fixed small error in segment_clouds.h (segment:: in class method declaration with class definition)
Debugging intersection of all displayed planes with all displayed planes
Debug version that runs, computes plane-plane interesections and keeps only intersections
of quasi-orthogonal planes in a structure. I must now analyze two clouds, perform the analysis,
assume the camera is more or less horizontal so the largest y component is along the verticla line.
The assumption is that the plane-plane intersections of the largest planes are alined with the
edges formed by wall-wall intersection in a prismatic room.

TODO: compare results with two images.
TODO: run analysis with less points
TODO: how to make use of the RGB image file.
eigen.h, eigen.hpp come from PCL (just there for reference). Will be used to
transform on (x,y,z) coordinate system into another orthogonal coordinate system.

I have computed a collection of ortho vectors along with various dot products.
Check out processPlanes() in segment_clouds.cpp .

With these, I will rotate each to a system (1,0,0), (0,1,0), (0,0,1) . The first
camera will have a transformation  T1, and the second camera a transformation T2.
The composite transformation will thus be inv(T2)*T1(camera1 vector)  to transform
points from camera 1 to the coordinate system of camera 2. One will still need a translation
to position the clouds correctly. (Height should be easy. z might be possible (since
both cameras are in the same room, pointing towards the end of the room.). One could also assume
that the object of interest is approximately at the same distance from each camera.
I now compute the transformation of the cloud to a standard coordinate  (1,0,0), (0,1,0), (0,0,1)
Seems to work. However, registration cannot be tested (from a rotational point of view), until I do
the analysis for two clouds.

Note: It is soon time to reintroduce initial voxel filtering. The easiest way will be to filter every other
point out of the original organized cloud, before removing the NaNs.  That will accelerate algorithms by
at least a factor of 4.
VoxelGridSkip works. I can specify a skip of 2 and it will skip 2 in each
direction, and will also remove Nans at the same time. First and last argumetns
can be the same (cloud_src and cloud_tgt). Templatized.
Display of 2D images and plane extraction works on two images.
Check out the addition of two new routines in the register class
to accomplish this.
Extract planes from two clouds, compute transformation to standard coordinate system.
Combine transformations, and regisiter clouds.  results are not very good.
Got my first automatic registration (rotation) and as a bonus, height of ceiling.
I had to set the PLANE RANSAC threshold to 0.02  in order to capture small orthogonal
planes to the main planes in the ceiling. Problem: how to make this work in general.

Seeking lines within planes will not work because the Kinect has a natural scan direction,
so false lines will likely be found, which are not physical.

Consider applying  clustering algorithm to each plane to identify which planes corespond
to solid planes, and which planes are the "false" result of objects in the scene aligned
by chance to form a plane.

Consider some kind of multi-scale approach. Start with higher thresholds, and go towards
lower thresholds. I am not sure, intuitively of how well that would work.