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Google Begins Blurring Faces In Street View
mytrip notes a News.com article reporting that Google has begun blurring faces in its Street View service, which has spawned privacy concerns since its introduction last year. Google has been working for a couple of years to advance the state of the art of face recognition. Quoting News.com: 'The technology uses a computer algorithm to scour Google's image database for faces, then blurs them, said John Hanke, director of Google Earth and Google Maps, in an interview at the Where 2.0 conference...' Google wrote about the program in their Lat/Long blog."
If you have an out of focus picture, can you manipulate the image mathematically to put it "in focus" or is there some information lost in the out-of-focusness so you can't do this.
A:Yes
And if so, with the appropriate app, will you be able to un-blur the people's faces in Google Street View?
A:Yes
You can't add pixels that aren't there, and an out of focus picture is effectively a lower resolution.
You can, however, apply statistical analysis and AI learning techniques to guess the likely locations of pixels. In that way, you can sharpen a photo somewhat, though it may be inexact. My understanding is that contextual analysis is the next step- if you have pictures of a person and a blurry person, and have more pictures of that person and less-blurry people, you can make predictions about who the fuzzy people are.
Of course, I wear a beard so that I'll always be fuzzy.
"The cup is in turn designed for holding hot or cold liquids, and has an open rim and closed base." --US Patent #5425497
Google has already added a face search feature to image search. It's not too shabby either. I'm sure they're looking into other options as well.
Aside from time factor (I suppose it works 24h/day), what's the big legal difference from what the TV programs do when they show random people, in scenes from the cities or so?
This article from a year ago shows that Google has had public implementations of facial recognition for some time. Simply appending &imgtype=face to a Google image search URL will just show images of faces.
Interesting that you should say that... as this was a recent BBC article I read. And it's not even "upskirt", it's just taking pictures of peoples behinds. Of course, the best part is the last sentence...
"The past was erased, the erasure was forgotten, the lie became truth." ~1984 George Orwell
From a signal processing perspective, this is the same as convolving with a Gaussian. And if you take the Fourier transform of that blurred image, you get the transform of the image multiplied by the transform of the Gaussian (which is just another Gaussian). From there all you have to do is divide by this Gaussian, take the inverse transform, and walla, you have the desired non-blurred image. This is called a deconvolution, and I've written code to do this for an image processing class.
There are some caveats. You have to guess how blurred the image is - what focal length is and what not. Noise and compression can kill you, so you need to filter those out first (or limit your deconvolution filter to low frequency content). In addition at the edges of the image (or edge of the blur boundary) information is genuinely lost as the gaussian falls outside the boundary and is discarded.
Focus Magic is a commercial package that refocuses blurred images, and they have some interesting sample photos.
Well, the thing is: people are more than happy to jump to conclusions, without having any context for that photo.
E.g., I've waited for a taxi at a street corner before. Admittedly, I'm a guy, but I don't remember any law or moral code that forbids women to use taxis either. So it doesn't take too much of a stretch of imagination to allow for the possibility that those two girls too were just waiting for their ride. Or maybe they went shopping and are waiting for the BF of one of them to come give them a ride home. Or various other possibilities.
We don't actually have enough data to make a judgment there. If they're on the same corner for several hours straight, daily, yes, then they're probably working there. But we don't know that. We have just a snapshot that doesn't really say anything by itself.
But people are more than happy to jump to a conclusion anyway.
The same applies to a lot of other situations.
E.g., it's trivial to take someone's photo that looks like he's walking towards a brothel, when he's just really walking past it.
E.g., the most heinous case of "it's not what it looks" involved a UK chav filming himself pissing on what looked to him like a dead-drunk woman passed out on the side-walk. Turns out that she wasn't drunk, she was just dying of liver failure. (And before you jump to conclusions again, there _are_ ways to get that without being an alcoholic.) So instead of calling an ambulance, the retard filmed himself pissing on her while she was dying, and posted the movie.
A polar bear is a cartesian bear after a coordinate transform.
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