Template Update Methods in Adaptive Biometric Systems: A Critical Review

  • Authors:

  • Ajita Rattani;Biagio Freni;Gian Luca Marcialis;Fabio Roli

  • Affiliations:

  • Department of Electrical and Electronic Engineering, University of Cagliari, Italy;Department of Electrical and Electronic Engineering, University of Cagliari, Italy;Department of Electrical and Electronic Engineering, University of Cagliari, Italy;Department of Electrical and Electronic Engineering, University of Cagliari, Italy

  • Venue:
  • ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
  • Year:
  • 2009

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Abstract

Template representativeness is a fundamental problem in a biometric recognition system. The performance of the system degrades if the enrolled templates are un-representative of the substantial intra-class variations encountered in the input biometric samples. Recently, several template updates methods based on supervised and semi-supervised learning have been proposed in the literature with an aim to update the enrolled templates to the intra-class variations of the input data. However, the state of art related to template update is still in its infancy. This paper presents a critical review of the current approaches to template updating in order to analyze the state of the art in terms of advancement reached and open issues remain.