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General / Re: Algorithms used in Photoscan
« on: May 30, 2013, 02:09:00 AM »
Hi Dmitry,
We are a research team at Kansas State University. We used PhotoScan Pro heavily for various of projects. So do you think it's possible to share the literatures you mentioned in your post? We need do a project report as well based on Algorithms Photoscan uses.
Thanks a lot!!
Nan
We are a research team at Kansas State University. We used PhotoScan Pro heavily for various of projects. So do you think it's possible to share the literatures you mentioned in your post? We need do a project report as well based on Algorithms Photoscan uses.
Thanks a lot!!
Nan
Hello Arko,
We are happy to get positive feedback regarding PhotoScan software.
PhotoScan workflow is similar to the one you have presented, with an exception that our implementation is not based on the popular Bundler+PMVS2+CMVS assembly.
Here is a more detailed explanation of individual processing steps:
- Feature matching across the photos.
At the first stage PhotoScan detects points in the source photos which are stable under viewpoint and lighting variations and generates a descriptor for each point based on its local neighborhood. These descriptors are used later to detect correspondences across the photos. This is similar to the well known SIFT approach, but uses different algorithms for a little bit higher alignment quality.- Solving for camera intrinsic and extrinsic orientation parameters.
PhotoScan uses a greedy algorithm to find approximate camera locations and refines them later using a bundle-adjustment algorithm. This should have many things in common with Bundler, although we didn't compare our algorithm with Bundler thoroughly.- Dense surface reconstruction.
At this step several processing algorithms are available. Exact, Smooth and Height-field methods are based on pair-wise depth map computation, while Fast method utilizes a multi-view approach.- Texture mapping.
At this stage PhotoScan parametrizes a surface possibly cutting it in smaller pieces, and then blends source photos to form a texture atlas.
Many of the PhotoScan algorithms are based in part on previously published papers, but are implemented from scratch and are thoroughly optimized for faster processing speeds. It is worth noting that we have favored algorithms with higher accuracy output over faster approaches with less accurate output.
With best regards,
Dmitry Semyonov
AgiSoft LLC