> Ah, well, appearances can be deceptive.  There are many papers
> in computer vision in which you can see fancy 3D reconstructions
> produced from camera images.  However, when you really get 
> into the nitty gritty of how these work you'll usually find that
> they were either produced under highly contrived conditions or 
> the result you can see is not statistically representative (i.e.
> you might get a good result, but only 20% of the time).

Thanks Bob, 

For my purposes, I'm actually fairly comfortable with "highly contrived
conditions", results that are very approximate or just robust object
segmentation (rather than full/partial reconstruction). I share a lab with a
Robocup team, and was toying with the idea of trying to adapt their C++ code
and their highly contrived soccer field to my experiments. Unfortunately,
though, Robocup vision would fail if you were to throw a yellow ball onto
the field (instead of red): the systems aren't "open-ended" enough for my
liking.

> However, this is a problem that I'm currently working on a 
> solution for (see http://code.google.com/p/sentience/).

This looks very interesting. How long (and on what sort of machine) does it
take to process each stereo pair with your dense stereo correspondence
algorithm?

> These are all non-trivial problems and I don't know of any 
> libraries (java or otherwise) which "out of the box" perform
> 3D reconstruction in real time from camera images.

Thanks - it isn't looking too promising. It seems like I'm going to have to
use bright lights, simple objects and then write some code of my own (or
look into interfacing directly with a C++ system).

-Ben


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