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« on: May 06, 2011, 12:40:18 AM »
I've been using photoscan to align photos, then export the sparse cloud as bundle.out and using CMVS to create a dense cloud. The advantage to this is once CMVS has split the job into parts I can divide the work between several computers. This helps make up for the low amount of RAM I have (4GB) and distribute the processing.
For a large model of a building I thought it would help if I could run the alignment on a downsampled set of images to help run a lot of images without running out of memory. Then use higher resolution images for the dense reconstruction in the areas that need more detail.
Using a test set of about 18 photos in a 180 degree view, I ran alignment on them at 10Megapixels, 5MP, and 3MP sizes. I couldn't use the bundle.out from the 3MP set to reconstruct using the 10MP images. The points were all wrong. However if I used a 3MP bundle on a 3MP reconstruction, and 10MP bundle on a 10MP reconstruction, the two different point clouds lined up since they were based on the same images.
Suppose I align a large group of images covering a whole building facade, using images that I have downsampled to 3MP. Then I take a smaller group of those images, which cover a decorated entrance, and align them using the 10MP versions. The point cloud for that 10MP subset will probably be created at a different scale and orientation than the point cloud created from the whole set.
Would it be possible to add a feature which does this: Create two chunks with a certain amount of images in common between them, and then base the scale and orientation of the point clouds on the camera calibrations derived from those shared images?
Also it would be nice if I could import a point cloud to be meshed within Photoscan, and have an opportunity to export the dense cloud created during the meshing process.
I know there is alignment of meshes, and I haven't tried that yet. I would like to be able to work on cleaning up the point clouds more before meshing, and having some kind of automatic alignment at that stage would be helpful.