Two-step calibration method for multi-algorithm score-based face recognition systems by minimizing discrimination loss

N. Susyanto, Raymond N.J. Veldhuis, Lieuwe Jan Spreeuwers, C.A.J. Klaassen

    Research output: Contribution to conferencePaperpeer-review

    3 Citations (Scopus)


    We propose a new method for combining multi-algorithm score-based face recognition systems, which we call the two-step calibration method. Typically, algorithms for face recognition systems produce dependent scores. The two-step method is based on parametric copulas to handle this dependence. Its goal is to minimize discrimination loss. For synthetic and real databases (NIST-face and Face3D) we will show that our method is accurate and reliable using the cost of log likelihood ratio and the information-theoretical empirical cross-entropy (ECE).
    Original languageUndefined
    Number of pages7
    Publication statusPublished - 13 Jun 2016
    Event9th IAPR International Conference on Biometrics, ICB 2016 - Halmstad, Sweden
    Duration: 13 Jun 201616 Jun 2016
    Conference number: 9


    Conference9th IAPR International Conference on Biometrics, ICB 2016
    Abbreviated titleICB
    Internet address


    • discrimination loss
    • log likelihood ratio
    • two-step calibration method
    • EWI-27634
    • information-theoretical empirical cross-entropy
    • IR-104050
    • Face Recognition
    • multialgorithm score
    • SCS-Safety

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