Optimal linear combination of facial regions for improving identification performance

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 37, Issue 5, 2007, Pages 1138-1148

  Wong, Kin Chung ^a   Lin, Wei Yang ^b   Hu, Yu Hen ^a   Boston, Nigel ^a   Zhang, Xueqin ^c  

^a University of Wisconsin Madison   (United States)

^b NATIONAL CHUNG CHENG UNIVERSITY   (Taiwan)

^c EAST CHINA UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

3 D faces; Face recognition; Face Recognition Grand Challenge (FRGC); Information fusion

Indexed keywords

ALGORITHMS; COMPUTATIONAL GEOMETRY; DISCRIMINANT ANALYSIS; FEATURE EXTRACTION; INFORMATION FUSION; THREE DIMENSIONAL;

FACIAL REGIONS; LINEAR DISCRIMINANT ANALYSIS; MULTIREGION FACE RECOGNITION;

FACE RECOGNITION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; BIOMETRY; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; EVALUATION; FACE; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; INFORMATION RETRIEVAL; METHODOLOGY; QUALITY CONTROL; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIOMETRY; COMPUTER SIMULATION; FACE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; INFORMATION STORAGE AND RETRIEVAL; LINEAR MODELS; MODELS, BIOLOGICAL; PATTERN RECOGNITION, AUTOMATED; QUALITY CONTROL; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 35148868111     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2007.895325     Document Type: Article

References (59)

