{"submission_id":"55b4a43d-27af-4ed1-a23d-32fd28783b82","submission_revision_id":"8318a9f0-b1c1-42c9-81ee-7cb8576c8ca4","revision_version":2,"submission_status":"under_review","submitted_at":"2026-08-16T13:40:00.818657Z","submitter_name":"Aditya Prakash","submitter_email":"prakashadityaap@gmail.com","task":{"status":"submitted","version":2,"extra_fields":{},"submitted_at":"2026-08-16T13:40:00.818657+00:00","industry_domain":"Computer Vision / 3D Geometry (point-set registration)","task_short_name":"point_set_registration","operating_system":"Linux","task_description":"Summary: given corresponding 3D point pairs related by an unknown similarity transform (scale + rotation + translation) with small noise, recover s, R, t minimizing mean squared residual (Umeyama). Output s, R, t and the achieved RMS to `result.json`.\n\nFormulas and schema are in `SPEC.md`. See below:\n\n## Goal\n`scene.json` gives two ordered lists of 3D points, `src` and `dst` (same length,\npoint `src[i]` corresponds to `dst[i]`), related by an unknown **similarity\ntransform** plus small measurement noise:\n\n```\ndst[i] ≈ s · R · src[i] + t\n```\n\nRecover the scalar scale `s > 0`, the rotation `R` (3×3, orthonormal, det +1), and the\ntranslation `t` (3-vector, mm) that minimize the mean squared residual. Write them to\n`result.json` along with the achieved RMS error.\n\n## Method (accepted: any correct least-squares solution)\nClosed form (Umeyama 1991):\n1. Centroids `μ_s`, `μ_d`; centered `X_s = src − μ_s`, `X_d = dst − μ_d`.\n2. `Σ = (1/N) X_dᵀ X_s`; SVD `Σ = U D Vᵀ`.\n3. `S = I`, but set `S[2,2] = −1` if `det(U)·det(V) < 0`. Then `R = U S Vᵀ`.\n4. `s = trace(D S) / var(src)` where `var(src) = (1/N) Σ‖X_s‖²`.\n5. `t = μ_d − s R μ_s`.\n\n## Input: `scene.json`\n```\n{ \"src\": [[x,y,z], ...], \"dst\": [[x,y,z], ...] }\n```\n\n## Output: `result.json`\n```\n{\n  \"scale\": <float>,\n  \"R\": [[3x3]],\n  \"t\": [x, y, z],\n  \"rms_error\": <float>   // sqrt( mean_i || s R src_i + t - dst_i ||^2 )\n}\n```\n`R` must be a valid rotation (orthonormal, det +1). Python 3.11 + NumPy only. No\nnetwork access.\n","software_licensing":"Free/Open Source","evaluation_criteria":null,"verification_method":"Binary pass/fail via `python grader.py scene.json result.json <agent_output_file>`. ALL must hold:\n1. Submission has keys `scale`, `R` (3x3), `t` (3-vector), `rms_error`.\n\n2. scale > 0; R orthonormal with det = +1 (tol 1e-9).\n\n3. The transform is optimal on the data: achieved RMS <= reference optimum + 1e-4.\n\n4. Self-reported rms_error matches the recomputed value (tol 1e-4).\n\n5. Matches the reference: |scale| diff <= 1e-5, rotation geodesic error <= 1e-4 rad,\n   translation error <= 1e-3 mm.","software_and_version":"Python 3.11 with NumPy 1.24+ (standard library only otherwise)","specific_requirements":null,"expected_completion_time":null},"files":[{"file_id":"71b300e2-be24-4262-941f-84552f1ce24a","filename":"scene.json","category":"input_materials","content_type":"application/json","size_bytes":3944},{"file_id":"d09ca046-fcc4-4ab2-94c8-01c8d797dd24","filename":"SPEC.md","category":"input_materials","content_type":"text/markdown","size_bytes":1213},{"file_id":"a050d3f8-a435-4f0e-9a98-8585e3693a1b","filename":"result.json","category":"reference_output","content_type":"application/json","size_bytes":469},{"file_id":"5463b787-6110-43ea-b56c-d37a4f749eb2","filename":"grader.py","category":"reference_output","content_type":"text/x-python","size_bytes":4426}],"deep_review":{"overall_verdict":"Accept","review_text":"**Overall Verdict:** Accept — The submission is complete, internally consistent, objectively gradable, and reachable with the declared open-source toolchain.\n\n**Completeness Check:**\n- Instruction: Complete — The transformation objective, least-squares method, units, output schema, and rotation constraints are explicit.\n- Inputs: Complete — `scene.json` contains 20 equal-length pairs of finite numeric 3D points with nondegenerate geometry and no missing values.\n- Toolchain: Complete — Python 3.11, NumPy 1.24+, Linux, and offline execution form a practical, freely obtainable single-machine workflow.\n- Reference output: Complete — `result.json` has the required fields and dimensions; its positive scale, proper rotation, translation, optimality conditions, and reported RMS are numerically consistent with the input.\n- Rubric: Complete — `grader.py` implements the stated binary checks with explicit tolerances, strict finite-value and shape validation, residual recomputation, and reference comparisons.\n\n**File and Task Reachability:**\nAttachment classification: reachable. Task classification: reachable. All four attachments were inspected: `scene.json` (3,944-byte JSON), `SPEC.md` (1,213-byte UTF-8 Markdown), `result.json` (469-byte JSON), and `grader.py` (4,426-byte UTF-8 Python). Their downloaded sizes match the manifest, their actual formats match their declared roles, and there are no containers, encryption barriers, or unreviewed contents. The evaluator was inspected statically rather than executed; its relevant numerical contract and reference values were independently checked. Solver-visible inputs are separated from the reference and evaluator assets by manifest category. End to end, a solver can read the paired points, compute the similarity transform with Python and NumPy, emit the specified JSON, and be evaluated deterministically against the protected reference. License keys, accounts, tokens, and other credentials are not required from the contributor. Confidential, proprietary, or internal material may be evaluated as submitted evidence without requiring additional disclosure.\n\n**Special Screening:**\n- `public_benchmark` — The task explicitly identifies the canonical Umeyama 1991 method and supplies its closed-form equations. This does not expose the instance-specific numerical answer, which still requires processing the submitted point data; the offline environment further limits answer retrieval.\n\n**Recommended Changes:**\nThe submission provides coherent inputs, a valid reference, and a hardened evaluator. No changes are required.","reviewed_at":"2026-08-19T18:25:46.304772Z"},"claim":null}