Biometric Template Update: An Experimental Investigation on the Relationship between Update Errors and Performance Degradation in Face Verification

  • Gian Luca Marcialis
  • Ajita Rattani
  • Fabio Roli
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5342)


Current methods for automatic template update are aimed at capturing large intra-class variations of input data and at the same time restricting the probability of impostor’s introduction in client’s galleries. These automatic methods avoid the costs of supervised update methods, which are due to repeated enrollment sessions and manual assignment of identity labels. Most of state-of-the-art template update approaches add input patterns to the claimed identity’s gallery on the basis of their matching score with the existing templates, which must be above a very high “updating” threshold. However, regardless of the value of such updating threshold, update errors do exist and impact strongly on the effectiveness of update procedures. The introduction of impostors into the galleries may degrade the performance quickly. This effect has not been studied in the literature so far. Therefore, a first experimental investigation is the goal of this paper, with a case study on a face verification system.


Biometrics Template update Intra-class variations Face biometrics template update errors impostors threshold selection 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Gian Luca Marcialis
    • 1
  • Ajita Rattani
    • 1
  • Fabio Roli
    • 1
  1. 1.Department of Electrical and Electronic Engineering Piazza d’ArmiUniversity of CagliariCagliariItaly

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