The task of face recognition has been actively
researched in recent years. This paper provides an up-to-date review of major human face recognition research. We first present an
overview of face recognition and its applications. Then, a literature review of the most recent face recognition techniques is presented.
Description and limitations of face databases which are used to test
the performance of these face recognition algorithms are given. A
brief summary of the face recognition vendor test (FRVT) 2002, a
large scale evaluation of automatic face recognition technology, and
its conclusions are also given. Finally, we give a summary of the research results.
[1] Francis Galton, "Personal identification and description," In Nature,pp. 173-177, June 21, 1888.
[2] W. Zaho, "Robust image based 3D face recognition," Ph.D. Thesis, Maryland University, 1999.
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[4] T. Fromherz, P. Stucki, M. Bichsel, "A survey of face recognition," MML Technical Report, No 97.01, Dept. of Computer Science,
University of Zurich, Zurich, 1997.
[5] T. Riklin-Raviv and A. Shashua, "The Quotient image: Class based
recognition and synthesis under varying illumination conditions," In CVPR, P. II: pp. 566-571,1999.
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active appearance models," In ECCV, 1998.
[7] T. Sim, R. Sukthankar, M. Mullin and S. Baluja, "Memory-based face
recognition for vistor identification," In AFGR, 2000.
[8] T. Sim and T. Kanade, "Combing models and exemplars for face
recognition: An illuminating example," In Proceeding Of Workshop on Models Versus Exemplars in Computer Vision, CUPR 2001.
[9] L. Sirovitch and M. Kirby, "Low-dimensional procedure for the characterization of human faces," Journal of the Optical Society of America A, vol. 2, pp. 519-524, 1987.
[10] M. Turk and A. Pentland "Face recognition using eigenfaces," In Proc.
IEEE Conference on Computer Vision and Pattern Recognition, pp.586-591, 1991.
[11] P. Belhumeur, P. Hespanha, and D. Kriegman, "Eigenfaces vs fisherfaces: Recognition using class specific linear projection," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19,
no. 7, pp. 711-720, 1997.
[12] M. Fleming and G. Cottrell, "Categorization of faces using unsupervised feature extraction," In Proc. IEEE IJCNN International
Joint Conference on Neural Networks, pp. 65-70, 1990.
[13] B. Moghaddam, W. Wahid, and A. Pentland, "Beyond eigenfaces:
Probabilistic matching for face recognition," In Proc. IEEE
International Conference on Automatic Face and Gesture Recognition, pp. 30-35,1998.
[14] A. Lanitis, C. Taylor, and T. Cootes, "Automatic interpretation and
coding of face images using flexible models," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 743 -756, 1997.
[15] K. Jonsson, J. Matas, J. Kittler, and Y. Li, "Learning support vectors for face verification and recognition," In Proc. IEEE International
Conference on Automatic Face and Gesture recognition, pp. 208-213,
2000.
[16] R. Brunelli and T. Poggio, "Face recognition: Features versus
templates," IEEE Transactions on Pattern Analysis and Machine
Intelligence, vol. 15, no. 10, pp. 1042-1052, 1993.
[17] D. J. Beymer, "Face recognition under varying pose," A.I. Memo 1461,
Center for Biological and Computational Learning, M.I.T., Cambridge,
MA, 1993.
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recognition by elastic bunch graph matching," IEEE Transactions on
Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 775 -779, 1997.
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detection and recognition," In Proc. IEEE International Conference on
Acoustics, Speech, and Signal Processing, vol. 6, pp. 3553-3556,1999.
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http://www.dodcounterdrug.com/facialrecognition/FRVT2000/frvt2000.htm.
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shape-from-hading," Technical Report CARTR -919, 1999., Center for
Automation Research, University of Maryland, College Park, MD,1999.
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active appearance models," In ECCV, 1998.
[24] A.S. Georghiades, P.N. Belhumeur, and D.J. Kriegman, "From few to
many: Generative models for recognition under variable pose and illumination," In AFGR, 2000.
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characterisation of human faces," J. Optical Soc. of Am., vol. 4, pp. 519-524, 1987.
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Pattern Analysis and Machine Intelligence, vol. 12, pp. 831-835, Dec.1990.
