<title>Stereoscopic video: asymmetrical coding with temporal interleaving</title>
Bibliographic record
Abstract
Asymmetrical coding has been shown to be a viable method for reducing the bandwidth required for stereoscopic video storage and transmission. In the basic version of asymmetric coding, high quality images are streamed to one eye, and lower quality images are streamed to the other eye. To remove this imbalance in image quality between the two eyes, we propose a modified version of asymmetrical coding where high-quality images are interleaved with reduced-quality images within each stream. The change between high-quality and reduced-quality images occurs in counter-phase for the two image streams, such that the levels of image quality are cross-switched between streams. Experimental evidence is provided to show that a cross-switch is best positioned at scene cuts where it is masked, otherwise it is visible as a 'jerky motion' in the stereoscopic picture. We conclude that a modified version of asymmetric coding with cross-switches occurring at scene-cuts is a useful method for balancing the image quality between eyes without introducing artifacts, while maintaining the feature of bandwidth reduction for stereoscopic video storage and transmission.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".