
AI Can Recognize Your Face Even If You’re Pixelated - tonybeltramelli
https://www.wired.com/2016/09/machine-learning-can-identify-pixelated-faces-researchers-show/
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Gaessaki
Pixelating and blurring images has long been known to be insufficient in
completely obscuring information [1]. In fact, in a lot of computer vision
work, the image resolution is reduced to ignore noise and facilitate the
workload for algorithms anyway. Completely destroying information through
blacking out is preferable.

[1] [https://dheera.net/projects/blur](https://dheera.net/projects/blur)

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evincarofautumn
I’m not terribly surprised by this. Downsampling is a really effective way to
create a “fingerprint” by which you can identify some data. And that’s
essentially how an image-searching service works.

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userbinator
It also means that people with similar faces might get identified as the same
person.

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dogma1138
Which has always been a problem as both fingerprint identification and facial
recognition are probability based, and often the confidence level is
considerably lower than what anyone would be comfortable with.

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Houshalter
I dont know about pixelation, but gaussian blur can be undone mathematically.
Pixelation at least destroys the vast majority of the information.

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dogma1138
Depending on how it's pixelated, I seems that there is a trend of making more
pixels because it looks cooler but also reduces the masking power of the
process considerably.

I would think that a 64 by 64 grid could be sufficient for pretty high level
of confidence matching. And matching doesn't need to be perfect it often is
far from it it needs to be good enough to provide a basis for elimination.

It might even work with considerably lower resolutions because with video
pixels aren't static and they change so you get considerably more data than
what you would get out of a single frame, once you account for things like
lighting and video compression you can get quite a bit of data out of it.

This is not that dissimilar from analysing aerial or geospatial photography
you can have features represented by a single pixel sometimes and you need to
identify them with high enough confidence so you develop models based on how
the pixels would "change" over time, or how would the effect nearby pixels at
the end this what allows you to distinguish between a tank and an SUV or
between a man holding a gun and a man holding a cat, these aren't perfect by
any stretch of the imagination but we have put decades of work into this.

I would assume that you can both extrapolate directly and indirectly apply a
lot of those methods onto facial recognition of pixelated images.

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paulpauper
if you have the original font, blurring can be defeated . always better to
just black out text that you don;t want to to be seen

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forgotpwtomain
Can journalists stop writing 'AI' everywhere when it's just Neural Nets? It's
all starting to look ridiculous - if you need a popular science friendly word,
what's wrong with Image Recognition Program?

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bonoboTP
More clicks this way. More clicks, more ad revenue. That simple.

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chriswarbo
Reminds me of
[https://en.wikipedia.org/wiki/Christopher_Paul_Neil](https://en.wikipedia.org/wiki/Christopher_Paul_Neil)

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tmikaeld
This is based on having the original (unpixelated) image in every case, right?

