CloudCompare forum

Hi all,

I’ve got a subsampling problem that’s quite difficult to explain...

I’m interested in modelling flow around vegetation, and have a number of high resolution scans for single plants.

I’m trying to work out how the spatial representation of the vegetation influences the modelled flow patterns.

I’ve voxelised the scans (octree subsampling) so can represent the vegetation at (approximately) known resolutions e.g. 1 cm, by extracting the xyz-coordinates.

I’ve got scans at a range of resolutions (0.25 cm – 4 cm).

However, for the model I need to keep the point spacing the same (at the minimum spacing of 0.25 cm) for all of the different resolutions.

It’s a convoluted process, but effectively I need to subsample to coarsen the resolution, but then resample the points back into a standard 0.25 cm point spacing format.

Any suggestions of how this could be done? I was thinking potentially MLS with upscaling, or a work-around using repeated translations.

Any advice would be greatly appreciated.

Thanks,
Rich

Indeed that's quite difficult ;)

You can also mesh your coarse cloud and sample points on it to get a higher density?