<title>Visual comfort and apparent depth in 3D systems: effects of camera convergence distance</title>
Bibliographic record
Abstract
We investigated the effect of convergence of stereoscopic cameras on visual comfort and apparent depth. In Experiment 1, viewers rated comfort and depth of three stereoscopic sequences acquired with convergence distance set at 60, 120, 180, 240 cm, or infinity (i.e., parallel). Moderately converged conditions were rated either as comfortable (i.e., 240 cm) or more comfortable (i.e., 120 and 180 cm) than the parallel condition. The 60 cm condition was rated the least comfortable. Camera convergence had no effects on ratings of apparent depth. In Experiment 2, we used computer-generated stereoscopic still images to investigate the effects of convergence in the absence of lens distortions. Results matched those obtained in Experiment 1. In Experiment 3, we artificially introduced keystone distortions in stereoscopic still images. We found that increasing the amount of keystone distortion caused only a minimal decrease in visual comfort and apparent depth.
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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 | 0.007 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".