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[29] M.A. Grudin, "A compact multi-level model for the recognition of facial images," Ph.D. thesis, Liverpool John Moores Univ., 1997.
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vision systems," Pattern Recognition, vol. 32, pp. 547-564,1999.
[31] A. Pentland, B. Moghaddam, and T. Starner, "View-Based and
modular eigenspaces for face recognition," Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, pp. 84-91, 1994.
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of ear and face images in appearance-based biometrics," IEEE Trans.
On Pattern analysis and machine intelligence, vol. 25, no. 9,September 2003.
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identification," IEEE Trans. Pattern Analysis and Machine
Intelligence, vol. 20, no. 12, pp. 1295-1307, Dec. 1998.
World Academy of Science, Engineering and Technology 19 2008
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scenes," Computer Analysis of Image and patterns, pp. 432-439, 1995.
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A convolutional neural-network approach," IEEE Trans. Neural Networks, vol. 8, pp. 98-113, 1997.
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segmentation of 3D objects from 2D images," Proc. IEEE Int'l Conf. Computer Vision, pp. 121-128, 1993.
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for human face identification," Proc. Second IEEE Workshop
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[1] Francis Galton, "Personal identification and description," In Nature,pp. 173-177, June 21, 1888.
[2] W. Zaho, "Robust image based 3D face recognition," Ph.D. Thesis, Maryland University, 1999.
[3] R. Chellappa, C.L. Wilson and C. Sirohey, "Humain and machine recognition of faces: A survey," Proc. IEEE, vol. 83, no. 5, pp. 705-740, may1995.
[4] T. Fromherz, P. Stucki, M. Bichsel, "A survey of face recognition," MML Technical Report, No 97.01, Dept. of Computer Science,
University of Zurich, Zurich, 1997.
[5] T. Riklin-Raviv and A. Shashua, "The Quotient image: Class based
recognition and synthesis under varying illumination conditions," In CVPR, P. II: pp. 566-571,1999.
[6] G.j. Edwards, T.f. Cootes and C.J. Taylor, "Face recognition using
active appearance models," In ECCV, 1998.
[7] T. Sim, R. Sukthankar, M. Mullin and S. Baluja, "Memory-based face
recognition for vistor identification," In AFGR, 2000.
[8] T. Sim and T. Kanade, "Combing models and exemplars for face
recognition: An illuminating example," In Proceeding Of Workshop on Models Versus Exemplars in Computer Vision, CUPR 2001.
[9] L. Sirovitch and M. Kirby, "Low-dimensional procedure for the characterization of human faces," Journal of the Optical Society of America A, vol. 2, pp. 519-524, 1987.
[10] M. Turk and A. Pentland "Face recognition using eigenfaces," In Proc.
IEEE Conference on Computer Vision and Pattern Recognition, pp.586-591, 1991.
[11] P. Belhumeur, P. Hespanha, and D. Kriegman, "Eigenfaces vs fisherfaces: Recognition using class specific linear projection," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19,
no. 7, pp. 711-720, 1997.
[12] M. Fleming and G. Cottrell, "Categorization of faces using unsupervised feature extraction," In Proc. IEEE IJCNN International
Joint Conference on Neural Networks, pp. 65-70, 1990.
[13] B. Moghaddam, W. Wahid, and A. Pentland, "Beyond eigenfaces:
Probabilistic matching for face recognition," In Proc. IEEE
International Conference on Automatic Face and Gesture Recognition, pp. 30-35,1998.
[14] A. Lanitis, C. Taylor, and T. Cootes, "Automatic interpretation and
coding of face images using flexible models," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 743 -756, 1997.
[15] K. Jonsson, J. Matas, J. Kittler, and Y. Li, "Learning support vectors for face verification and recognition," In Proc. IEEE International
Conference on Automatic Face and Gesture recognition, pp. 208-213,
2000.
[16] R. Brunelli and T. Poggio, "Face recognition: Features versus
templates," IEEE Transactions on Pattern Analysis and Machine
Intelligence, vol. 15, no. 10, pp. 1042-1052, 1993.
[17] D. J. Beymer, "Face recognition under varying pose," A.I. Memo 1461,
Center for Biological and Computational Learning, M.I.T., Cambridge,
MA, 1993.
