  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.
