Related to my previous question, is there some realistic chance to extract surveillance camera positions out of google streetview pictures by means of computer vision algorithms? I'm no expert in that area. But it should be easier than face detection and the like.
I think you're wrong about it being an easier problem than face recognition (though I suspect you mean face detection).
Consider that faces are of a reasonably regular shape, generally have 2 eyes a nose and a mouth in a specific configuration whilst surveillance cameras from one manufacturer will look different from those of another and look different from different angles.
With faces, if you can't see the person's face you're not interested in it, but in your scenario you're interested in detecting the camera regardless of it's relative position to you.
Whilst not impossible (i.e. humans can do it!) I don't think computer science is quite up to the task just yet.....
I definitely agree with Rob that extracting the camera locations is going to be more difficult than face detection (or even recognition).
How about a different tack on your question: how to find the location of the camera taking surveillance images.
There are standard (if complicated) photogrammetry techniques to map 2D or 3D coordinates of objects using photographs from multiple cameras or a single camera at multiple angles. What you're looking for would be "reverse photogrammetry" which I haven't seen before, but this interesting legal anecdote suggests it's feasible.
This sounds like the class of problem for which Amazon's Mechanical Turk was invented. I don't believe that an image processing or image recognition algorithm is within our current understanding and hardware/software capabilities.