Modelling extreme wide‐angle lens cameras
Bibliographic record
Abstract
Abstract The use of consumer cameras fitted with extreme wide‐angle (EWA) lenses for photogrammetric measurement is increasing. Conventional modelling of EWA systems relies on the pinhole camera model and up to five radial lens distortion terms. Aiming to reduce model complexity, this paper reports on an investigation into an alternate approach using fisheye lens models for EWA systems, despite them not falling strictly into the fisheye category. Four fisheye models were tested on four different cameras under laboratory conditions. The self‐calibration results show superior model fit for all fisheye models over the pinhole‐plus‐radial model in terms of residual RMS. The number of radial distortion terms required for the fisheye models was lower in all cases, so model complexity was reduced. Independent assessment revealed very similar 3D reconstruction accuracy for all models. The results suggest that fisheye modelling is an advantageous alternative for EWA lens systems.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".