| title: Point Cloud Voxel Downsampling | |
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| # Voxel downsampling with geometry preservation | |
| How far `bigpointcloud_001.ply` (11,357 points, normals + RGB) can be voxel-downsampled before its | |
| geometry degrades, measured rather than eyeballed: surface displacement (mean / RMS / p95 / | |
| Hausdorff), normal deviation and bounding-box shrinkage across a sweep of voxel sizes, plus a | |
| comparison against random subsampling at the same point budget. | |
| - **safe** — voxel 0.210, 8,832 pts (78%), mean error 0.032, normals within 5.7° | |
| - **aggressive** — voxel 0.279, 5,592 pts (49%), mean error 0.083, normals within 13.3° | |
| At the same 5,592-point budget, random subsampling matches the mean error but is 3× worse at the | |
| Hausdorff bound. See `index.html` for the full write-up, `voxel_downsample.py` for the script. | |