Stereopsis from interocular temporal delay: disentangling the effects of target versus background luminance
Bibliographic record
Abstract
Introducing differences to the left-eye and right-eye images is an informative way to study stereoscopic depth perception, and particularly relevant to optically-limited stereoscopic displays (e.g., virtual and augmented reality). One such example with dynamic visual inputs is the Pulfrich effect–a depth misperception observed for horizontally moving objects with interocular luminance differences classically applied globally to both the moving stimuli and their background. Here, we disentangled the effects of the interocular luminance differences of moving stimuli and background in the Pulfrich effect. In our experiment, an observer judged the perceived direction of the 3D rotation of a sinusoidally-moving pair of small white squares presented against a gray background. The stimuli were presented in a mirror haploscope. In randomly interleaved trials we applied interocular luminance differences to the moving stimulus, the stationary background, or both. The stimulus and background manipulations introduced interocular contrast differences, which are also known to cause the Pulfrich effect. To estimate the magnitude of the illusory depth percept, we introduced a nulling interocular delay to the undimmed eye, and measured psychometric functions using the method of constant stimuli. Surprisingly, we found that the interocular delay required to null the effect was larger with the stimulus-only luminance manipulation than with the classic global or the background manipulation. Our results suggest that contrast plays a more significant role in modulating the phenomenon than previously thought. However, the source of the contrast variation (object versus background luminance) is important; larger effects were seen when the target luminance was varied than vice versa. These results have potentially important implications for understanding neural mechanisms responsible for this spatio-temporal illusion.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".