Abstract
This paper describes a novel face recognition method, the orthoface method. The method is efficient and invariant to variation in lighting conditions, facial expressions and alien objects. At the centre of the orthoface method is a set of basis vectors named the orthofaces. Orthofaces are more effective basis vectors from a discrimination viewpoint because each of them accounts for the individual features of a training face. We will explain the logic behind the orthoface method. We will also justify with both mathematical reasoning and experimental results why the orthoface method is the method that leads to effective classification strategies.
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References
Anil K. Jain, Robert P.W. Duin, and Jianchang Mao, Statistical Pattern Recognition: A Review, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22, No1, January 2000.
Belhumeur P., Hespanhu J. and Kriegman D., Eigen Faces vs. Fisherfaces: Recognition Using Class Specific Linear Projection, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 19, July 1997.
Chellappa, R, Wilson, C., and Sirohey, S., Human and Maachine Recognition of Faces: A Survey, Proceedings of IEEE, Vol 83, No.5, 1995.
Jolliffe, I.T., Principal Component Analysis. Springer-Verlag; New York; 1986.
Pentland, A., Moghaddam, B., and Stamer T.. View-Based and Modular Eigenspaces for Face Recognition. IEEE Conference on Computer Vision & Pattern Recognition, 1994
Turk, M. & Pentland, A., Eigenfaces for recognition, Journal of Cognitive Neuroscience, 3(1), 1991.
Turk, M. & Pentland, A., Face recognition using eigenfaces, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June Maui, Hawaii, 1991.
Welsh, J. W., and Shah. D., Facial-Feature Image Coding Using Principal Components, Electronic Letters. Vol. 28, October, 1992.
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© 2001 Springer-Verlag London
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Li, B., Siang, V.P. (2001). Orthofaces for Face Recognition. In: Bramer, M., Preece, A., Coenen, F. (eds) Research and Development in Intelligent Systems XVII. Springer, London. https://doi.org/10.1007/978-1-4471-0269-4_19
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DOI: https://doi.org/10.1007/978-1-4471-0269-4_19
Publisher Name: Springer, London
Print ISBN: 978-1-85233-403-1
Online ISBN: 978-1-4471-0269-4
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