Fusion of classifiers for illumination robust face recognition

Expert Systems with Applications

Volumn 36, Issue 5, 2009, Pages 8946-8954

  Franco, Annalisa ^a   Nanni, Loris ^a  

^a UNIVERSITY OF BOLOGNA   (Italy)

Author keywords

Face recognition; Fusion of classifiers; Illumination conditions

Indexed keywords

CLASSIFIERS; LEARNING SYSTEMS;

FACE DATABASE; FUSION OF CLASSIFIERS; ILLUMINATION CONDITIONS; ROBUST RECOGNITION; VARIABLE ILLUMINATIONS;

FACE RECOGNITION;

EID: 60849137466     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2008.11.006     Document Type: Article

References (50)

1. Adini Y., Moses Y., and Ullman S. Face recognition: The problem of compensating for changes in illumination direction. IEEE Transactions on Pattern Analysis and Machine Intelligence 19 (1997) 721-732
2. Arandjelovic, O., & Cipolla, R. (2006). A new look at filtering techniques for illumination invariance in automatic face recognition. In Proceedings of IEEE conference on automatic face ad gesture recognition (pp. 449-454).
3. Atick J., Griffin P., and Redlich N. Statistical approach to shape from shading: Reconstruction of three-dimensional face surfaces from single two-dimensional images. Neural Computation 8 (1996) 1321-1340
4. Bartlett, M. S., & Sejnowski, T. J. (1997). Independent components of face images: A representation for face recognition. In Proceedings of the fourth annual joint symposium on neural computation.
5. Basri, R., & Jacobs, D. (2001). Lambertian reflectance and linear subspaces. In Proceedings of international conference on computer vision (Vol. 2, pp. 383-390).
6. Batur A.U., and Hayes III M.H. Segmented linear subspaces for illumination-robust face recognition. International Journal of Computer Vision 57 1 (2004) 49-66
7. Belhumeur, P. N., & Kriegman, D. J. (1997). What is the set of images of an object under all possible lighting conditions? In Proceedings, IEEE conference on computer vision and pattern recognition (pp. 52-58).
8. Belhumeur P.N., Hespanha J.P., and Kriegman D.J. Eigenfaces vs. fisherfaces: Recognition using class specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence (1997) 711-720
9. Belhumeur P.N., Hespanha J.P., and Kriegman D.J. Eigenfaces vs. fisherfaces: Recognition using class specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence 19 (1997) 711-720
10. Blackburn, D. M., Bone, J. M., & Phillips, P. J. (2001). FRVT 2000 Evaluation Report .
11. Blanz V., and Vetter T. Face recognition based on fitting a 3D morphable model. IEEE Transactions on Pattern Analysis and Machine Intelligence 25 9 (2003) 1-11
12. Cappelli, R., Maio, D., & Maltoni, D. (2002). Subspace classification for face recognition. In Proceedings of workshop on biometric authentication - ECCV'02 (BIOW2002) (pp. 133-141).
13. Chen W., Er M.J., and Wu S. Illumination compensation and normalization for robust face recognition using discrete cosine transform in logarithm domain. IEEE Transactions on Systems, Man and Cybernetics - Part B: Cybernetics 36 2 (2006) 458-466
14. Chen, T., Yin, W., Zhou, X. S., Comaniciu, D., & Huang, T. S. (2005). Illumination normalization for face recognition and uneven background correction using total variation based image models. In: Proceedings of international conference on computer vision and pattern recognition (Vol. 2, pp. 532-539).
15. Chen T., Yin W., Zhou X., Comaniciu D., and Huang T. Total variation models for variable lighting face recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 28 9 (2006) 1519-1524
16. Connie T., Jin A.T.B., Ong M.G.K., and Ling D.N.C. An automated palmprint recognition system. Image and Vision Computing 23 (2005) 501-515
17. Du, S., & Ward, R. (2005). Wavelet based illumination normalization for face recognition. In Proceedings of international conference on image processing (Vol. 2, pp. 954-957).
18. Fenga G., Hua D., Zhang D., and Zhou Z. An alternative formulation of Kernel LPP with application to image recognition. NeuroComputing 69 (2006) 1733-1738
19. Georghiades, A. S., Kriegman, D. J., & Belhumeur, P. N. (1998). Illumination cones for recognition under variable lighting: Faces. In Proceedings, IEEE conference on computer vision and pattern recognition (pp. 52-58).
20. Georghiades A., Kriegman D., and Belhumeur P. From few to many: Generative models for recognition under variable pose and illumination. IEEE Transactions Pattern Analysis and Machine Intelligence 40 (2001) 643-660
21. 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
