match_mip_2d — 3D `match_localize` op

• Data kinds: voxel × voxel → position

• Call: import fullseye as fs; fs.ledger.match_mip_2d(scene_vol, model_vol, device='cpu') (to call the implementation directly, import match3d; match3d.match_mip_2d(scene_vol, model_vol, device='cpu'); from the registry, ops3d.get("match_mip_2d"))

• GPU: this op has a GPU path (device="cuda")

Usage

MIP projection → 2-D NCC (structure = voxel → 2-D, method = NCC, transform = orthogonal MIP).

Reduces the problem via maximum intensity projections along 3 orthogonal directions to 3 2D problems, locates with the existing 2D NCC → estimates the 3D coordinates redundantly from the 3 images. Cheaper than full 3D NCC, for coarse alignment. Suited to translation search without rotation.

Procedure: voxel_to_mips makes 3 MIPs for both scene and model; in each projection the bbox of the model MIP's > 5%·max is cropped as the template, and accel_match.ncc_locate_batch (2D NCC, template-centre convention) gives the position. The projection collapsing axis 0 gives (y,x), axis 1 gives (z,x), axis 2 gives (z,y), so each coordinate is obtained from 2 images, and their mean is returned. Returns [z, y, x] as (3,) float64 (a mean of integer NCC positions, so in steps of .5). No score is returned.

• The position is where in the scene MIP the centre of the cropped bbox template lands. Not the centre of the model

volume.

• Projections whose model MIP is all 0 are skipped; if a coordinate cannot be obtained from even 1 image, it becomes 0.0 (no exception

is raised).

• MIPs lose depth information through overlap, so they are weak with multiple objects and clutter.

Downstream: pass this coarse position to refine_translation_lk / refine_lm.

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)

• matching_localize — py -3.11 examples_3d/matching_localize.py

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

refine_peak_newton · refine_translation_lk · refine_lm · fuse_to_voxel

Same category (`match_localize`)

match_shape_3d · match_chamfer_3d · match_curvature_3d · match_hough_3d · match_points_ncc

*Provenance: match3d.py — 3D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

match_mip_2d — 3D match_localize op