1. K. W. Bowyer, K. Chang, and P. Flynn, "A survey of approaches to three-dimensional face recognition," in Proc. Int. Conf. Pattern Recog., 2004, vol. 1, pp. 358-361.
2. W. Zhao, R. Chellappa, P. J. Phillips, and A. Rosenfeld, "Face recognition: A literature survey," ACM Comput. Surv., vol. 35, no. 4, pp. 399-458, 2003.
3. P. J. Phillips, H. Moon, S. A. Rizvi, and P. J. Rauss, "The feret evaluation methodology for face-recognition algorithms," IEEE Trans. Pattern Anal. Mach. Intell., vol. 22, no. 10, pp. 1090-1104, Oct. 2000.
4. P. J. Phillips, P. Grother, R. Micheals, D. M. Blackburn, E. Tabassi, and M. Bone, "Face recognition vendor test 2002," in Proc. Int. Workshop Anal. and Model. Faces and Gestures, 2003, p. 44.
5. K. I. Chang, K. W. Bowyer, and P. J. Flynn, "An evaluation of multimodal 2D + 3D face biometrics," IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 4, pp. 619-624, Apr. 2005.
6. M. Jones and P. Viola, "Face recognition using boosted local features," Mitsubishi Electr. Res. Lab., Cambridge, MA, Tech. Rep. TR2003-25, Apr. 2003.
7. A. Pentland, B. Moghaddam, and T. Starner, "View-based and modular eigenspaces for face recognition," in Proc. IEEE Conf. CVPR, 1994, pp. 84-91.
8. W. Y. Lin, N. Boston, and Y. H. Hu, "Summation invariant and its application to shape recognition," in Proc. IEEE Int. Conf. Acoust., Speech, and Signal Process., 2005, vol. V, pp. 205-208.
9. W. Y. Lin, K. C. Wong, N. Boston, and Y. H. Hu, "Fusion of summation invariants in 3D human face recognition," in Proc. IEEE Conf. Comput. Vis. and Pattern Recog., 2006, vol. 2, pp. 1369-1376.
10. J. Kittler, M. Hatef, R. P. W. Dum, and J. Matas, "On combining classifiers," IEEE Trans. Pattern Anal. Mach. Intell., vol. 20, no. 3, pp. 226-239, Mar. 1998.
11. L. Hong and A. K. Jain, "Integrating faces and fingerprints for personal identification," IEEE Trans. Pattern Anal. Mach. Intell. vol. 20, no. 12, pp. 1295-1307, Dec. 1998.
12. A. Ross and A. Jain, "Information fusion in biometrics," Pattern Recognit. Lett., vol. 24, no. 13, pp. 2115-2125, 2003.
13. D. Wolpert, "Stacked generalization," Neural Netw., vol. 5, no. 2, pp. 241-259, 1992.
14. S. Fine, R. Gilad-Bachrach, and E. Shamir, "Query by committee, linear separation and random walks," Theor Comput. Sci., vol. 284, no. 1, pp. 25-51, 2002.
15. Y. Freund, "Boosting a weak learning algorithm by majority," Inf. Comput., vol. 121, no. 2, pp. 256-285, 1995.
16. H. S. Seung, M. Opper, and H. Sompolinsky, Query by committee," in Proc. Comput. Learn. Theory, 1992, pp. 287-294.
17. J. Twomey and A. Smith, "Committee networks by resampling," in Intelligent Engineering Systems Through Artificial Neural Networks, vol. 5. New York: ASME Press, 1995, pp. 153-158.
18. H. Drucker, C. Cortes, L. D. Jackel, Y. LeCun, and V. Vapnik, "Boosting and other ensemble methods," Neural Comput., vol. 6, no. 6, pp. 1289-1301, 1994.
19. L. K. Hansen and P. Salamon, Neural network ensembles," IEEE Trans. Pattern Anal. Mach. Intell., vol. 12, no. 10, pp. 993-1001, Oct. 1990.
20. A. Krogh and J. Vedelsby, "Neural network ensembles, cross validation, and active learning," in Advances in Neural Information Processing Systems, vol. 7, G. Tesauro, D. Touretzky, and T. Leen, Eds. Cambridge, MA: MIT Press, 1995, pp. 231-238.
21. M. Perrone and L. N. Cooper, "When networks disagree: Ensemble method for neural networks," in Artificial Neural Networks for Speech and Vision, R. J. Mammone, Ed. New York: Chapman & Hall, 1993, pp. 126-142.
22. P. Sollich and A. Krogh, "Learning with ensembles: How over-fitting can be useful," in Advances in Neural Information Processing Systems, vol. 8. Cambridge, MA: MIT Press, 1996, pp. 190-196.
23. K. Tumer and J. Ghosh, "Error correlation and error reduction in ensemble classifiers," Connect. Sci., vol. 8, no. 3/4, pp. 385-403, 1996.
24. M. I. Jordan and R. A. Jacobs, "Hierarchical mixtures of experts and the EM algorithm," Neural Comput., vol. 6, pp. 181-214, 1994.
25. M. I. Jordan, L. Xu, and G. E. Hinton, "An alternative model for mixture of experts," in Advances in Neural Information Processing Systems. Cambridge, MA: MIT Press, 1995, pp. 633-640.
26. M. Jordan and L. Xu, "Convergence properties of the EM approach to learning in mixture-of-experts architectures," Dept. Brain and Cognitive Sci., MIT, Cambridge, MA, Tech. Rep. 9302, 1993.
27. Z. Chair and P. Varshney, "Optimal data fusion in multiple sensor detection systems," IEEE Trans. Aerosp. Electron. Syst., vol. AES-22, no. 1, pp. 98-101, Jan. 1986.
28. B. Chen and P. Varshney, "A bayesian sampling approach to decision usion using hierarchical models," IEEE Trans. Signal Process., vol. 50, no. 8, pp. 1809-1818, Aug. 2002.
29. L. Xu, A. Krzyzak, and C. Y. Suen, "Methods of combining multiple classifiers and their applications to handwriting recognition," IEEE Trans. Syst., Man, Cybern., vol. 22, no. 3, pp. 418-435, May 1992.
30. K. Woods, W. P. Kegelmeyer, Jr., and K. Bowyer, "Combination of multiple classifier using local accuracy estimates", IEEE Trans. Pattern Anal. Mach. Intell., vol. 19, no. 4, pp. 405-410, Apr. 1997.
