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> The sample scan provided by Megel to demonstrate the scanner's capabilities took, he claims, less than an hour of wall time and just four clicks of user inter
by skykooler 6y ago
> The sample scan provided by Megel to demonstrate the scanner's capabilities took, he claims, less than an hour of wall time and just four clicks of user interaction — though the processing requires the in-beta cloud platform or a more powerful host PC, with the Raspberry Pi unable to provide enough compute itself.
Is there an actual reason for this? Given the Raspberry Pi is a computer too, shouldn't it be able to compute the results as well, only slower than a proper PC?
- admash 6y agoThe unstated phrase at the end of the sentence being “to finish in a reasonable amount of time.” No one wants to wait two weeks while their r-pi converts a point cloud to a mesh.
- joshvm 6y agoPhotogrammetry is extremely compute-intensive, but it is embarassingly parallel. You need to compute feature points in all your images (which is generally fairly fast, even if you use something like SIFT). Then you have to match features which, in the worst case (non sequential images) is a brute-force N^2 problem where each N (images) might have several thousand potential keypoints. Once you've done that, you do some non-linear optimisation (typically Levenberg Marquadt or some variant) to solve for pairwise camera parameters, orientations and feature point locations. The joint problem is called bundle adjustment and you might have millions of points to solve for. Finally you have to mesh all these points together using I guess something like Delanuey triangulation. Even on a good desktop processor, it can take hours for a small scene. You really want a GPU for it.