A Survey On Anti-Spoofing Methods For Face Recognition with RGB Cameras of Generic Consumer Devices
October 08, 2020 ยท The Cartographer ยท ๐ Journal of Imaging
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"Title-pattern auto-detect: A Survey On Anti-Spoofing Methods For Face Recognition with RGB Cameras of Generic Consumer Devices"
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Authors
Zuheng Ming, Muriel Visani, Muhammad Muzzamil Luqman, Jean-Christophe Burie
arXiv ID
2010.04145
Category
cs.CV: Computer Vision
Citations
70
Venue
Journal of Imaging
Last Checked
1 day ago
Abstract
The widespread deployment of face recognition-based biometric systems has made face Presentation Attack Detection (face anti-spoofing) an increasingly critical issue. This survey thoroughly investigates the face Presentation Attack Detection (PAD) methods, that only require RGB cameras of generic consumer devices, over the past two decades. We present an attack scenario-oriented typology of the existing face PAD methods and we provide a review of over 50 of the most recent face PAD methods and their related issues. We adopt a comprehensive presentation of the methods that have most influenced face PAD following the proposed typology, and in chronological order. By doing so, we depict the main challenges, evolutions and current trends in the field of face PAD, and provide insights on its future research. From an experimental point of view, this survey paper provides a summarized overview of the available public databases and extensive comparative experimental results of different PAD methods.
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