3D reconstruction of largest Hallstatt tumulus grave in central Europe (T3 entry)

Hi all!

This is my entry for the T3 Season 2 - The Model challenge: 

A survey of the earliest Celtic lunar calendar based on free open source tools

 http://de.wikipedia.org/

The "building":

The royal tomb at Magdalenenberg, near Villingen-Schwenningen, in Germany’s Black Forest, is the largest Hallstatt tumulus grave in central Europe, measuring over 320ft (100m) across and (originally) 26ft (8m) high. The royal tomb functioned as a lunar calendar and preserves a map of the sky at Midsummer 618 BC, the presumed date of the burial. The order of the secondary burials around the central royal tomb fits exactly the pattern of the constellations visible in the northern hemisphere at Midsummer in 618 BC, while timber alignments mark the position not of the sunrise and sunset but of the moon, and notably the Lunar Standstill. Lunar Standstills are marked in several ancient cultures (including sites in Colorado and Ohio), usually by standing stones that indicate the point where the moon seems to rise and set in the same place, instead of rising in one place and appearing to move across the sky to set in another.

As such the royal tomb at Magdalenenberg is the earliest and most complete example of a Celtic calendar focused on the moon. Following Caesar’s conquest of Gaul, the Gallic culture was destroyed and these types of calendar were completely forgotten in Europe.

http://www.world-archaeology.com/

See also: http://en.wikipedia.org/

The copter:

  • A Hexacopter (Mikrokopter frame, APM 2.6) based on a design concept by Stehen Gienow.

The cameras: 

  • Canon Elph 110 HS, one converted to IR

The free open source image and 3D processing chain:

The open source Ground Control Station:

The flight:

  • Flight altitude: 50m AGL 
  • Ground image resolution: 0.7cm

The Results:

  • 3D point could before dense matching:

  • Clipped 3D point cloud after dense matching (however, not the highest resolution possible):

You can download this file here (22MB *.zip).

  • RGB orthophoto:

  • IR orthophoto:

  • Soil Adjusted Vegetation Index map:

  • Digital surface model draped over a hill shade model and the IR orthophoto:

The georeferenced model

  • Google Earth: T3_Magdalenenberg.kmz (with subfolders)
    • including:
      • Flight path
      • Camera trigger locations
      • RGB orthophoto
      • IR orthophoto
      • DSM model
    • Size: 11MB

The 3D model to play with

  •  WebGL 3D model 
    • it might take some time to load...
    • tested with Firefox, Chrome, IE and Safari (needs to be enabled)
    • this is how it looks (in case it doesn't load)

A 3D visualization for some more serious analysis

  • Orthophoto 

  • Hillshade

  • Enhanced Vegetaion Index

The APM Log file:

Some random remarks:

  • All data is georeferenced
  • MicMac (as well as the whole processing chain) is quite complex
  • Due to security reasons I always take off in stabilize mode
  • Landing should have been automatic but needed to be interrupted due to some curious onlookers 
  • APM+Droidplanner is a great professional product
  • It would be great to have an image dataset (or several) available on DIYDrones for comparing image processing software
  • Color calibration is a big issue

Thanks to Gary, DIYdrones, 3DRobotics, and the developers of the free open source tools!

Thorsten

Views: 4433

Comment by Phill Scott on February 1, 2014 at 6:59am

Hi Thorsten,

Your results look great - would you be able to provide some background on how you did this? Or, if not (because of the competition), can you (or anyone) point to some good source material / tutorials on this?

Many Thanks,

Phill


Developer
Comment by Linus on February 1, 2014 at 7:00am

Beeindruckend! Just wow!


T3
Comment by Thorsten on February 1, 2014 at 10:15am

Thanks! Danke! 

Phill, there are millions of steps to take care about. This is why I "only" provided links to the software I used. This has nothing to do with the T3 contest. But I cannot write a full tutorial. I guess it would end up in writing a book. Moreover, I started with all this (hard- and software) the time when this contest was opened. So no time for writing up any documentation so far - except this blog post. But, for sure there are (at least sparse) documentations for most of the software packages. What are you interested in primarily?

I am planning to develop a GUI for all this which would make it a lot easier for sure. But it is just more or less just a plan for now...

Thorsten


Moderator
Comment by Gary Mortimer on February 1, 2014 at 10:15am

Phill all the software links are above. Thorsten as for the others well done. I have been blown away by the work undertaken this time. It just shows the unmanned aircraft part really is the simple bit, post production is hard. When DIYD started this was just the sort of work we all imagined. I don't think we thought it would happen using free tools and with such accuracy so quickly.


T3
Comment by Thorsten on February 1, 2014 at 10:29am

Gary, thanks!

If you start from scratch and are crazy enough to build your own copter from some list of parts and if you have to build the camera mount, the vibration damping etc. on your own it takes time too. But if you carefully RTFM - which is very good - everything works fine and you can build the copter you need without crashing. This is great! The advantage is that you really know your copter. However, it takes time.

This is maybe similar to the software. For example I just came across this: http://imagine.enpc.fr/~moulonp/openMVG/. But until you have a chain up and running it can take long for sure. So I have to admit that I was also surprised that I could achieve such results so quickly.


Moderator
Comment by Gary Mortimer on February 2, 2014 at 1:38am

We are certainly going to have to lean on all you experts for help generating a wiki page for others to learn from. I am running through some point clouds I created in 2010 with some of the software new to me that I have seen here and my head hurts! Very cool though and one wonders what things will look like in another five years time.


T3
Comment by Thorsten on February 2, 2014 at 2:42am

Normally, I do not work with point clouds because I do not really need them. To visualize the point clouds presented above I used MeshLab and CloudCompare - which I forgot to mention in the post. But, yes this sometimes hurts - with increasing intensity the larger the clouds get. There is also Blender if you are interested in 3D animations. Gerard recently showed an example using Blender on DIYDrones


Moderator
Comment by Gary Mortimer on February 2, 2014 at 3:22am

I also use CloudCompare and like its ability to save in Lidar formats so I can they use the point clouds in other places. I am just mucking about with all this stuff, its nerdy interest! I do think a simple tool chain could greatly help environmental work.


T3
Comment by Thorsten on February 2, 2014 at 3:38am

A simple toolchain would be perfect. But it is complex since we have to deal with such diverse things as log files, images, exif data, GIS data formats, spatial coordinates, image processing, color calibration, statistical analysis, RGB and IR overlays, not to forget bugs in the various packages etc. Expensive commercial software takes care about some of these steps. But for sure not all. I am planning to implement a more comprehend tool chain - focussing on environmental work - in a user friendly GUI. I'll let you know if I make any progress...

Comment by Ned Horning on February 2, 2014 at 7:59am

I like the idea of a wiki page. I'm also working on these sorts of aerial photo work flows and would like to contribute to some sort of online collaborative environment but don't know how to make that happen so it's productive. My focus is on extracting information to support conservation applications. I agree that the image acquisition platforms are surprisingly mature and increasingly accessible to the masses. The open source photo pre-processing chain to make ortho-mosaics and other image products is taking shape but information extraction (image classification, feature recognition...) is still quite rudimentary. Any thoughts on how to harness expertise and enthusiasm to develop and document open source work flows?

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