Expert Conciliation for Multi Modal Person Authentication Systems by Bayesian Statistics

نویسندگان

  • Elizabeth Saers Bigün
  • Josef Bigün
  • Benoît Duc
  • Stefan Fischer
چکیده

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 modiiable. By using real data coming from a person authentication system using image and speech data we were able to connrm that the proposed supervisor improves the quality of individual expert decisions by reaching success rates of 99.5 %.

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تاریخ انتشار 1997