ADSB - Part 2 or I now have a public server to display locations on

As you might have seen in a previous post I have been working an ADSB receiver for my UAV.

Well now I have also created a server with the web front end running on it at http://globelock.dyndns.org:8081/

I still find it amazing how far away I can pick up aircraft from the standard antenna sitting on my roof

Structure from an un-ordered set of photos

 

For quite some time now I have been working on how to get a 3d-mesh from a set of photos working so that I can have real-time terrain mapping on the UAV using the 2 on board cameras.
After search the web and finding a lot of pre-compiled binaries that would work on the ARM CPUS that are in the UAV I finally found some source code. The unfortunate thing is that it all has some very vague instructions on how to get it up and running...

The software I found was the following:

• osm-bundler (https://code.google.com/p/osm-bundler/)
• This is just a few scripts that wrap up all the bundler steps

• bundler-sfm (https://github.com/snavely/bundler_sfm)
• the bundler software the processes the images into a course point map

• cmvs-pmvs (https://github.com/pmoulon/CMVS-PMVS )
• takes the output of bundler and converts it to a dense point map

• meshlab (installed via package on Fedora)
• Viewer for point cloud data and exporter for other tools like blender

So after many tests the process was as follows:

1. take a set of photos with my Samsung Galaxy S3 phone
2. Run RunBundler.py (from osm-bundler) with the --photos option pointing to the directory containing a copy of photos from phone
•  The first time you also need to run RunBundler with the --checkCameraDatabase to create an entry in the camera database for the focal length. I skipped this as I thought it was not needed. In the end I set it 12 (12mm) as that should be about right for this phone camera.
  
3. The above creates a directory in /tmp, cd into that directory
4. run Bundle2PMVS list.txt bundle/bundle.out
   This will create some files in a subdirectory named 'pmvs'
5. Edit 'pmvs/prep_pmvs.sh' supplying a path for the binaries
6. run the above file
7. run pmvs2 pmvs/ pmvs_options.txtThis will now have created the dense point cloud in 'pmvs/models/pmvs_options.txt.ply'
   This file can now be used in meshlab