002, pp. 235-241.
3. Lee K., Ho J., and Kriegman D. Acquiring linear subspaces for face recognition under variable lighting. IEEE Transactions on Pattern Analysis and Machine Intelligence 27 5 (2005) 684-698
4. Gross R., Baker S., Matthews I., and Kanade T. Face recognition across pose and illumination. In: Li S.Z., and Jain A.K. (Eds). Handbook of Face Recognition (2004), Springer-Verlag 193-216
5. R. Gross, J. Shi, J.F. Cohn, Quo Vadis Face Recognition? The Current State of the art in Face Recognition, Tech. Rep. TR-01-17, Carnegie Mellon University, June 2001.
6. P. Phillips, P. Grother, R. Micheals, D. Blackburn, E. Tabassi, J. Bone, FRVT 2002: Evaluation Report, Tech. Rep., Face Recognition Vendor Test, 2002. Available from: .
7. Geof H. Givens, J. Ross Beveridge, Bruce A. Draper, David Bolme, A statistical assessment of subject factors in the PCA recognition of human faces, in: CVPR 2003 Workshop on Statistical Analysis in Computer Vision Workshop, IEEE Computer Society, 2003, (online only).
8. Geof H. Givens, J. Ross Beveridge, Bruce A. Draper, David Bolme, Using a generalized linear mixed model to study the configuration space of a PCA + LDA human face recognition algorithm, in: Proceedings of Articulated Motion and Deformable Objects, 3rd International Workshop (AMDO 2004), 2004, pp. 1-11.
9. Geof H. Givens, J. Ross Beveridge, Bruce A. Draper, P. Jonathon Phillips, Repeated measures GLMM estimation of subject-related and false positive threshold effects on human face verification performance, in: Empirical Evaluation Methods in Computer Vision Workshop: In Conjunction with CVPR, 2005, (electronic only).
10. Mitra S., Savvides M., and Brockwell A. Statistical performance evaluation of biometric authentication systems using random effects models. IEEE Transactions on Pattern Analysis and Machine Intelligence 29 4 (2007) 517-530
11. Phillips P.J., Flynn P.J., Scruggs T., Bowyer K.W., Chang J., Hoffman K., Marques J., Min J., and Worek W. Overview of the face recognition grand challenge. Conference on Computer Vision and Pattern Recognition (2005), IEEE Computer Society 947-954
12. P. Phillips, P. Flynn, T. Scruggs, K. Bowyer, W. Worek, Preliminary face recognition grand challenge results, in: Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition, Southampton, UK, 2006.
13. C. Xie, M. Savvides, B.V. Kumar, Redundant class-dependence feature analysis based on correlation filters using frgc2.0 data, in: Proceedings of IEEE Computer Vision and Pattern Recognition Conference, vol. 2, 2005, pp. 266-273.
14. Liu C. Capitalize on dimensionality increasing techniques for improving face recognition grand challenge performance. IEEE Transactions on Pattern Analysis and Machine Intelligence 28 5 (2006) 725-737
15. G. Doddington, W. Liggett, A. Martin, M. Przbocki, D. Reynolds, Sheep, goats, lambs and wolves-a statistical analysis of speaker performance in the NIST 1998 speak recognition evaluation, in: 5th International Conference on Spoken Language Processing (ICSLP), Syndey, Australia, 1998, (paper 608).
16. Breslow N.E., and Clayton D.G. Approximate inference in generalized linear mixed models. Journal of the American Statistical Association 8 (1993) 9-25
17. Wolfinger R., and O'Connell M. Generalized linear models: a pseudo-likelihood approach. Journal of Statistical Computation and Simulation 48 (1993) 233-243
18. Littell R.C., Milliken G.A., Stroup W.W., and Wolfinger R. SAS System for Mixed Models (1996), SAS Publishing, Cary NC
19. SAS Institute, The GLIMMIX Procedure, June 2006. Available from: .
20. McCullagh P., and Nelder J.A. Generalized Linear Models. second ed. (1989), Chapman and Hall, New York, NY
21. Y. Yacoob, L. Davis, Smiling faces are better for face recognition, in: International Conference on Face Recognition and Gesture Analysis, 2002, pp. 52-57.
22. T. Faltemier, K. Bowyer, P.J. Flynn, Using a multi-instance enrollment representation to improve 3D face recognition, in: IEEE Conference on Biometrics: Theory, Applications and Systems, 2007, pp. 1-6.
23. Phillips P., Moon H., Rizvi S., and Rauss P. The FERET evaluation methodology for face recognition algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence 22 10 (2000) 1090-1104
24. D.M. Blackburn, M. Bone, P.J. Phillips, Facial Recognition Vendor Test 2000: Executive Overview, Tech. Rep., Face Recognition Vendor Test, 2000. Available form: .
25. P. Phillips, P. Grother, R. Micheals, D. Blackburn, E. Tabassi, J. Bone, FRVT 2002: Overview and Summary, Tech. Rep., Face Recognition Vendor Test, 2002. Available from: .
26. Krotkov E.P. Active Computer Vision by Cooperative Focus and Stereo (1989), Springer-Verlag New York Inc., Secaucus, NJ, USA
27. Kirby M., and Sirovich L. Application of the Karhunen-Loeve procedure for the characterization of human faces. IEEE Transactions on Pattern Analysis and Machine Intelligence 12 1 (1990) 103-107
28. M.A. Turk, A.P. Pentland, Face recognition using eigenfaces, in: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 1991, pp. 586-591.
29. Comaniciu D., and Meer P. Mean shift: a robust approach toward feature space analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 24 (2002) 603-619
30. Furl N., Phillips P.J., and O'Toole A.J. Face recognition algorithms and the other-race effect: computational mechanisms for a developmental contact hypothesis. Cognitive Science 26 (2002) 797-815
31. Geof H. Givens, J. Ross Beveridge, Bruce A. Draper, Patrick Grother, P. Jonathon Phillips, How features of the human face affect recognition: a statistical comparison of three face recognition algorithms, in: Proceedings of IEEE Computer Vision and Pattern Recognition, 2004, pp. 381-388.