On internal representations in face recognition systems

Pattern Recognition

Volumn 33, Issue 7, 2000, Pages 1161-1177

  Grudin, Maxim A ^a  

^a Miros Inc   (United States)

Author keywords

Computer vision; Eigenfaces; Elastic graphs; Face recognition; Multiresolution techniques; Neural networks; Principal component analysis; Template matching; Wavelets

Indexed keywords

COMPUTER VISION; FEATURE EXTRACTION; IMAGE ANALYSIS; NEURAL NETWORKS; PATTERN MATCHING; PATTERN RECOGNITION SYSTEMS; STATISTICAL METHODS;

FACE RECOGNITION SYSTEMS; PRINCIPAL COMPONENT ANALYSIS (PCA); TEMPLATE MATCHING;

OBJECT RECOGNITION;

EID: 0033734303     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0031-3203(99)00104-1     Document Type: Article

References (56)

1. A. Samal, P.A. Iyengar, Automatic recognition and analysis of human faces and facial expressions: a survey, Pattern Recognition 25 (1992) 65-77.
2. D. Valentin, H. Abdi, A.J. O'Toole, G.W. Cottrell, Connectionist models of face processing: a survey, Pattern Recognition 27 (1994) 1209-1230.
3. R. Chellappa, C.L. Wilson, S. Sirohey, Human and machine recognition of faces: a survey, Proc. IEEE 83 (1995) 705-740.
4. J. Daugman, Face and gesture recognition: overview, IEEE Trans. Pattern Anal. Mach. Intell. 19 (1997) 675-676.
5. R. Brunelli, T. Poggio, Face recognition: features versus templates, IEEE Trans. Pattern. Anal. Mach. Intell 15 (1993) 1042-1052.
6. W.W. Bledsoe. The model method in facial recognition, Panoramic Research Inc., Tech. Rep. PRI:15, Palo Alto, CA, 1964.
7. A.J. Goldstein, L.D. Harmon, A.B. Lesk, Identification of human faces, Proc. IEEE 59 (1971) 748.
8. Y. Kaya, K. Kobayashi, A basic study on human face recognition, in: S. Watanabe (Ed.), Frontiers of Pattern Recognition, Academic Press, New York, 1972, pp. 265-289.
9. T. Poggio, F. Girosi, Networks for approximation and learning, Proc. IEEE 78 (1990) 1481-1497.
10. I. Craw, H. Ellis, J.R. Lishman, Automatic extraction of face features, Pattern Recognition Lett. 5 (1987) 183-187.
11. M. Bichsel. Strategies of robust object recognition for identification of human faces. Ph.D. thesis, Eidgenossischen Technischen Hochschule, Zurich, 1991.
12. X. Jia, M.S. Nixon, Extending the feature vector for automatic face recognition, IEEE Trans. Pattern. Anal. Mach. Intell 17 (1995) 1167-1176.
13. R.J. Baron, Mechanisms of human facial recognition, Int. J. Man. Mach. Stud. 15 (1981) 137-178.
14. K. Karhunen, Über lineare methoden in der Wahrscheinlichkeitsrechnung, Ann. Acad. Sci. Fennicae Ser. A1, Math. Phys. 37 (1946).
15. L. Sirovich, M. Kirby, Low-dimensional procedure for the characterisation of human face, J. Opt. Soc. Amer. 4 (1987) 519-524.
16. M. Kirby, L. Sirovich, Application of the Karhunen-Loeve procedure for the characterization of human faces, IEEE Trans. Patt. Anal. Mach. Intell. 12 (1990) 103-108.
17. M.A. Turk, A.P. Pentland, Face recognition using eigenfaces, Proceedings of the International Conference on Pattern Recoginition, 1991, pp. 586-591.
18. J. Zhang, Y. Yan, M. Lades, Face Recognition: Eigenface, Elastic Matching and Neural Nets, Proceedings of the IEEE 85 (1997) 1423-1435.
19. A.P. Pentland, B. Moghaddam, T. Starner, M.A. Turk, View-based and modular eigenspaces for face recognition, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1994, pp. 84-91.
20. D.J. Beymer, Face Recognition Under Varying Pose, A.I. Memo No. 1461, MIT, New York, 1993.
21. A.J. O'Toole, K.A. Deffenbacher, J. Barlett. Classifying faces by race and sex using an autoassociative memory trained for recognition, Proceedings, of the 13th Annual Conference Cognition Science Society, Hillsdale, Erlbaum, NJ; 1991.
22. A.J. O'Toole, H. Abdi, K.A. Deffenbacher, D. Valentin, A low dimensional representation of faces in the higher dimensions of space, J. Opt. Soc. Amer. A 10 (1993) 405-411.
23. A.J. O'Toole, H. Abdi, K.A. Deffenbacher, D. Valentin, A perceptual learning theory of the information in faces, in: T. Valentine (Ed.), Cognitive and Computational Aspects of Face Recognition, Routledge, London, 1995, pp. 159-182.
24. K.T. Blackwell, T.P. Vogl, S.D. Hyman, G.S. Barbour, D.L. Alkon, A new approach to hand-written character recognition, Pattern Recognition 25 (1992) 655-666.
25. B. Moghaddam, A. Pentland, Probabilistic visual learning for object representation, IEEE Trans. Pattern Anal. Mach. Intell. 19 (1997) 696-710.
26. P. Werbos. Beyond regression: new tools for prediction and analysis in the behavioral sciences. Ph.D. Thesis, Applied Mathematics, Harvard University, 1974.
27. E. Oja, A simplified neuron model as a principal component Analyzer, J. Math. Biol. 13 (1982) 267-273.
28. G.W. Cottrell, P. Munro. Principal component analysis of images via backpropagation. Proc. Soc. Photo-Optical Instrum. Engng. (1988) 1070-1076.
