Assessment of a Footstep Biometric Verification System

  • Rubén Vera Rodríguez
  • John S.D. Mason
  • Nicholas W.D. Evans
Part of the Advances in Pattern Recognition book series (ACVPR)

Abstract

This chapter reports some novel experiments which assess the potential of footsteps as a biometric. We present a semi-automatic capture system and report results on a large database of footstep signals with independent development and evaluation data sets comprised of more than 3000 footsteps collected from 41 persons. An optimisation of geometric and holistic feature extraction approaches is reported. Following best practice we report some of the most statistically meaningful and best verification scores ever reported on footstep recognition. An equal error rate of 10% is obtained with holistic features classified with a support vector machine. As an added benefit of the work, the footstep database is freely available to the research community. Currently, the research focus is on features extraction on a new high spatial density footsteps database.

Keywords

Support Vector Machine Ground Reaction Force Equal Error Rate Speaker Recognition Automatic Speech Recognition System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London Limited 2009

Authors and Affiliations

  • Rubén Vera Rodríguez
    • 1
  • John S.D. Mason
    • 1
  • Nicholas W.D. Evans
    • 2
  1. 1.Swansea UniversitySwanseaUK
  2. 2.Institut Eurécom2229 route des CrêtesFrance

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