flow_from_depth_motion — DRIVE ttc op

• Data kinds: image2d × matrix × matrix → table

• Call: import fullseye as fs; fs.ledger.flow_from_depth_motion(depth, K, T_rel) -> 'dict' (to call the implementation directly, import drivettc; drivettc.flow_from_depth_motion(depth, K, T_rel) -> 'dict'; from the registry, opsdrive.get("flow_from_depth_motion"))

Usage

> This operator's description has not been translated yet. The original text follows as it is.

深度像と剛体運動から 真の像の流れ: `{"u", "v", "valid", "depth1"}`(各 (H, W))。

画素の 3-D 点を `T_rel で動かして再投影し、u = col₁ − col₀、v = row₁ − row₀`。動かした後に

カメラの背後へ行く点や深度の無い画素は `valid = False(u, v は NaN)。depth1` は動かした後の深度。

光学流の推定器の採点に使う真値(推定器と同じ規約: (x, y) → (x + u, y + v))。

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.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

• poc_ttc_rss — py -3.11 examples/poc_ttc_rss.py

• poc_world_terrain — py -3.11 examples/poc_world_terrain.py

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

course_layout · course_occupancy · course_contains · world_build · world_camera · world_move · lidar_scan · rss_longitudinal_same

Same category (ttc)

relative_motion · foe_from_motion · ttc_truth · ttc_from_flow · ttc_from_scale · ttc_from_range · label_extent · foe_from_flow

*Provenance: drivettc.py — DRIVE 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.