On 28/01/2008, Benjamin Johnston <[EMAIL PROTECTED]> wrote:
> I'm after either: fairly robust object segmentation; 2.5D or 3D
> reconstruction; object recognition; or something like superquadric
> reconstruction. Something that attempts to describe the physical structure
> of the world seen through the camera.


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



> I know this is possible – I see it done again and again at AI conferences;


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).

Programs such as the CMU photopopup and photosynth appear impressive,
but in the CMU case the reconstruction quality is poor (good enough
for entertainment, but not much else) and the photosynth case they're
still trying to reduce the huge amount of number crunching needed to
produce the point cloud models (which can take hours or days with
current computers).

There is progress being made on 3D reconstruction using scanning laser
rangefinders.  This is the same kind of technology used in the DARPA
chellenges, but it's not cheap and it's certainly not "off the shelf"
in software terms.

I think it will be possible to produce colour 3D models in real time
from camera images using reasonably low cost off the shelf technology
within about five years, but for the moment it remains as a kind of
holy grail in computer vision.  Once this happens then many new
robotics applications will become possible.

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