[stfwn]

Fiducial markers are commonly used in photogrammetry to either speed up the process, make the resulting model more accurate or a balance of both depending on what the user is looking for. Good fiducials make for distinct features that can easily be matched across different images.

It works best if you play into the algorithm used to find the point correspondences. One commonly used one is SIFT [1]. It's a multi-step process where each step introduces some invariances, like scale invariance through convolution with gaussian kernels at different standard deviations to create a 'scale space', then doing blob detection in that space by looking at second derivative maxima and minima.

The matching process does of a lot of convolution, which is linear (so you can combine a gaussian and laplacian kernel and do both in one shot) and it can be nicely parallelized. The 8 hours of processing of ~80GB of 24MP images was on a GTX 1080.

I wouldn't say that it's particularly slow considering the amount of data and complexity of the operations, but surely a speedup would be very welcome and useful. It would become much more accessible to game companies, movie studios and even industries that (afaik) don't make much use of 3D models yet -- perhaps archaeology or anthropology would jump at the opportunity of scanning and sharing super high res models.

[1]: https://en.wikipedia.org/wiki/Scale-invariant_feature_transf...