Earlier quoted context omitted.
FaceID samples are generated from a very small camera. It’s trivial to train a CNN image classifier that can identify an individual, even when they are wearing a hat, grew facial hair, have a scar, etc
And now have that work without depth data, increase the population size from one person to 1+ billion, apply to moving video, aim for high precision and high recall, keep it battery friendly as you distribute to all police, somehow get the classifier of 1B unique people onto all these embedded devices, keep it up to date as people age, etc.... Hardly trivial.
But I was attempting to rebut GP’s point that a small camera is incapable of performing facial recognition. That’s plain incorrect. Speed/scale are orthogonal issues.