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Comparison of Statistical Classifiers as Applied to the Face Recognition System Based on Active Shape Models

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Computer Recognition Systems

Part of the book series: Advances in Soft Computing ((AINSC,volume 30))

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Abstract

In this paper, a face recognition algorithm based on statistical model of Active Shape (ASM) is presented. A 31 degree-of-freedom shape model was used. The model was derived from a set of 183 faces shapes and named the learning set. Criteria of selection of face to model classifiers were evaluated. Classification was implemented in the shape space, in its Principal Component Analysis (PCA) and Multiple Discriminant Analysis (MDA) transformations. In the shape space the Euclidean and Mahalanobis metrics were used. Euclidean metric was used in PCA and MDA spaces as well. The results were based on experiments carried out on the set of 651 images of eight persons. Further proceedings in the case of ambiguous classification results were suggested.

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© 2005 Springer-Verlag Berlin Heidelberg

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Krol, M., Florek, A. (2005). Comparison of Statistical Classifiers as Applied to the Face Recognition System Based on Active Shape Models. In: Kurzyński, M., Puchała, E., Woźniak, M., żołnierek, A. (eds) Computer Recognition Systems. Advances in Soft Computing, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32390-2_93

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  • DOI: https://doi.org/10.1007/3-540-32390-2_93

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25054-8

  • Online ISBN: 978-3-540-32390-7

  • eBook Packages: EngineeringEngineering (R0)

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