Abstract
Several different techniques have been proposed for computer recognition of human faces. This paper presents the first results of an ongoing project to compare several recognition strategies on a common database.
A set of algorithms has been developed to assess the feasibility of recognition using a vector of geometrical features, such as nose width and length, mouth position and chin shape. The performance of a Nearest Neighbor classifier, with a suitably defined metric, is reported as a function of the number of classes to be discriminated (people to be recognized) and of the number of examples per class. Finally, performance of classification with rejection is investigated.
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References
R. J. Baron. Mechanisms of human facial recognition. International Journal of Man Machine Studies, 15:137–178, 1981.
W. W. Bledsoe. Man-machine facial recognition. Technical Report Rep. PRI:22, Panoramic Research Inc, Paolo Alto, Cal., 1966.
R. Brunelli. Edge projections for facial feature extraction. Technical Report 9009-12, I.R.S.T, 1990.
R. Brunelli, Face recognition: Dynamic programming for the detection of face outline. Technical Report 9104-06, I.R.S.T, 1991.
J. Buhmann, J. Lange, and C. von der Malsburg. Distortion invariant object recognition by matching hierarchically labeled graphs. In Proceedings of IJCNN'89, pages 151–159, 1989.
D. J. Burr. Elastic matching of line drawings. IEEE Transactions on Pattern Analysis and Machine Intelligence, 3(6):708–713, 1981.
P. J. Burt. Smart sensing within a pyramid vision machine. Proceedings of the IEEE, 76(8):1006–1015, 1988.
H. Chan and W. W. Bledsoe. A man-machine facial recognition system: some preliminary results. Technical report, Panoramic Research Inc., Cal, 1965.
G. Cottrell and M. Fleming. Face recognition using unsupervised feature extraction. In Proceedings of the International Neural Network Conference, 1990.
A. J. Goldstein, L. D. Harmon, and A. B. Lesk. Identification of human faces. In Proc. IEEE, Vol. 59, page 748, 1971.
Zi-Quan Hong. Algebraic feature extraction of image for recognition. Pattern Recognition, 24(3):211–219, 1991.
P. J. Huber. Robust Statistics. Wiley, 1981.
T. Kanade. Picture processing by computer complex and recognition of human faces. Technical report, Kyoto University, Dept. of Information Science, 1973.
Y. Kaya and K. Kobayashi. A basic study on human face recognition. In S. Watanabe, editor, Frontiers of Pattern Recognition, page 265. 1972.
Y. Lee. Handwritten digit recognition using k nearest-neighbor, radial basis functions and backpropagation neural networks. Neural Computation, 3(3), 1991.
O. Nakamura, S. Mathur, and T. Minami. Identification of human faces based on isodensity maps. Pattern Recognition, 24(3):263–272, 1991.
T. Poggio and S. Edelman. A network that learns to recognize three-dimensional objects. Nature, 343(6225):1–3, 1990.
T. Poggio and F. Girosi. A theory of networks for approximation and learning. Technical Report A.I. Memo No. 1140, Massachusetts Institute of Technology, 1989.
J. Sergent. Structural processing of faces. In A.W. Young and H.D. Ellis, editors, Handbook of Research on Face Processing. North-Holland, Amsterdam, 1989.
M. Turk and A. Pentland. Eigenfaces for recognition. Technical Report 154, MIT Media Lab Vision and Modeling Group, 1990.
H. Voorhees. Finding texture boundaries in images. Technical Report AI-TR 968, M.I.T. Artificial Intelligence Laboratory, 1987.
A. W. Young and H. D. Ellis, editors. Handbook of Research on Face Processing. NORTH-HOLLAND, 1989.
Alan L. Yuille. Deformable templates for face recognition. Journal of Cognitive Neuroscience, 3(1):59–70, 1991.
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© 1992 Springer-Verlag Berlin Heidelberg
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Brunelli, R., Poggio, T. (1992). Face recognition through geometrical features. In: Sandini, G. (eds) Computer Vision — ECCV'92. ECCV 1992. Lecture Notes in Computer Science, vol 588. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-55426-2_90
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DOI: https://doi.org/10.1007/3-540-55426-2_90
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