Comparison of Radial and Tangential Geometries for Cylindrical Panorama
Bibliographic record
Abstract
This paper presents a new approach whichbuilds 360-degree cylindrical panoramic images from multiple cameras. In order to ensure a perceptually correct result, mosaicing typically requires either a planar or near-planar scene, parallax-free camera motion between source frames, or a dense sampling of the scene. When these conditions are not satisfied, various artifacts may appear. There are many algorithms to overcome these problems.We propose a panoramic setup where cameras are placed evenly around a circle. Instead of looking outward, which is the traditionalconfiguration, we propose to make the optical axes tangent to the camera circle, a "tangential" configuration.We will demonstrate that this configuration is very insensitive to depth estimation, which reduces stitching artifacts. This property is only limited by the fact that tangential cameras usually occlude each other along the circle.Beside an analysis and comparison of radial and tangential geometries, we provide an experimental setup with real panoramas obtained in realistic conditions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".