A Confidence-Based Update Rule for Self-updating Human Face Recognition Systems

  • Sri-Kaushik Pavani
  • Federico M. Sukno
  • Constantine Butakoff
  • Xavier Planes
  • Alejandro F. Frangi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5558)

Abstract

The aim of this paper is to present an automatic update rule to make a face recognition system adapt itself to the continuously changing appearance of users. The main idea is that every time the system interacts with a user, it adapts itself to include his or her current appearance, and thus, it always stays up-to-date. We propose a novel quality measure, which is used to decide whether the information just learnt from a user can be used to aggregate to what the system already knows. In the absence of databases that suit our needs, we present a publicly available database with 14,279 images of 35 users and 74 impostors acquired in a span of 5 months. Experiments on this database show that the proposed measure is adequate for a system to learn the current appearance of users in a non-supervised manner.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Sri-Kaushik Pavani
    • 1
    • 2
  • Federico M. Sukno
    • 1
    • 2
  • Constantine Butakoff
    • 1
    • 2
  • Xavier Planes
    • 1
    • 2
  • Alejandro F. Frangi
    • 1
    • 2
  1. 1.Center for Computational Imaging & Simulation Technologies in Biomedicine (CISTIB), Information & Communications Technologies DepartmentUniversitat Pompeu FabraBarcelonaSpain
  2. 2.Networking Biomedical Research Center on BioengineeringBiomaterials and Nanomedicine (CIBER-BBN)BarcelonaSpain

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