Apple reveals how its iPhone X's Face ID works... most of the time

Face ID has been a bit of a thorn in Apple's side for its iPhone X, no thanks to claims the AI-powered login mechanism can be tricked by cheapish masks or relatives of handset owners. Now, this week, Apple has published a blog post describing in a fair amount of detail how its algorithms behind the Face ID authentication system work. The approach is based on OverFeat, a model developed by researchers at New York University, that teaches a deep convolutional neural network (DCN) to classify, locate and detect objects in images. It works by using a binary classifier to detect whether or not a face is present in images taken from the front-facing camera, and a feature extractor and bounding box regression network to perform the actual identification. Pictures from the camera are run through the feature extractor to break down the images into shapes and portions, and these are passed to the binary classifier and the regressor.