Face Analytics

Nowadays, the increasingly growing number of mobile and computing devices has led to a demand for safer user authentication systems. Face anti-spoofing is a measure towards this direction for biometric user authentication, and in particular face recognition, that tries to prevent spoof attacks.

Safe User Authenticate System:

We have a complete pipeline/api to do face authentication and verification as a part of our “face analytics” package.

The state-of-the-art anti-spoofing techniques leverage the ability of deep neural networks to learn discriminative features, based on cues from the training set images or video samples, in an effort to detect spoof attacks.

Head Pose Estimation: User’s head rotation detection in terms of ( pitch, yaw and roll )
Eye Gaze Estimation: Identifies user’s eye movements and whether they are closed or open.
Occlusions Detection: Directing whether the user is wearing eye glasses or masks etc.
Face Liveness: Anti spoofing module to detect presentation and replay attacks.
Face Verification: Verification network for identifying the user.