[18] L. Wiskott, J.-M. Fellous, N. Kruger, and C. von der Malsburg, "Face
recognition by elastic bunch graph matching," IEEE Transactions on
Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 775 -779, 1997.
[19] A. Nefian and M. Hayes, " An embedded hmm-based approach for face
detection and recognition," In Proc. IEEE International Conference on
Acoustics, Speech, and Signal Processing, vol. 6, pp. 3553-3556,1999.
[20] U.S. Department of Defense, "Facial Recognition Vendor Test, 2000,"Available:
http://www.dodcounterdrug.com/facialrecognition/FRVT2000/frvt2000.htm.
[21] W. Zhao and R. Chellappa, " Robust face recognition using symmetric
shape-from-hading," Technical Report CARTR -919, 1999., Center for
Automation Research, University of Maryland, College Park, MD,1999.
[22] L. Zheng, "A new model-based lighting normalization algorithm and its application in face recognition," Master-s thesis, National University of Singapore, 2000.
[23] G.J. Edwards, T.F. Cootes, and C.J. Taylor, "Face recognition using
active appearance models," In ECCV, 1998.
[24] A.S. Georghiades, P.N. Belhumeur, and D.J. Kriegman, "From few to
many: Generative models for recognition under variable pose and illumination," In AFGR, 2000.
[25] D.B. Graham and N.M., "Allinson face recognition from unfamiliar views: Subspace methods and pose dependency," In AFGR, 1998.
[26] L. Sirovich and M. Kirby, "Low-Dimensional procedure for the
characterisation of human faces," J. Optical Soc. of Am., vol. 4, pp. 519-524, 1987.
[27] M. Kirby and L. Sirovich, "Application of the Karhunen- Loève procedure for the characterisation of human faces," IEEE Trans.
Pattern Analysis and Machine Intelligence, vol. 12, pp. 831-835, Dec.1990.
[28] M. Turk and A. Pentland, "Eigenfaces for recognition," J. Cognitive Neuroscience, vol. 3, pp. 71-86, 1991.
[29] M.A. Grudin, "A compact multi-level model for the recognition of facial images," Ph.D. thesis, Liverpool John Moores Univ., 1997.
[30] L. Zhao and Y.H. Yang, "Theoretical analysis of illumination in pcabased
vision systems," Pattern Recognition, vol. 32, pp. 547-564,1999.
[31] A. Pentland, B. Moghaddam, and T. Starner, "View-Based and
modular eigenspaces for face recognition," Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, pp. 84-91, 1994.
[32] K. Chang, K.W. Bowyer and S. Sarkar, "Comarison and combination
of ear and face images in appearance-based biometrics," IEEE Trans.
On Pattern analysis and machine intelligence, vol. 25, no. 9,September 2003.
[33] L. Hong and A. Jain, "Integrating faces and fingerprints for personal
identification," IEEE Trans. Pattern Analysis and Machine
Intelligence, vol. 20, no. 12, pp. 1295-1307, Dec. 1998.
World Academy of Science, Engineering and Technology 19 2008
[34] P. Verlinde, G. Matre, and E. Mayoraz, "Decision fusion using a multilinear
classifier," Proc. Int-l Conf. Multisource-Multisensor
Information Fusion, vol. 1, pp. 47-53, July 1998.
[35] T.J. Stonham, "Practical face recognition and verification with
WISARD," Aspects of Face Processing, pp. 426-441, 1984.
[36] K.K. Sung and T. Poggio, "Learning human face detection in cluttered
scenes," Computer Analysis of Image and patterns, pp. 432-439, 1995.
[37] S. Lawrence, C.L. Giles, A.C. Tsoi, and A.D. Back, "Face recognition:
A convolutional neural-network approach," IEEE Trans. Neural Networks, vol. 8, pp. 98-113, 1997.
[38] J. Weng, J.S. Huang, and N. Ahuja, "Learning recognition and
segmentation of 3D objects from 2D images," Proc. IEEE Int'l Conf. Computer Vision, pp. 121-128, 1993.
[39] S.H. Lin, S.Y. Kung, and L.J. Lin, "Face recognition/detection by
probabilistic decision-based neural network," IEEE Trans. Neural Networks, vol. 8, pp. 114-132, 1997.