22. Hallinan, P. (1994). A low-dimensional representation of human faces for arbitrary lighting conditions. In Proceedings, IEEE conference on computer vision and pattern recognition (pp. 995-999).
23. He X., Yan S., Hu Y., Niyogi P., and Zhang H.-J. Face recognition using Laplacianfaces. IEEE Transactions on Pattern Analysis and Machine Intelligence 27 3 (2005) 328-340
24. Jacobs, D. W., Belhumeur, P. N., & Barsi, R. (1998). Comparing images under variable illumination. In Proceedings, IEEE conference on computer vision and pattern recognition (pp. 610-617).
25. Lee, K. C., Ho, J., & Kriegman, D., (2001). Nine points of lights: Acquiring subspaces for face recognition under variable illumination. In Proceedings of the international conference on computer vision and pattern recognition (Vol. 1, pp. 519-526).
26. Lee K.C., 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
27. Levoy, M., & Hanrahan, M. (1996). Light field rendering. In Proceedings of computer graphics annual conference series (pp. 31-41).
28. Liu D.H., Shen L.S., Lam K.M., and Kong X. Illumination invariant face recognition. Pattern Recognition 38 (2005) 1705-1716
29. Maio D., Maltoni D., Jain A.K., and Prabhakar S. Handbook of fingerprint recognition (2003), Springer, New York
30. Manjunath, B., Chellappa, R., & Von der Malsburg, C. (1992). A feature based approach to face recognition. In Proceedings of IEEE conference on computer vision and pattern recognition (pp. 373-378).
31. Murase H., and Nayar S. Visual learning and recognition of 3D objects from appearances. International Journal of Computer Vision 14 (1995) 5-25
32. Nanni L., and Lumini A. Region boost learning for 2D + 3D based face recognition. Pattern Recognition Letters 28 15 (2007) 2063-2070
33. Nanni L., and Lumini A. Wavelet decomposition tree selection for palm and face authentication. Pattern Recognition Letters 29 3 (2008) 343-353
34. Nanni L., and Maio D. Weighted sub-Gabor for face recognition. Pattern Recognition Letters 28 4 (2007) 487-492
35. Ojala T., Pietikainen M., and Harwood D. A comparative study of texture measures with classification based on feature distributions. Pattern Recognition 29 (1996)
36. Ojala T., Pietikainen M., and Maenpaa T. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence 24 7 (2002) 971-987
37. ORL database of faces, .
38. Phillips, P. J., Grother, P., Micheals, R. J., Blackburn, D. M., Tabassi, E., & Bone, J. M. (2003). Face Recognition Vendor Test 2002 Evaluation Report, NISTIR 6965. .
39. Qing, L., Shan, S., & Gao, W. (2004). Eigen-harmonic faces: Face recognition under generic lighting. In Proceedings of international conference on automatic face and gesture recognition (pp. 296-301).
40. Qing L., Shan S., Gao W., and Du B. Face recognition under generic illumination based on harmonic relighting. International Journal of Pattern Recognition and Artificial Intelligence 19 4 (2005) 513-531
41. Savvides, M., Kumar, B. V., & Khosla, P. K. (2004). Corefaces - robust shift invariant PCA based correlation filter for illumination tolerant face recognition. In Proceedings of the international conference on computer vision and pattern recognition (Vol. 2, pp. 834-841).
42. Shashua, A. (1994). Geometry and Photometry in 3D Visual Recognition, PhD Thesis, MIT.
43. Tan, X., & Triggs, B. (2007). Enhanced local texture feature sets for face recognition under difficult lighting conditions. In Proceedings of the IEEE international workshop on analysis and modeling of faces and gestures (pp. 168-182).
44. Wang, H., Li, S. Z., & Wang, Y. (2004). Face recognition under varying lighting conditions using self quotient image. In Proceedings of the IEEE international conference on automatic face and gesture recognition (pp. 819-824).
45. Yale Face Database B, .
46. Zhang, L., & Samaras, D. (2004). Pose invariant face recognition under arbitrary unknown lighting using spherical harmonics. In Proceedings of biometric authentication workshop (pp. 10-23).
47. Zhang, W., Shan, S., Chen, X., & Gao, W. (2006). Are Gabor phases really useless for face recognition? In Proceedings of international conference on pattern recognition (Vol. 4, pp. 606-609).
48. Zhao, W. (1999). Improving the robustness of face recognition. In Proceedings of second international conference on audio- and video-based person authentication, Washington, DC (pp. 78-83).
49. Zhao, W. (1999). Robust image based 3D face recognition. PhD Thesis. University of Maryland.
50. Zhao, W., & Chellappa, R. (1999). Robust face recognition using symmetric shape-from-shading. Technical Report CAR-TR-919. Center for Automation Research, University of Maryland.