Thank you for your comments Geobit and Yoann,
Just a few thoughts, perhaps it's easiest if I use quotes:
I must say I always get frustrated when our Alexey resumes something saying, "this can be done with Python...". (I suspect he smiles like an evil swot when he adds " so easily"... Yes it is great to have the py api, but not everyone knows how to use it, and there are dozens of simple but terribly useful things that should already be among menu items, and "Split in chunks" is one of them.
- I agree some things could just be integrated into the software, rather than having to rely on Python. For people who don't know Python (like me), remember there is also this library with scripts, including a "split in chunks" script:
http://wiki.agisoft.com/wiki/Python I know the scripts didn't work anymore the day after PS 1.3 was released, but perhaps they've now been updated.
I usually merge them at the end after chunk alignment (no matter what method) and re-align the merged chunk. I'm almost sure that Photoscan takes the camera orientations in the merged chunk as initials so there is no need to export and create a new chunk from scratch, but on the contrary one can build the sparse cloud and optimize directly.
- I don't think this is in fact the case. I think if you re-run "align images" in a merged chunk, PhotoScan simply starts from scratch (perhaps unless you use pre-selection: reference) and re-calculates everything, ignoring the previously calculated camera orientations.
One goal of this procedure is to keep cameras grouped (calibration wise) as they were originally and that might be the right path in some cases. i.e. when chunks were photographed in diferent sesions with the same camera but eventually with diferent focus settings. (to create a chunk from blank might lead Pscan to put all photos in the same basket)
- Remember that in such cases you can also simply work in a single chunk, and then group photographs taken in different sessions in different camera calibration groups, using the camera calibration groups on the left of the Tools -> Camera Calibration window.
I think that there must be a reason to not keep (merge) tie points created during chunk to chunk alignment. My guess is that the quality of the feature point matches ch2ch cannot be evaluated in the same way as is done inside a chunk where they link photos-to-photos and their residuals can be miminized by moving photos relatively. On the contrary, during ch2ch alignment, the relative orientations between photos inside a chunk must be kept while the entire block moves during iterations to mimimize the global residual for all at once. After ch2ch alignment one tie point could have a very big reprojection error due to the rigidnes of the two structures it belongs to... well this is just my theory.
- This might be true. Even then though, in case they can't be compared
in the same way, surely there is some way to interlink everything, and perhaps simply give less weight to tie points matched during chunk alignment. In case of camera-based chunk alignment though, if both chunks have been aligned using the same image alignment settings, I would think you could almost directly tranfser tie points from photo A to B to C with the same weight. But of course I don't know what the magic behind the scenes in the PS algorithms is, so this is something Alexey would have to comment on
Cheers,
Thomas