A Closed-Form Solution to Single Underwater Camera Calibration Using Triple Wavelength Dispersion and Its Application to Single Camera 3D Reconstruction
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we present a new method to estimate the housing parameters of an underwater camera by making full use of triple wavelength dispersion. Our method is based on an important finding that there is a closed-form solution to the distance from the camera center to the refractive interface once the refractive normal is known. The correctness of this finding is mathematically proved in this paper. To the best of our knowledge, such a finding has not been studied or reported, and hence is never proved theoretically. As well, the refractive normal can be estimated by solving a set of linear equations using wavelength dispersion. Our method does not require any calibration target, such as a checkerboard pattern, which may be difficult to manipulate when the camera is deployed deep undersea. Extensive experiments have been carried out which include simulations to verify the correctness and robustness to noise of our method and real experiments. The results of real experiments show that our method works as expected. The accuracy of our results is evaluated against the ground truth in both simulated and real experiments. Finally, we also show how we can apply dispersion to compute the 3D shape of an object using one single camera.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it