How does face liveness detection work?

It detects if the person in front of the camera is the one he or she claims to be, if that person is acting by his or her own free will, or if someone else is trying to commit fraud by showing a picture or a video of that person, or even using a face fake mask.

How do you measure face recognition?

The Recognition Rate is the simplest measure. It relies on a list of gallery images (usually one per identity) and a list of probe images of the same identities. The Recognition Rate is the total number of correctly identified probe images divided by the total number of probe images.

How does passive liveness work?

Passive liveness detection technology runs in the background without users even realizing that it is occuring, so-called “security through obscurity”. It detects features of presentation attacks such as edges, texture and depth to clearly distinguish a live person’s face from an inanimate or spoofed face.

How do you beat liveness detection?

Active systems provide fraudsters with instructions that can be “reverse engineered” to attack and defeat the liveness check. Known techniques to break them include using a simple 2D mask with cut out eyes or animation software to mimic head movements, smiling, and blinking.

What is the difference between face verification and face recognition?

Face recognition is a general topic that includes both face identification and face verification (also called authentication). On one hand, face verification is concerned with validating a claimed identity based on the image of a face, and either accepting or rejecting the identity claim (one-to-one matching).

How do I determine the accuracy of face recognition?

You should read about True positive and True negative, false positve and negatives. With this formula of your accuracy=(TP+TN)/(Total). face recognition accuracy cab be measured according to the percentage of the recognized faces per the total number of tested faces of the same person.