31. C. Ji and S. Ma, "Combinations of weak classifiers," IEEE Trans. Neural Netw., vol. 8, no. 1, pp. 32-42, Jan. 1997.
32. M. Petrakos, J. A. Benediktsson, and I. Kanellopoulos, "The effect of classifier agreement on the accuracy of the combined classifier in decision level fusion," IEEE Trans. Geosci. Remote Sens., vol. 39, no. 11, pp. 2539-2546, Nov. 2001.
33. Y. Huang and C. Suen, "A method of combining multiple experts for the recognition of unconstrained handwritten numerals," IEEE Trans. Pattern Anal. Mach. Intell., vol. 17, no. 1, pp. 90-94, Jan. 1995.
34. K. W. Bowyer, K. Chang, and P. Flynn, "A survey of approaches and challenges in 3D and multi-modal 3D + 2D face recootion," Comput. Vis. Image Underst., vol. 101, no. 1, pp. 1-15, 2006.
35. J. Y. Cartoux, J. T. Lapreste, and M. Richetin, "Face authentification or recognition by profile extraction from range images," in Proc. Workshop Interpretation 3D Scenes, 1989, pp. 194-199.
36. J. C. Lee and E. Milios, "Matching range images of human faces," in Proc. 3rd Int. Conf. Comput. Vis., 1990, pp. 722-726.
37. G. G. Gordon, "Face recognition based on depth and curvature features," in Proc. IEEE Conf. CVPR, 1992, pp. 808-810.
38. H. T. Tanaka, M. Ikeda, and H. Chiaki, "Curvature-based face surface recognition using spherical correlation. Principal directions for curved object recootion," in Proc. 3rd IEEE Int. Conf. Autom. Face and Gesture Recog., 1998, pp. 372-377.
39. G. Medioni and R. Waupotitsch, "Face modeling and recognition in 3-d," in Proc. IEEE Int. Workshop Anal. and Model. Faces and Gestures, 2003, pp. 232-233.
40. C. Hesher, A. Srivastava, and G. Erlebacher, "A novel technique for face recognition using range imaging," in Proc. 7th Int. Symp. Signal Process. and Its Appl., 2003, vol. 2, pp. 201-204.
41. T. Heseltine, N. Pears, and J. Austin, "Three-dimensional face recognition: An eigensurface approach," in Proc. Int. Conf. Image Process., 2004, vol. 5, pp. 1421-1424.
42. I. A. Kakadiaris, G. Passalis, T. Theoharis, G. Toderici, I. Konstantinidis, and N. Murtuza, "Multimodal face recognition: Combination of geometry with physiological information," in Proc. IEEE Conf. CVPR, 2005, vol. 2, pp. 1022-1029.
43. K. I. Chang, K. Bowyer, and P. J. Flynn, Adaptive rigid multiregion selection for handling expression variation in 3D face recognition," in Proc. IEEE Comput. Soc. Conf. CVPR - Workshops, 2005, p. 157.
44. G. Passalis, I. A. Kakadiaris, T. Theoharis, G. Toderici, and N. Murtuza, "Evaluation of 3D face recognition in the presence of facial expressions: An annotated deformable model approach," in Proc. IEEE Comput. Soc. Conf. CVPR - Workshops, 2005, p. 171.
45. A. M. Bronstein, M. M. Bronstein, and R. Kimmel, "Three-dimensional face recognition," Int. J. Comput. Vis., vol. 64, no. 1, pp. 5-30, 2005.
46. M. P. do Carmo, Differential Geometry of Curves and Surfaces. Englewood Cliffs, NJ: Prentice-Hall, 1976.
47. M. Fels and P. J. Olver, "Moving coframes: I. A practical algorithm," Acta Appl. Math., vol. 51, no. 2, pp. 161-213, 1998.
48. M. Fels and P. J. Olver, "Moving coframes: II. Regularization and theoretical foundations," Acta Appl. Math., vol. 55, no. 2, pp. 127-208, 1999.
49. M. Faundez-Zanuy, "Data fusion in biometrics," IEEE Aerosp. Electron. Syst. Mag., vol. 20, no. 1, pp. 34-38, Jan. 2005.
50. J. J. Clark and A. L. Yuille, Data Fusion for Sensory Information Processing Systems. Norwell, MA: Kluwer, 1990.
51. L. I. Kuncheva, C. J. Whitaker, C. A. Shipp, and R. P. W. Duin, "Is independence good for combining classifiers?" Proc. ICPR, 2000, pp. 168-171.
52. P. J. Phillips, P. J. Flynn, T. Scruggs, K. W. Bowyer, J. Chang, K. Hoffman, J. Marques, J. Min, and W. Worek, "Overview of the face recognition grand challenge," in Proc. IEEE Conf. CVPR, 2005, vol. 1, pp. 947-954.
53. R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification, 2nd ed. New York: Wiley-Interscience, 2000.
54. P. N. Belhumeur, J. Hespanha, and D. J. Kriegman, "Eigenfaces vs. fisherfaces: Recognition using class specific linear projection," IEEE Trans. Pattern Anal. Mach. Intell., vol. 19, no. 7, pp. 711-720, Jul. 1997.
55. V. N. Vapnik, The Nature of Statistical Learning Theory. New York: Springer-Verlag, 1995.
56. C.-C. Chang and C.-J. Lin. (2001). LIBSVM: A Library for Support Vector Machines. [Online]. Available: http://www.csie.ntu.edu.tw/ cjlin/libsvm
57. P. Phillips, P. Flynn, T. Scruggs, K. Bowyer, and W. Worek, "Preliminary face recognition grand challenge results," in Proc. 7th Int. Conf. Autom. Face and Gesture Recog., 2006, pp. 15-24.
58. P. Sinha, B. Balas, Y. Ostrovsky, and R. Russell, "Face recognition by humans: 19 results all computer vision researchers should know about," Proc. IEEE, vol. 94, no. 11, pp. 1948-1962, 2006.
59. T. Maurer, D. Guigonis, I. Maslov, B. Pesenti, A. Tsaregorodtsev, D. West, and G. Medioni, "Performance of geometrix activeid 3D face recognition engine on the FRGC data," in Proc. IEEE Comput. Soc. Conf. CVPR - Workshops, 2005, vol. 3, p. 154.