How Does AI Training Work in Face Biometrics?

Advancing research in facial anti-spoofing is not possible without data. Big data is paramount to building a powerful facial liveness detector because convolutional neural networks have millions of parameters, and the optimization process is a bit tricky. The well-trained network is composed of properly configured parameters. When we feed the input image into this function, it returns the class of input indicating whether it is spoof or not. To train a detector, we collect a set of photos or videos of many live people and a set of spoofs.