voxel_grid_downsample — 3D preprocess op

Data kinds: pointspoints

Call: import fullseye as fs; fs.ledger.voxel_grid_downsample(points, voxel_size: 'float') (to call the implementation directly, import pcl_filter; pcl_filter.voxel_grid_downsample(points, voxel_size: 'float'); from the registry, ops3d.get("voxel_grid_downsample"))

Usage

Thin a point set on a lattice of edge voxel_size, collapsing each cell to one centroid point (deterministic).

> The detailed description below is the original text — the summary and the headings are translated.

空間を一辺 `voxel_size` の立方体セルに区切り、同じセルに落ちた点をその重心

1 点で代表させる。密度ムラを均し、下流(ICP・特徴量)の計算量を点数で抑える標準手法。

出力順はボクセル座標の辞書順で固定(同じ入力なら常に同じ出力=決定論的)。

Parameters

----------

points : array_like, shape (N, 3)

入力点群。

voxel_size : float

セルの一辺(> 0)。大きいほど強く間引く。

Returns

-------

ndarray, shape (M, 3)

各占有セルの重心(M <= N)。すべて入力の軸並行 bounding box 内に収まる。

Notes

-----

`voxel_size <= 0` は ValueError。空入力は空 (0,3) を返す(graceful)。

重心はセル内の点の平均なので、必ず入力点の凸包(ゆえに bbox)内に入る。

Background guides (the physics and conventions behind this op)

depth_sensors — 深度センサの知識 — 測距原理・実機の値・欠測の出方

References (sample data, literature)

• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).

• Operator provenance and references — the sources of the research/methods this op family came from.

Runnable examples (verified samples that actually call this op)

pointcloud_downsamplingpy -3.11 examples_3d/pointcloud_downsampling.py

Ops the type connects to (they accept points as input)

points_to_voxel · gaussians_to_voxel · estimate_point_normals · to_points · match_points_ncc · match_pca · moment_axes · icp_point2point_3d

Same category (preprocess)

statistical_outlier_removal · radius_outlier_removal · mls_smooth · volume_downsample


*Provenance: pcl_filter.py — 3D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.