Comparison of stereoscopic and nonstereoscopic video images for visual telephone systems
Bibliographic record
Abstract
Possible differences in perceptual qualities between stereoscopic and non-stereoscopic images were investigated using a field-sequential stereoscopic display. A total of forty non-expert viewers were asked to rate overall image quality, sharpness and sense of presence using the double-stimulus continuous quality scale (ITU-R Recommendation 500). Viewers rated a set of five video sequences (stereoscopic and non-stereoscopic) each presented at four levels of image quality that were obtained by varying the quantization level (Q=0, 32, 36, and 39) of a generic H.264 video compression codec. Each sequence was 8 seconds long at 30 frames per second and the spatial resolution of each frame was common image format (CIF, 352 x 240 pixels). Image size was 15.5 cm x 11.6 cm and scene contents were representative of visual telephone systems with one, two or three individuals. The experimental results showed that viewers' ratings depended on the sequences and that there was no reliable difference between stereoscopic and non-stereoscopic sequences in terms of image quality and perceived sharpness. However, binocular disparity tended to improve ratings of sense of presence. We conclude that incorporating stereoscopic information into visual telephone systems can be useful for enhancing sense of presence.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".