[GeoWeb3DContest] Rotterdam data

[Information and updates on Web3D's Rotterdam city data competition]

The Rotterdam texture atlases appear to be completely random.
When I open a vrml version of the afrikuunderwuk data in a vrml editor:
http://dug9.users.sourceforge.net/web3d/temp/screenshot_dug9gui_test.jpg
the long buidling in the lower left, I can pick chunks/sections of it, and just in the little stretch we see, there are 3 different texture files involved. So to draw that building, you'd need to load at least 3 1024x1024 image textures. That's sub-optimal.
I don't see a pattern to how they did the textures. 
-Doug
more..
ROTTERDAM> AFRIKUNNDERWUK TEXTURES
(8 x 19) + 5 ~= 160
160 x 1024x1024x4 = 160 x 4MB = 640MB
with mipmapping lets say 128 layers 1.3GB
Yes that's texture heavy.

Hypotheses for seeming randomness to the texture atlases:
H0: military requirements: they had to scramble the textures in little bits so an enemy could not reconstruct a coherent base map from the texture images
H1: the software they used for authoring accidentally randomized
H2: there's a pattern / a method to the madness and I just can't see it

A first job of fixing might be to reconstruct a conherent base/orhtophoto texture
Method 1: use googleEarth snapshots
Method 2: get a vrml browser to render (however slowly) the buildings and ground as given, as seen from above. Then do a snapshot in the vrml browser to get a vertical texture. Tile those textures to get an orthophoto
Method 3: ask Rotterdam for their original ortho images

Once there are coherent orthophoto textures for the ground, then the building texture coordinates would need to be re-done.
Method A: manually
Method B: use image correlation and search algorithms to find roof texture in orthophoto, then shift the texture coordinates
Because there are textures for the sides of the buildings too, and if we desire per-building atlases, then
Method C: iterate over buildings, and for each building:
- iterate over shape faces, and for each face
-- from texture coordinates and original atlas image, extract the pixels for that face, and place in a new per-building atlas
and in this way automatically build per-building atlases including sides and roof