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Expert conciliation for multi modal person authentication systems by Bayesian statistics

  • Audio-video Features and Fusion
  • Conference paper
  • First Online:
Audio- and Video-based Biometric Person Authentication (AVBPA 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1206))

Abstract

We present an algorithm functioning as a supervisor module in a multi expert decision making machine. It uses the Bayes theory in order to estimate the biases of individual expert opinions. These are then used to calibrate and conciliate expert opinions to one opinion. We present a framework for simulating decision strategies using expert opinions whose properties are easily modifiable. By using real data coming from a person authentication system using image and speech data we were able to confirm that the proposed supervisor improves the quality of individual expert decisions by reaching success rates of 99.5 %.

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Author information

Authors and Affiliations

  1. Dep. of Statistics, Stockholm University, S-106 91, Stockholm

    E. S. Bigün

  2. EPFL Signal Processing Laboratory, CH-1015, Lausanne

    J. Bigün, B. Duc & S. Fischer

  3. KTH Center for Safety Research, S-100 44, Stockholm

    E. S. Bigün

Authors
  1. E. S. Bigün
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  2. J. Bigün
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  3. B. Duc
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  4. S. Fischer
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Editor information

Josef Bigün Gérard Chollet Gunilla Borgefors

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© 1997 Springer-Verlag Berlin Heidelberg

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Bigün, E.S., Bigün, J., Duc, B., Fischer, S. (1997). Expert conciliation for multi modal person authentication systems by Bayesian statistics. In: Bigün, J., Chollet, G., Borgefors, G. (eds) Audio- and Video-based Biometric Person Authentication. AVBPA 1997. Lecture Notes in Computer Science, vol 1206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0016008

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  • DOI: https://doi.org/10.1007/BFb0016008

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-62660-2

  • Online ISBN: 978-3-540-68425-1

  • eBook Packages: Springer Book Archive

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