Effect of disparity and motion on visual comfort of stereoscopic images
Bibliographic record
Abstract
It is well known that some viewers experience visual discomfort when looking at stereoscopic displays. One of the factors that can give rise to visual discomfort is the presence of large horizontal disparities. The relationship between excessive horizontal disparity and visual comfort has been well documented for the case in which disparity magnitude does not change across space and time, e.g. for objects in still images. Much less is known about the case in which disparity magnitude varies over time, e.g., objects moving in depth at some velocity. In this study, we investigated the relationship between binocular disparity, object motion and visual comfort using computer-generated stereoscopic video sequences. Specifically, viewers were asked to rate the visual comfort of stereoscopic sequences that had objects moving periodically back and forth in depth. These sequences varied with respect to the number, size, position in depth, and velocity of movement of the objects in the scene. The results indicate that change in disparity magnitude over time might be more important in determining visual comfort than the absolute magnitude of the disparity per se. The results also suggest that rapid switches between crossed and uncrossed disparities might negatively affect visual comfort.
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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 | 0.003 |
| 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) | 0.003 | 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".