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Robust Audio Visual Biometric Person Authentication with Liveness Verification

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Intelligent Multimedia Analysis for Security Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 282))

Abstract

In this paper we propose liveness verification for enhancing the robustness of audio-visual biometric person authentication systems. Liveness verification ensures that biometric cues are acquired from a live person who is actually present at the time of capture for authenticating the identity. The proposed liveness checking technique based on cross-modal association models involves hybrid fusion of acoustic and visual speech correlation features, which measure the degree of synchrony between the lips and the voice extracted from speaking face video sequences. Performance evaluation in terms of DET (Detector Error Tradeoff) curves and EERs (Equal Error Rates) on publicly available audiovisual speech databases show a significant improvement in robustness of system against different types of simulated replay attacks.

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Author information

Authors and Affiliations

  1. Faculty of Information Sciences and Engineering, University of Canberra, Australia

    Girija Chetty

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  1. Girija Chetty
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Editor information

Editors and Affiliations

  1. TOBB ETÜ Computer Engineering Department, Sögütözü Cad.No:43, Sögütözü, 06560, Ankara, Turkey

    Husrev Taha Sencar

  2. Computing, Information Systems and Mathematics, Kingston University London, Penrhyn Road, KT1 2EE, Surrey, UK

    Sergio Velastin

  3. Department of Informatics, Aristotle University of Thessaloniki, Box 451, GR-54124, Thessaloniki, Greece

    Nikolaos Nikolaidis

  4. France Telecom R&D (Orange Labs) Beijing, Raycom Infotech Park C, 2 Science Institute South Road, Haidian District, 100080, Beijing, China

    Shiguo Lian

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Chetty, G. (2010). Robust Audio Visual Biometric Person Authentication with Liveness Verification. In: Sencar, H.T., Velastin, S., Nikolaidis, N., Lian, S. (eds) Intelligent Multimedia Analysis for Security Applications. Studies in Computational Intelligence, vol 282. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11756-5_3

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  • DOI: https://doi.org/10.1007/978-3-642-11756-5_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-11754-1

  • Online ISBN: 978-3-642-11756-5

  • eBook Packages: EngineeringEngineering (R0)

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