Abstract
This paper demonstrates how the EM algorithm can be used for learning and matching mixtures of point distribution models. We make two contributions. First, we show how to shape-classes can be learned in an unsupervised manner. Second, we show how recognition by alignment can be realised by fitting a mixture of linear shape deformations. We evaluate the method on the problem of learning class-structure and recognising Arabic characters.
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© 2002 Springer-Verlag Berlin Heidelberg
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Al-Shaher, A.A., Hancock, E.R. (2002). Linear Shape Recognition with Mixtures of Point Distribution Models. In: Caelli, T., Amin, A., Duin, R.P.W., de Ridder, D., Kamel, M. (eds) Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2002. Lecture Notes in Computer Science, vol 2396. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-70659-3_21
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DOI: https://doi.org/10.1007/3-540-70659-3_21
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