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 [BibTeX] [Marc21]
Score Calibration in Face Recognition
Type of publication: Journal paper
Citation: I.Mantasari_IETBMT_2014
Journal: IET Biometrics
Year: 2014
Month: February
Pages: 1-11
ISSN: 2047-4938
Crossref: I.Mantasari_Idiap-RR-01-2014:
URL: http://digital-library.theiet....
DOI: 10.1049/iet-bmt.2013.0066
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.
Keywords: calibration performance evaluation, calibration performance metric, categorical calibration, face recognition system, Inter-session Variability Modelling, likelihood ratio interpretation, linear score transformation, linearly calibrated face recognition scores, mobile biometrics, speaker recognition field, surveillance camera face databases
Projects BBfor2
Authors Mandasari, Miranti I.
Günther, Manuel
Wallace, Roy
Saedi, Rahim
Marcel, Sébastien
Van Leeuwen, David
Added by: [UNK]
Total mark: 0
  • I.Mantasari_IETBMT_2014.pdf