Score calibration in face recognition
- Author(s): Miranti Indar Mandasari 1 ; Manuel Günther 2 ; Roy Wallace 2, 3 ; Rahim Saeidi 1, 4 ; Sébastien Marcel 2 ; David A. van Leeuwen 1
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View affiliations
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Affiliations:
1:
Centre for Language and Speech Technology, Radboud University Nijmegen, Nijmegen, The Netherlands;
2: Biometrics Group, Idiap Research Institute, Martigny, Switzerland;
3: Zap Technology, Brisbane, Australia;
4: Speech and Image Processing Unit, School of Computing, University of Eastern Finland, Joensuu, Finland
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Affiliations:
1:
Centre for Language and Speech Technology, Radboud University Nijmegen, Nijmegen, The Netherlands;
- Source:
Volume 3, Issue 4,
December 2014,
p.
246 – 256
DOI: 10.1049/iet-bmt.2013.0066 , Print ISSN 2047-4938, Online ISSN 2047-4946
(http://creativecommons.org/licenses/by-nc-nd/3.0/)
An evaluation of the verification and calibration performance of a face recognition system based on inter-session variability modelling is presented. As an extension to calibration through linear transformation of scores, categorical calibration is introduced as a way to include additional information about images for calibration. The cost of likelihood ratio, which is a well-known measure in the speaker recognition field, is used as a calibration performance metric. The results obtained from the challenging mobile biometrics and surveillance camera face databases indicate that linearly calibrated face recognition scores are less misleading in their likelihood ratio interpretation than uncalibrated scores. In addition, the categorical calibration experiments show that calibration can be used not only to improve the likelihood ratio interpretation of scores, but also to improve the verification performance of a face recognition system.
Inspec keywords: face recognition; visual databases; calibration; surveillance; biometrics (access control)
Other keywords: surveillance camera face databases; speaker recognition field; intersession variability modelling; calibration performance evaluation; categorical calibration; face recognition system; linearly calibrated face recognition scores; calibration performance metric; likelihood ratio interpretation; linear score transformation; mobile biometrics
Subjects: Measurement standards and calibration; Computer vision and image processing techniques; Image recognition
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