tb_estimate_alpha — 2D `typed` op

• Data kinds: points → feature

• Call: fullseye.apply(img, "tb_estimate_alpha", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

Usage

Returns a recommended alpha based on the scale of the point cloud (based on the median nearest-neighbor distance).

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

各点の最近傍距離の中央値 `m` を求め、半径しきい値 1/alpha ≈ 2m(隣接間隔の約 2 倍まで

許す)となるよう `alpha = 1/(2m)` を返す。これで表面付近の素性の良い四面体は残しつつ、

大きく間延びした四面体(=凹み・外側)を切り落とせる。重複点は最近傍 0 になるため正の距離のみ使う。

Parameters

----------

points : array_like (N,3)

Returns

-------

alpha : float

正の有限値。

2-D 進化レジストリへ橋渡しした 3d の op `estimate_alpha。実装は同じで、呼び出し規約だけ op(v, a, b) に合わせてある。この op に調整点は無く、a も b` も使われない。

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)

• (none yet)

Ops the type connects to (they accept `feature` as input)

identity

Same category (`typed`)

tb_points_to_voxel · tb_estimate_point_normals · tb_iss_keypoints · tb_angle_3points · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal · tb_radius_outlier_removal

*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

tb_estimate_alpha — 2D typed op