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Audio-Visual Identity Verification and Robustness to Imposture

  • Walid Karam
  • Chafic Mokbel
  • Hanna Greige
  • Gérard Chollet
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5558)

Abstract

The robustness of talking-face identity verification (IV) systems is best evaluated by monitoring their behavior under impostor attacks. We propose a scenario where the impostor uses a still face picture and a sample of speech of the genuine client to transform his/her speech and visual appearance into that of the target client. We propose MixTrans, an original text-independent technique for voice transformation in the cepstral domain, which allows a transformed audio signal to be estimated and reconstructed in the temporal domain. We also propose a face transformation technique that allows a frontal face image of a client to be animated, using principal warps to deform defined MPEG-4 facial feature points based on determined facial animation parameters. The robustness of the talking-face IV system is evaluated under these attacks. Results on the BANCA talking-face database clearly show that such attacks represent a serious challenge and a security threat to IV systems.

Keywords

Identity verification audio-visual forgery talking-face imposture voice conversion face animation biometric verification robustness 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Walid Karam
    • 1
    • 2
  • Chafic Mokbel
    • 1
  • Hanna Greige
    • 1
  • Gérard Chollet
    • 2
  1. 1.University of BalamandAl-KurahLebanon
  2. 2.CNRS-LTCI, TELECOM ParisTechParisFrance

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