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Meshing Lidar Data on the Farm


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Hi all

I've read through previous posts on this topic as well as other websites attempting to solve this, but I have yet to find an adequate solution.

I am trying to build a workflow for meshing large point clouds (lidar ply files) that we can offload to our render farm. The issues I'm currently having:

1. The point clouds have no normals so point cloud ISO does not work. I'm not sure what math other point cloud software uses to generate normals on point clouds.
2. I've tested using both VDB from points and Particle Fluid Surfacer. The particle fluid surfacer seems to be faster at meshing the points, but the big problem with both is that it ends up giving you thickness which is ultimately double the number of polygons and completely unnecessary.
3. The point clouds are massive (averaging 100 million points per file), and I haven't found a good way of automatically splitting that up into better chunks. The point cluster is really slow on that many points.

Any advice would be much appreciated. I'd love to keep this inside Houdini rather than using traditional point cloud software, mainly because I can run it on the farm and because the rest of our workflow is all houdini based.

Thanks!

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Hi Nick,

I am experimenting also with large point clouds datasets but find there is a ton of work to do to manipulate these in an effective way and finding the right algorithms to estimate normals, filter outliers, classify semantically the point cloud, etc...

The method you are seems to me like a dead end as the pointCloudISO SOP is very slow so large datasets don't seem to me viable using that method. You can try adding a normal (0,1,0) should do, and see how it works...

Regarding meshing those, I feel this requires specialised tools given the amount of points... Even pcopen struggles... I guess needs some extra amount of effort... have a look at the things Ia m looking at...

 

Good luck

fastRec_techReport.pdf

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