Abstract
Face presentation attack detection has received increasing attention ever since the vulnerabilities to spoofing have been widely recognized. The state of the art in software-based face anti-spoofing has been assessed in three international competitions organized in conjunction with major biometrics conferences in 2011, 2013, and 2017, each introducing new challenges to the research community. In this chapter, we present the design and results of the three competitions. The particular focus is on the latest competition, where the aim was to evaluate the generalization abilities of the proposed algorithms under some real-world variations faced in mobile scenarios, including previously unseen acquisition conditions, presentation attack instruments, and sensors. We also discuss the lessons learnt from the competitions and future challenges in the field in general.
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Notes
- 1.
The dataset was not yet released at the time of the competition.
- 2.
- 3.
The source code for baseline can be downloaded along with the OULU-NPU database.
- 4.
Idiap submitted also the scores of the individual sub-systems.
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The financial support from the Finnish Foundation for Technology Promotion and Infotech Oulu Doctoral Program is acknowledged.
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Komulainen, J., Boulkenafet, Z., Akhtar, Z. (2019). Review of Face Presentation Attack Detection Competitions. 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_14
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