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wstuartcl | 3 years ago

There have been pretty huge leaps over partially obstructed facial recognition algorithms in the last few years -- I think state of the art is approaching no meaningful loss of match mask vs no mask.

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snapcaster|3 years ago

How could this be true? I don't follow the field but so much of the signal is being obscured it's hard to imagine how accuracy wouldn't suffer

flangola7|3 years ago

tldr machine learning is magic

iPhone face unlock has worked while wearing a mask for a while now.

You know how you can identify exactly which family member is walking in the door from across the house, and maybe even what mood they're in? Or how little clarity you need to identify your child or spouse on a 480p camera feed? That's what machine learning makes possible across all types of sensor input, picking out those little but distinct patterns. There's really no way to be anonymous in public once ML surveillance software is widespread.

blobbers|3 years ago

Negative ghost rider.

It is most certainly not, unless you’re talking straight on well lit training data.

wstuartcl|3 years ago

This is not my understanding, I have read at least 7 or 8 papers that seem to have for various models and techniques reduced the delta between masked and unmasked recognition to be very similar on false positive and positive rates.

https://www.mdpi.com/2076-3417/11/16/7310 https://www.sciencedirect.com/science/article/pii/S240589632... ...

That said I have no insight as to how many of these techniques have been found to scale well or have started to make it into product. It has been publicly reported that NEC’s NeoFace (a system that many police and govt use) newer versions does indeed have occlusion (mask) recognition operating at very high levels.

anyways thats just my understanding as an interested bystander -- not in the field.