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Comment by codelord | Hacker News Reader

For those who are new to machine learning, this is like duct taping four wheels together and calling it a Lamborghini. Maybe a good start if you want to learn about basics of face recognition, but iPhoneX FaceID keywords here are clickbait. This is nothing like the technology used in iPhoneX.

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It kind of reminds me of when George Hotz declared that he'd created a competitor to Tesla Autopilot by training an end-to-end neural network on dashcam footage and running it on an Android phone. Sure, he had something which technically worked in brief demos but a proof of concept doesn't come close to even an alpha version of a commercial product.

This is fake news, imo.

You can currently run Hotz' software Openpilot on your car and many do. The general consensus is that it's as good as Tesla's AP2. There are hours of footage of Openpilot driving by actual users (not PR videos) on Youtube.

It most certainly does "come close to even an alpha version of a commercial product".

'Can' and 'do' aren't the same as 'should'. I can't find any recent numbers but the general trend seems to be that OpenPilot averages about one disengagement/intervention per 5 miles, while Autopilot (when not limited by the 'hands on wheel' check) significantly further between disengagements.

It's one thing to have a few tech-savvy enthusiasts installing your system and using it a bit with a good understanding of its strengths and weaknesses. It's another thing entirely to let tens of thousands of random members of the general public use your system for months on end with minimal-to-no training and no technical insight into it.

Sorry about the uses of the term 'fake news' I guess.

But I was just making the point that it's definitely at least Alpha software.

Please do not normalize that term in contexts to which it does not apply. This is not "news," and can therefore neither be real nor fake.

People have actually put this on their vehicle. It actually works pretty well from what I have seen.

https://www.youtube.com/watch?v=GzrHNI6eCHo https://www.youtube.com/watch?v=XYUHrI5-A9A https://www.youtube.com/watch?v=UkS-iJ5auD4

Exactly. Not to mention that Apple most certainly uses conventional and well-established biometrics, along with precise 3d mapping. The article is not even in the right direction.

It's literal click bait, and should be flagged as such.

Can you please explain further? How does it work on the iPhone? How is it different from this method?

For one it uses a numbers of sensors: https://support.apple.com/en-us/HT208108 But also to generalize to makeup and occlusion and millions of faces you have to do much more. There are hundreds of papers on the subject.

The technique in the article does not seem to be using depth data (there is a picture in the article), only RGB image data.

So, he could have gotten the same results with a webcam.

My understanding is that these depth cameras create a 3d point cloud and use the rgb to map/overlay color onto the 3d.

The article does mention doing experiments using depth information from a Kinect. Also, the actual code on the github repo does appear to use depth info.

It specifically mentions RGBD (RGB+Depth).

Face ID sensor will projects 30000 infrared dots onto the user's face, and then it reads the projected pattern. The pattern is sent to a deep neural network in order to confirm a match with the phone owner's face.

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