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An Experimental Comparison of Classifier Fusion Rules for Multimodal Personal Identity Verification Systems

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Multiple Classifier Systems (MCS 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2364))

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Abstract

In this paper, an experimental comparison between fixed and trained fusion rules for multimodal personal identity verification is reported. We focused on the behaviour of the considered fusion methods for ensembles of classifiers exhibiting significantly different performance, as this is one of the main characteristics of multimodal biometrics systems. The experiments were carried out on the XM2VTS database, using eight experts based on speech and face data. As fixed fusion methods, we considered the sum, majority voting, and order statistics based rules. The considered trained methods are the Behaviour Knowledge Space and the weighted averaging of classifiers outputs.

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Authors and Affiliations

  1. Dept. of Electrical and Electronic Eng., University of Cagliari, Piazza d’Armi, 09123, Cagliari, Italy

    Fabio Roli, Giorgio Fumera & Daniele Muntoni

  2. Centre for Vision, Speech and Signal Processing School of Electronics, Computing and Mathematics, University of Surrey, Guildford, GU2 7XH, UK

    Josef Kittler

Authors
  1. Fabio Roli
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  2. Josef Kittler
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  3. Giorgio Fumera
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  4. Daniele Muntoni
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Editor information

Editors and Affiliations

  1. Dept. of Electrical and Electronical Engineering, University of Cagliari, Piazza D’Armi, 09123, Cagliari, Italy

    Fabio Roli

  2. Centre for Vision, Speech and Signal Processing, University of Surrey, Guilford, Surrey, GUZ 7XH, UK

    Josef Kittler

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© 2002 Springer-Verlag Berlin Heidelberg

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Roli, F., Kittler, J., Fumera, G., Muntoni, D. (2002). An Experimental Comparison of Classifier Fusion Rules for Multimodal Personal Identity Verification Systems. In: Roli, F., Kittler, J. (eds) Multiple Classifier Systems. MCS 2002. Lecture Notes in Computer Science, vol 2364. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45428-4_32

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  • DOI: https://doi.org/10.1007/3-540-45428-4_32

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43818-2

  • Online ISBN: 978-3-540-45428-1

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