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Recent Advances in Face Presentation Attack Detection

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Handbook of Biometric Anti-Spoofing

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

The undeniable convenience of face recognition (FR) based biometrics has made it an attractive tool for access control in various application areas, from airports to remote banking. Widespread adoption of face biometrics, however, depends on the perception of robustness of such systems. One particular vulnerability of FR systems comes from presentation attacks (PA), where a subject A attempts to impersonate another subject B, by presenting, say, a photograph of B to the biometric sensor (i.e., the camera). PAs are the most likely forms of attacks on face biometric systems, as the camera is the only component of the biometric system that is exposed to the outside world. Presentation attack detection (PAD) methods provide an additional layer of security to FR systems. The first edition of the Handbook of Biometric Anti-Spoofing included two chapters on face-PAD. In this chapter we review the significant advances in face-PAD research since the publication of the first edition of this book. In addition to new face-PAD methods designed for color images, we also discuss advances involving other imaging modalities, such as near-infrared (NIR) and thermal imaging. Research on detecting various kinds of attacks, both planar as well as involving three-dimensional masks, is reviewed. The chapter also summarizes a number of recently published datasets for face-PAD experiments.

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Notes

  1. 1.

    ISO/IEC 30107-1: 2016 Part 1.

  2. 2.

    http://www.tabularasa-euproject.org/.

  3. 3.

    Open source implementation available on https://github.com/mnikitin/Learn-Convolutional-Neural-Network-for-Face-Anti-Spoofing.

  4. 4.

    Open-source implementation of FASNet is available on https://github.com/OeslleLucena/FASNet.

  5. 5.

    www.lytro.com.

  6. 6.

    www.tesla-project.eu.

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Acknowledgements

This work has been supported by the European H2020-ICT project TeSLA (grant agreement no. 688520), the project on Secure Access Control over Wide Area Networks (SWAN) funded by the Research Council of Norway (grant no. IKTPLUSS 248030/O70), and by the Swiss Center for Biometrics Research and Testing.

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Authors and Affiliations

  1. Biometrics Security and Privacy Group, Idiap Research Institute, Centre du Parc, Rue Marconi 19, PO Box 592, 1920, Martigny, Switzerland

    Sushil Bhattacharjee, Amir Mohammadi, André Anjos & Sébastien Marcel

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  1. Sushil Bhattacharjee
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  2. Amir Mohammadi
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  3. André Anjos
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  4. Sébastien Marcel
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Correspondence to Sushil Bhattacharjee .

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Editors and Affiliations

  1. Idiap Research Institute, Martigny, Switzerland

    Sébastien Marcel

  2. University of Southampton, Southampton, UK

    Mark S. Nixon

  3. Universidad Autonoma de Madrid, Madrid, Spain

    Julian Fierrez

  4. EURECOM, Biot Sophia Antipolis, France

    Nicholas Evans

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Bhattacharjee, S., Mohammadi, A., Anjos, A., Marcel, S. (2019). Recent Advances in Face Presentation Attack Detection. In: Marcel, S., Nixon, M., Fierrez, J., Evans, N. (eds) Handbook of Biometric Anti-Spoofing. Advances in Computer Vision and Pattern Recognition. Springer, Cham. https://doi.org/10.1007/978-3-319-92627-8_10

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  • DOI: https://doi.org/10.1007/978-3-319-92627-8_10

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