[40] S.Y. Kung and J.S. Taur, "Decision-Based neural networks with signal/image classification applications," IEEE Trans. Neural
Networks, vol. 6, pp. 170-181, 1995.
[41] M. Lades, J.C. Vorbruggen, J. Buhmann, J. Lange, C. Von Der
Malsburg, R.P. Wurtz, and M. Konen, "Distortion Invariant object recognition in the dynamic link architecture," IEEE Trans. Computers,
vol. 42, pp. 300-311, 1993.
[42] L. Wiskott and C. von der Malsburg, "Recognizing faces by dynamic link matching," Neuroimage, vol. 4, pp. 514-518, 1996.
[43] F. Samaria and F. Fallside, "Face identification and feature extraction
using hidden markov models," Image Processing: Theory andm Application, G. Vernazza, ed., Elsevier, 1993.
[44] F. Samaria and A.C. Harter, "Parameterisation of a stochastic model
for human face identification," Proc. Second IEEE Workshop
Applications of Computer Vision, 1994.
[45] S. Tamura, H. Kawa, and H. Mitsumoto, "Male/Female identification from 8_6 very low resolution face images by neural network," Pattern
Recognition, vol. 29, pp. 331-335, 1996.
[46] T. Kanade, "Picture processing by computer complex and recognition
of human faces," technical report, Dept. Information Science, Kyoto
Univ., 1973.
[47] A.J. Goldstein, L.D. Harmon, and A.B. Lesk, "Identification of human
faces," Proc. IEEE, vol. 59, pp. 748, 1971.
[48] Y. Kaya and K. Kobayashi, "A basic study on human face recognition," Frontiers of Pattern Recognition, S. Watanabe, ed., pp. 265, 1972.
[49] R. Bruneli and T. Poggio, "Face recognition: features versus templates," IEEE Trans. Pattern Analysis and Machine Intelligence,
vol. 15, pp. 1042-1052, 1993.
[50] I.J. Cox, J. Ghosn, and P.N. Yianios, "Feature-Based face recognition
using mixture-distance," Computer Vision and Pattern Recognition,
1996.
[51] B.S. Manjunath, R. Chellappa, and C. von der Malsburg, "A Feature
based approach to face recognition," Proc. IEEE CS Conf. Computer
Vision and Pattern Recognition, pp. 373-378, 1992.
[52] R.J. Baron, "Mechanism of human facial recognition," Int'l J. Man Machine Studies, vol. 15, pp. 137-178, 1981.
[53] M. Bichsel, "Strategies of robust object recognition for identification of human faces," Ph.D. thesis, idgenossischen Technischen
Hochschule, Zurich, 1991.
[54] T. Vetter and T. Poggio, "Linear object classes and image synthesis
from a single example image," IEEE Trans. Pattern Analysis and Machin Intelligence, Vol. 19, no. 7, pp. 733-742, July 1997.
[55] D. Beymer and T. Poggio, "Face recognition from one model view,"
Proc. Fifth Int-l Conf. Computer Vision, 1995.
[56] T. Vetter and V. Blanz, "Estimating coloured 3D face models fromfingle images: An example based approach," Proc. Conf. Computer
Vision (ECCV -98), vol. II, 1998.
[57] A.S. Georghiades, P.N. Belhumeur, and D.J. Kriegman, "From few to
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@article{"International Journal of Information, Control and Computer Sciences:56992", author = "A. S. Tolba and A.H. El-Baz and A.A. El-Harby", title = "Face Recognition: A Literature Review", abstract = "The task of face recognition has been actively
researched in recent years. This paper provides an up-to-date review of major human face recognition research. We first present an
overview of face recognition and its applications. Then, a literature review of the most recent face recognition techniques is presented.
Description and limitations of face databases which are used to test
the performance of these face recognition algorithms are given. A
brief summary of the face recognition vendor test (FRVT) 2002, a
large scale evaluation of automatic face recognition technology, and
its conclusions are also given. Finally, we give a summary of the research results.", keywords = "Combined classifiers, face recognition, graph matching, neural networks.", volume = "2", number = "7", pages = "2427-16", }
