tsdf_fusion op• Data kinds: sdf × depth → sdf
• Call: import fullseye as fs; fs.ledger.integrate(tsdf: 'np.ndarray', weight: 'np.ndarray', depth: 'np.ndarray', K, R, t, trunc: 'float', bounds: 'Optional[Bounds]' = None) -> 'None' (to call the implementation directly, import tsdf_fusion; tsdf_fusion.integrate(tsdf: 'np.ndarray', weight: 'np.ndarray', depth: 'np.ndarray', K, R, t, trunc: 'float', bounds: 'Optional[Bounds]' = None) -> 'None'; from the registry, ops3d.get("integrate"))
Integrate one depth frame into the volume by projective TSDF (in place, a weighted running average).
> The detailed description below is the original text — the summary and the headings are translated.
各 voxel 中心を (K,R,t) で射影(`X_cam = R X + t, u = fx*X/Z+cx`)し、対応画素の
観測深度 `d_meas と voxel のカメラ深度 d_voxel = Z_cam` を比較。
`sdf = min(1, (d_meas - d_voxel)/trunc)` を、以下すべてを満たす voxel にのみ適用:
画像内・`d_meas>0 かつ有限・(d_meas - d_voxel) >= -trunc`(表面より trunc 以上奥=
遮蔽領域は観測不能として 更新しない)。この valid 集合では sdf ∈ [-1,1]。
更新: `tsdf = (w*tsdf + sdf)/(w+1)、weight = w+1`(1 フレーム重み 1)。
bounds を渡すと voxel 中心を world で解釈し (K,R,t) は world→camera。bounds=None(既定)
では voxel 中心を grid-index フレーム((i+0.5,...))で解釈し (K,R,t) は grid→camera とする
(`fuse` は bounds を渡すので world 座標で融合される)。
• depth_sensors — 深度センサの知識 — 測距原理・実機の値・欠測の出方
• 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.
• transforms_repr — py -3.11 examples_3d/transforms_repr.py
sdf as input)sdf_to_occupancy · fuse_to_voxel · extract_surface_points · query_distance · sdf_union · sdf_intersect · sdf_subtract · sdf_smooth_union
tsdf_fusion)*Provenance: tsdf_fusion.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.