Hi Rene,

again sorry for the late chime in.
> •       Get an image of the object (e.g. a pool ball) from e.g. a stereo
> camera with texturing or e.g. a laser range finder.
I am not sure what are you trying to say with "camera with texturing",
but what has been done is applying the following stereo processing
code on the stereo images:
https://code.ros.org/svn/ros-pkg/stacks/image_pipeline/trunk/stereo_image_proc/mainpage.dox
Now, to improve the quality of the stereo correspondences, a pattern
projector has been uses to boost up the number of corresponding images
in both cameras
(http://www.willowgarage.com/blog/2009/06/19/sensor-head). Shall one
use a laser range finder, then it is important to notice that the
finder has to be tilted in order to generated the full 3D point cloud.

> •       Transform the image (either a stereo-photo or a “sphere” of
> distances) into a point cloud. A point cloud is a collection of
> points, where all points have a number of pre-defined attributes, like
> spatial coordinates, color, or neighborhood density. Point clouds are
> the universal data structures for performing 3-dimensional algorithms
> within ROS. TODO: figure out the algorithm
Do you still need more clarifications here?

> •       Transform the point cloud into a wireframe. TODO: figure out which
> algorithm is used for this.
Do you still need an example of this? I got some code but would need
to make it pcl-compatible first.

cheers, D.