A Survey On Anti-Spoofing Methods For Face Recognition with RGB Cameras of Generic Consumer Devices
It addresses the critical issue of anti-spoofing for face recognition systems, but as a survey, it is incremental in summarizing existing work.
This survey investigates face Presentation Attack Detection (PAD) methods using RGB cameras from consumer devices over the past two decades, reviewing over 50 recent methods and providing experimental comparisons of public databases and results.
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.