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
Review of face presentation attack detection competitions
|Author:||Komulainen, Jukka1; Boulkenafet, Zinelabidine1; Akhtar, Zahid2|
1Center for Machine Vision and Signal Analysis, University of Oulu, Oulu, Finland
2INRS-EMT, University of Quebec, Quebec City, Canada
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2019090326577
|Publish Date:|| 2021-01-02
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.
Advances in computer vision and pattern recognition
|Pages:||291 - 317|
Handbook of Biometric Anti-Spoofing
|Host publication editor:||
|Type of Publication:||
A3 Book chapter
|Field of Science:||
113 Computer and information sciences
The financial support from the Finnish Foundation for Technology Promotion and Infotech Oulu Doctoral Program is acknowledged.
© Springer Nature Switzerland AG 2019. This is a post-peer-review, pre-copyedit version of an article published in Handbook of Biometric Anti-Spoofing. Advances in Computer Vision and Pattern Recognition. The final authenticated version is https://doi.org/10.1007/978-3-319-92627-8_14.