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Face Class Modeling Using Mixture of SVMs

  • Conference paper
Image Analysis and Recognition (ICIAR 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3212))

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Abstract

We present a method for face detection which uses a new SVM structure trained in an expert manner in the eigenface space. This robust method has been introduced as a post processing step in a real-time face detection system. The principle is to train several parallel SVMs on subsets of some initial training set and then train a second layer SVM on the margins of the first layer of SVMs. This approach presents a number of advantages over the classical SVM: firstly the training time is considerably reduced and secondly the classification performance is improved, we will present some comparisions with the single SVM approach for the case of human face class modeling.

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© 2004 Springer-Verlag Berlin Heidelberg

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Meynet, J., Popovici, V., Thiran, JP. (2004). Face Class Modeling Using Mixture of SVMs. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30126-4_86

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  • DOI: https://doi.org/10.1007/978-3-540-30126-4_86

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23240-7

  • Online ISBN: 978-3-540-30126-4

  • eBook Packages: Springer Book Archive

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