%Aigaion2 BibTeX export from Idiap Publications
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@TECHREPORT{I.Mantasari_Idiap-RR-01-2014,
         author = {I. Mantasari, Miranti and G{\"{u}}nther, Manuel and Wallace, Roy and Saedi, Rahim and Marcel, S{\'{e}}bastien and Van Leeuwen, David},
       keywords = {calibration, forensic face recognition, likelihood ratio, linear score transformation.},
       projects = {BBfor2},
          month = {1},
          title = {Score Calibration in Face Recognition},
           type = {Idiap-RR},
         number = {Idiap-RR-01-2014},
           year = {2014},
    institution = {Idiap},
       abstract = {This paper presents an evaluation of verification and calibration performance of a face recognition system based on inter-session variability modeling. As an extension to the calibration through
linear transformation of scores, categorical calibration is introduced as a way to include additional
information of images to calibration. The cost of likelihood ratio, which is a well-known measure in
the speaker recognition field, is used as a calibration performance metric. Evaluated on the challenging MOBIO and SCface databases, the results indicate that through linear calibration the scores
produced by the face recognition system can be less misleading in its likelihood ratio interpretation. In addition, it is shown through the categorical calibration experiments that calibration can be
used not only to assure likelihood ratio interpretation of scores, but also improving the verification
performance of face recognition system.},
            pdf = {https://publications.idiap.ch/attachments/reports/2013/I.Mantasari_Idiap-RR-01-2014.pdf}
}