Topics

1

General / Automatic GCP identification

« on: October 24, 2012, 01:19:16 PM »

We use Photoscan for orthophoto and DEM generation from UAV imagery. We have established a workflow where we scatter orange targets throughout the study area for which we collect accurate differential GPS coordinates. We then manually identify these targets in PhotoScan for more accurate aerotriangulation. In a previous workflow with Bundler and PMVS2, we were able to automatically identify the orange points in the 3D point cloud and match them with their corresponding GPS points. This saved a lot of manual work. I have been wondering whether such a feature could be implemented in PhotoScan. When I saw the changelog in the latest release I noticed the following:
"Added support for automatic coded target detection (12 bit and 16 bit)"

Unfortunately, I have not been able to find out any more information about it in the wiki, forum, or help pages. I am wondering whether this new feature is related to my 'wish'. If so, could you provide information on how to use it? If not, would you be able to include this as a feature request?
Thanks and kind regards,
Arko

2

General / Algorithms used in Photoscan

« on: May 02, 2011, 04:04:36 AM »

Dear Dmitry,
First of all, I would like to say that you have produced a very impressive bit of software. We are using Photoscan and Photoscan Professional here at the University of Tasmania to derive 3D point clouds from historical aerial photography and aerial photographs acquired from an unmanned aerial vehicle (UAV). I have previously worked with SIFT, libsiftfast, Bundler, PMVS2, and CMVS, and have achieved some very good results with these tools. I have come across some examples where Photoscan outperforms Bundler when it comes to calculating camera position, orientation, and distortion parameters, especially when the focal length is unknown or uncertain (like in underwater photography). I am keen to publish some of our results in scientific journals, however, in order to do that I want to be able to report on the general type of algorithms that are used in Photoscan. As far as I can tell Photoscan follows a very similar approach to the following workflow:

• SIFT
• key matching
• bundle adjustment for camera position, orientation, and distortion parameters + sparse point cloud (based on Bundler?)
• patch-based multi-view stereo for dense point cloud reconstruction (based on PMVS2 and or CMVS?)
• surface reconstruction based on Delauney triangulation or Poisson surface reconstruction
• Texture mapping

I am curious to known if you developed your own algorithms from scratch or if you have built on and improved on existing algorithms. I realise that you might not be able to or not want to provide too much technical detail. However, in order to use the Photoscan results in a publication I want to be able to report on the workflow and methods. Any help would be greatly appreciated.
Thanks in advance and keep up the great work!
Arko