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User Verification by Combining Speech and Face Biometrics in Video

  • Imran Naseem
  • Ajmal Mian
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5359)

Abstract

In this paper, physiological biometrics from face are combined with behavioral biometrics from speech in video to achieve robust user authentication. The choice of biometrics is motivated by user convenience and robustness to forgery as it is hard to simultaneously forge these two biometrics. We used the Mel Frequency Cepstral Coefficients for text-independent speaker recognition and local scale invariant features for video-based face recognition. Results of the two classifiers were fused using a weighted sum rule and an equal error rate of 0.6% was achieved on the VidTIMIT audio-visual database. We also performed identification experiments and achieved a combined identification rate of 99.13% on the same database.

Keywords

Hide Markov Model Face Recognition Video Sequence Recognition Rate Scale Invariant Feature Transform 
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 Berlin Heidelberg 2008

Authors and Affiliations

  • Imran Naseem
    • 1
  • Ajmal Mian
    • 2
  1. 1.School of Electrical, Electronic and Computer EngineeringAustralia
  2. 2.School of Computer Science and Software EngineeringThe University of Western AustraliaAustralia

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