Optimal pixel aspect ratio for stereoscopic 3D displays under practical viewing conditions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In multiview 3DTVs the original 3D-scene is reconstructed based on the corresponding pixels of adjacent 2D views. For conventional 2D display the highest image quality is usually achieved by uniform distribution of pixels. However, recent studies on the 3D reconstruction process show that for a given total resolution, a non-uniform horizontally-finer resolution yields better visual experience on 3D displays. Unfortunately, none of these studies explicitly model practical viewing conditions, such as the role of the 3D display as a medium and behavior of the human eyes. In this paper the previous models are extended by incorporating these factors into the optimization process. Based on this extended formulation the optimal ratios are calculated for a few typical viewing configurations. Some supporting subjective studies are presented as well.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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