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."
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
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.