<title>Cross-switching in asymmetrical coding for stereoscopic video</title>
Bibliographic record
Abstract
Asymmetrical coding is a technique that can be used to reduce the bandwidth required for transmission and storage of stereoscopic video images. This technique is based on observations that a high level of perceived stereoscopic image quality can be maintained when the quality of the video stream to one eye is reduced. To address issues surrounding eye dominance and viewing comfort, we proposed to balance the inputs to the two eyes by cross-switching the image quality in the two streams over time. Here, we report two experiments on the visibility of cross-switches, for video sequences and random-dot stereograms. In both experiments, we manipulated a) the degree of asymmetry in quality of the video streams by varying image blur, and b) the timing of the cross-switch (either at a scene-cut or during a continuous scene). The viewers' task was to indicate whether the first of the second of a pair of stereoscopic presentations contained a cross-switch. We found that the cross-switch was masked by a scene cut, and that ease of detection depended on the degree of asymmetrical blur. We conclude that asymmetrical coding combined with cross-switching at scene cuts is a practical bandwidth-reduction technique for stereoscopic video.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".