two_view op• Data kinds: image2d × image2d → matrix
• Call: import fullseye as fs; fs.ledger.essential_8point(pts1, pts2, K1, K2=None) (to call the implementation directly, import twoview; twoview.essential_8point(pts1, pts2, K1, K2=None); from the registry, ops3d.get("essential_8point"))
The essential matrix E directly from correspondences and K. → E (3,3).
Procedure: estimate F with fundamental_8point(pts1, pts2), form E = K2ᵀ F K1, then use SVD to replace the singular values with (1, 1, 0) (the property of the essential matrix; the Frobenius norm of the result is fixed at √2).
• K1 (3,3) is the intrinsic matrix of image 1; if K2 is omitted, K1 is used for both images (assumes the same camera).
• Correspondences are (N,2) pixel coordinates. Validation and exceptions are the same as fundamental_8point (fewer than 8 points, mismatched point counts, non-finite, or input that is not (N,2) gives ValueError).
• The sign of E is indeterminate, and (R, t) splits into 4 candidates. recover_pose does the decomposition and the disambiguation by cheirality all together.
• Defenceless against outliers. The planar / pure-rotation degeneracy is not detected by this op either (recover_pose detects it). Deterministic.
• depth_sensors — Depth sensors — ranging principles, real-device figures, how dropouts appear
• 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.
• sfm_recon — py -3.11 examples_3d/sfm_recon.py
matrix as input)two_view)fundamental_8point · recover_pose · triangulate · sampson_distance
*Provenance: twoview.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.