The article may very well have exaggerated how easy it is to pull off. However, I would actually take it a step further.

I could build a facial recognition system for $0 using open-source software and freely available camera feeds.

That's the real crux of the article: The data (camera feeds) is out there. The software is out there. Anyone could do this.

Therefore, what are we doing to prevent it, if anything?

> One of the biggest problems in AI is that NN cannot match an object in 2 images if it was taken from different perspective

I think you've missed the last 5-ish years of NN development. Some of the latest Face2Vec stuff can handle different perspectives pretty well by either building a system that can predict 3D representations of the face from one shot[0] or by just training on two different perspectives of the same face and having the system output the same vector (I've read some work on this but Google is failing me at finding a reference).

If you can recognize people from different angles, computers will eventually be able to do it better than you. Probably already.

[0]https://arxiv.org/pdf/1703.10714.pdf

Bingo. 1) Train an algorithm that given any angle view of a human head, produce a 3D reconstruction of said head. (Depending upon the amount of face visible, the accuracy of the reconstruction increases. 2) Train an algorithm that given a human head geometry, it identifies any deformation due to facial expression and neutralizes that expression. 3) Trivial algorithm: given a human head geometry not facing the camera, rotate that head such that it is facing the camera. 4) render the human head geometry without expression, facing the camera, using the video image source as the texture map for said head. 5) Perform FR.

You're talking about training data, but (as I understand it) current commercial facial recognition may use learned features but from there it uses traditional biometrics to identify faces. So this criticism doesn't necessarily hold as these biometrics could easily be one-shot.

(Any facial recognition gurus feel free to enlighten me, of course! :)

Sure, but that's not that big a barrier.

First, there are some pretty good classified mugshot datasets in existence. FB's, for one.

Second, you can get some mileage out of just matching images to eachother. One or more cameras track an individual to get multiple angles. You may not know the individual's name, but you will know that it's the same person walking past the cameras every day.

Third, you can always target a limited set of faces. Don't casinos use something like this for persona non grata?

You just training on do two face images come from the same person.

https://towardsdatascience.com/one-shot-learning-face-recogn...

Did you read the article? They show the image that was matched of the professor compared to the training image, they are completely different perspectives.

You've been out of the loop, just look at FaceNet, your face in any orientation for a human to recognise is enough for the software to do so as well. Is already open source & doesn't need any manual tuning after it has been trained, also scales excellently.

Right on, for a minute I was wondering if there hasn't been a leap in the efficiency of neural nets that I missed.

That sounds reasonable but what do you think they're marketing?

depends on nytimes KPIs :D maybe just growing click rates on the article

99% of the stuff you see online is marketing.

Someone want to benefit from your visit.

If they don't try to sell you anything, they want to get traffic so they will create an attractive clickbait title

Well, that’s a conveniently tautological conspiracy theory.