What statistics / machine learning model is used to unlock cell phone with fingerprint / face? I am asking a high level question on what is the model "type" for unlock a cell phone using fingerprint / face. 


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*It seems to me supervised learning cannot be used, because we do not have labeled data. 

*Is it a "anomaly detection"? Where we model the normal patterns of a authenticated user and reject abnormal patterns? But for anomaly detection say 1 class SVM, we still need reasonable amount of "normal patterns". But it seems cell phone only needs to collect data from authenticated user couple of times.
What is the model used to check fingerprint / face to unlock a cell phone?
 A: I worked on the Android team that was responsible for face unlock so I can say roughly how that works. It does, in fact, use a statistical model. It is trained as a binary classifier by giving it pairs of pictures where either each image in the pair comes from the same person or one image is from the true person and the other is an impostor. This classifier outputs a matching score. Then a cutoff threshold is chosen. To unlock the phone all someone has to do is present a face that matches the stored profile better than the threshold. Separately, there are various technologies that try and determine if the camera is detecting an actual face or if it is an image or a video of a face. That used to be hard to do but I imagine now that the sensors have improved and it is more reliable.
Fingerprint matching is a bit different. If you look closely at your fingerprint you will see lots of places where a ridge ends or bifurcates. These are called minutiae. The first step is for an algorithm to locate the position of each visible minutiae. Then fingerprint matching occurs by trying to put the locations of the minutiae in correspondence with the locations from the stored template.
A: From this article on The Verge: 

[an infrared sensor] throws 30,000 infrared dots on your face. The systems reads the map, matches it against the stored image on the phone using a built-in neural network processor, and unlocks the phone.

So it is a neural network of some kind, if this reviewer can be trusted. Based on the image recognition literature, I would assume it's even a deep neural network. Unfortunately, as the comments say, we will likely never know exactly the model due to trade secrets. 
