register_fpfh — 3D feature_register op

• Data kinds: points × points → pose

• Call: import feat_fpfh; feat_fpfh.register_fpfh(src, dst, src_normals=None, dst_normals=None, voxel_size=None, normal_k=16, feature_k=60, n_bins=11, ransac_iters=8000, inlier_thr=None, edge_sim=0.9, mutual=True, ratio=0.95, seed=0, device='cpu') (or ops3d.get("register_fpfh"))

Usage

Estimate the rigid alignment (R,t) without an initial guess using FPFH descriptors and RANSAC.

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)

• feature_register — py -3.11 examples_3d/feature_register.py

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

fuse_to_voxel · pose_error · bundle_adjust · mean_reprojection_error · optimize_pose_graph · relative_pose · mean_edge_error · rotation_translation_error

Same category (feature_register)

harris3d_keypoints · iss_keypoints · compute_fpfh · shot_descriptor · register_spin · register_shot

*Provenance: feat_fpfh.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.