Abstract
A face recognition technique based on symbolic PCA approach is presented in this paper. The proposed method transforms the face images by extracting knowledge from training samples into symbolic objects, termed as symbolic faces. Symbolic PCA is employed to compute a set of subspace basis vectors for symbolic faces and then to project the symbolic faces into the compressed subspace. New test images are then matched with the images in the database by projecting them onto the basis vectors and finding the nearest symbolic face in the subspace. The feasibility of the new symbolic PCA method has been successfully tested for face recognition using ORL database. As compared to eigenface method, the proposed method requires less number of features to achieve the same recognition rate.
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References
Bock, H.H., Diday, E. (eds.): Analysis of Symbolic Data. Springer, Heidelberg (2000)
Choukria, A., Diday, E., Cazes, P.: Extension of the principal component analysis to interval data. In: NTTS 1995: New Techniques and Technologies for statistics, Bonn (1995)
Ichino, Y.: Generalized Minkowski metrics for mixed feature type data analysis. IEEE Trans. Systems Man Cybernet. (4), 698–708 (1994)
Jain, D.: Algorithms for clustering data. Prentice-Hall, Englewood Cliffs (1998)
Kirby, S.: Applications of the Karhunen–Loeve procedure for the characterization of human faces. IEEE Trans. Pattern Anal. Machine Intell. 12(1), 103–108 (1990)
Nagabhushan, P., Gowda, K.C., Diday, E.: Dimensionality reduction of symbolic data. Pattern Recognition Letters 16, 219–223 (1995)
Sudhanva, G.: Dimensionality reduction using geometric projection: a new technique. Pattern Recognition 5(8) (1995)
Turk, P.: Eigenfaces for Recognation. J. Cognitive Neuro Science, 71–86 (1991)
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© 2005 Springer-Verlag Berlin Heidelberg
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Hiremath, P.S., Prabhakar, C.J. (2005). Face Recognition Technique Using Symbolic PCA Method. In: Pal, S.K., Bandyopadhyay, S., Biswas, S. (eds) Pattern Recognition and Machine Intelligence. PReMI 2005. Lecture Notes in Computer Science, vol 3776. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11590316_37
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DOI: https://doi.org/10.1007/11590316_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30506-4
Online ISBN: 978-3-540-32420-1
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