Abstract
3-dimensional pattern recognition requires the definition of a similarity measure between 3-dimensional patterns. We discuss how to match 3-dimensional patterns, which are represented by a set of images taken from multiple directions and approximately represented by subspaces. The proposed method is to calculate the canonical angles, in particular the third smallest angle between two subspaces. We demonstrate the viability of the proposed method by performing a pilot study of face recognition.
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References
Murase, H., Nayar, S.K.: Illumination planning for object recognition in structured environments. In: Proc. of CVPR, pp. 31–38 (1994)
Oja, E.: Subspace Method of Pattern Recognition. Research Studies Press, Hertfordshire (1983)
Maeda, K., Watanabe, S.: A Pattern Matching Method with Local Structure. Trans. IECE J68-D 3, 345–352 (1984) (in Japanese)
Yamaguchi, O., Fukui, K., Maeda, K.: Face Recognition Using Temporal Image Sequence. In: Proc. of FG 1998, pp. 318–323 (1998)
Oja, E., Parkkinen, J.: On Subspace Clustering. In: Proc. of 7th ICPR, pp. 692–695 (1984)
Riittinen, H.: Short-cut Algorithms for the Learning Subspace Method. In: Proc. of ICASSP 1984 ,pp.17.2.1–17.2.4 (1984)
Dixmier, M.: Etude sur les Varietes et les Operaterns de Julia, avec Quelques Applications. Bull. Soc. Math. France 77, 11–101 (1949)
Björck, Å., Golub, G.H.: Numerical Methods for Computing Angles between Linear Subspaces. Mathematics of Computation 27, 579–594 (1975)
Chatelin, F.: Valeurs Propres de Matrices, Masson (1988)
Fukui, K., Yamaguchi, O.: Face Recognition Using Multi-viewpoint Patterns for Robot Vision. In: Proc. of ISRR 2003 (2003)
Epstein, R., et al.: 5 ± 2 Eigenimages Suffice: An Empirical Investigation of Low- Dimensional Lighting Models. In: Proc. of IEEE Workshop on Physics-based Modeling in CV, pp. 108–116 (1995)
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Maeda, Ki., Yamaguchi, O., Fukui, K. (2004). Towards 3-Dimensional Pattern Recognition. In: Fred, A., Caelli, T.M., Duin, R.P.W., Campilho, A.C., de Ridder, D. (eds) Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2004. Lecture Notes in Computer Science, vol 3138. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27868-9_117
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DOI: https://doi.org/10.1007/978-3-540-27868-9_117
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22570-6
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