Audio-Visual Identity Verification and Robustness to Imposture

  • Authors:
  • Walid Karam;Chafic Mokbel;Hanna Greige;Gérard Chollet

  • Affiliations:
  • University of Balamand, Al-Kurah, Lebanon and CNRS-LTCI, TELECOM ParisTech, Paris, France 75634;University of Balamand, Al-Kurah, Lebanon;University of Balamand, Al-Kurah, Lebanon;CNRS-LTCI, TELECOM ParisTech, Paris, France 75634

  • Venue:
  • ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
  • Year:
  • 2009

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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.