29. M. Kosugi. Robust identification of human face using mosaic pattern and BNP, Proceedings of the International Conference on Neural Networks for Signal Processing, 1992, pp. 209-305.
30. P.G. Luebbers, O.A. Uwechue, A.S. Pandya, A neural network based facial recognition system, Proc. SPIE 2243 (1994) 595-606.
31. O. Nakamura, S. Mathur, T. Minami, Identification of human faces based on isodensity maps, Pattern Recognition 24 (1991) 263-272.
32. J.M. Vincent, J.B. Waite, D.J. Myers, Automatic location of visual features by a system of multilayered perceptrons, IEE Proc.-F 139 (1992) 405-412.
33. F. Goudail, E. Lange, T. Iwamoto, K. Kyuma, N. Otsu, Fast face recognition method using high order autocorrelations, Proceedings of the International Joint Conference on Neural Networks, 1993, pp. 1297-1300.
34. M.F. Augusteijn, T.L. Skufca. Identification of human faces through texture-based feature recognition and neural network technology, Proceedings of the IEEE Conference on Neural Networks, 1993, pp. 392-398.
35. G.W. Cottrell, M.K. Fleming, Face recognition using unsupervised feature extraction, Proceedings of the International Conference on Neural Networks. Paris, 1990, pp. 322-325.
36. B.A. Golomb, D.T. Lawrence, T.J. Sejnowski, Sexnet: a neural network identifies sex from human faces, in: D.S. Touretzky, R. Lipmann (Eds.), Advances in Neural Computation Processing Systems, vol. 3, Kaufmann, San Mateo, 1991, pp. 572-577.
37. A. Lanitis, C.J. Taylor, T.F. Cootes, Automatic interpretation and coding of face images using flexible templates, IEEE Trans. Pattern Anal. Machine Intell. 19 (1997) 743-756.
38. A. Lanitis, C.J. Taylor, T.F. Cootes, Automatic face identification system using flexible appearance models, image and vision comput. 13 (1995) 393-401.
39. A. Yuille, D. Cohen, P. Hallinan. Feature extraction from faces using deformable templates. Proc. IEEE Computer Society Conference on Computer Vision and Pattern. Recognition 1989 104-109.
40. B.F.J. Manly, Multivariate Statistical Methods, a Primer, Chapman & Hall, London, 1986.
41. T.F. Cootes, C.J. Taylor, A. Lanitis. Active shape models: evaluation of the multiresolution method for improving image search, Proceedings of the 5th Br. Machine Vision Conference. BMVA Press, 1994, pp. 327-336.
42. I. Craw, P. Cameron. Parameterizing images for recognition and reconstruction, Proceedings of the BMVC 91 Glasgow, Scotland 1991, pp. 367-370.
43. I. Craw, A manifold model of face and object recognition, in: T. Valentine (Ed.), Cognitive and Computational Aspects of Face Recognition: Explorations in Face Space, Routledge, London, 1995, pp. 183-203.
44. M. Grudin, A compact multi-level model for the recognition of facial images Ph.D. Thesis Liverpool John Moores University, UK, 1997.
45. P. Penev, J.J. Atick, Local feature analysis: a general statistical theory for object representation, Network: Comput. Neural Systems 7 (1996) 477-500.
46. K.K. Sung, T. Poggio, Example-based learning for view-based human face detection, IEEE Trans. Pattern Anal. Machine Intell. 20 (1998).
47. M. Lades, J.C. Vorbruggen, J. Buhmann, J. Lange, C.v.d. Malsburg, R.P. Wurtz, W. Konen, Distortion invariant object recognition in the dynamic link architecture, IEEE Trans. Comput. 42 (1993) 300-311.
48. J. Daugman, Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by 2D visual cortical filters, J. Opt. Soc. Amer. (A) 2 (1985) 1160-1169.
49. D.L. Alkon, Memory storage and neural systems, Sci. Am. 261 (1989) 42-50.
50. D.L. Alkon, K.T. Blackwell, G.S. Barbour, S.A. Werness, T.P. Vogl, Biological plausibility of synaptic associative memory models, Neural Networks 7 (1994) 1005-1017.
51. L. Wiskott, J.M. Fellows, N. Krüger, C.v.d. Malsburg, Face recognition by elastic bunch graph matching, IEEE Trans, on Pattern. Anal. Mach. Intell. 19 (1997) 775-779.
52. N. Krüger, An algorithm for the learning of weights in discrimination functions using a priori constraints, IEEE Trans. Pattern Anal. Mach. Intell. 19 (1997) 764-768.
53. R.P. Würtz, Object recognition robust under translations, deformations, and changes in background, IEEE Trans. Pattern Anal. Mach. Intell. 19 (1997) 769-774.
54. M.A. Grudin, P.J.G. Lisboa, D.M. Harvey, Compact multi-level representation of human faces for recognition, Proceedings of IEE Conference on IPA-97 1997, 111-115.
55. P. Kalocsai, H. Neven, J. Steffens. Statistical analysis of gabor-filter representation, Proceedings of the Third IEEE International Conference on Automatic Face and Gesture Recognition, Nara, Japan, 1998, pp. 360-365.
56. D.J. Field, Relations between the statistics of natural images and the response properties of cortical cells, J. Opt. Soc. Am. (A) 4 (1997) 2379-2394.