Seeing double: The impact of perceptual organization on the limits of binocular fusion
Bibliographic record
Abstract
For a given disparity between two points, there is a 2D separation at which the fixated and disparate points cannot be fused simultaneously. The ratio of that disparity to the angular separation is referred to as the disparity gradient limit (Burt & Julesz, 1980). The disparity gradient limit is believed to reflect geometric constraints on fusion. However, this assumption is called into question by the observation that under natural viewing conditions violations of the disparity gradient limit are common, but diplopia is rarely experienced. One explanation for this discrepancy is the fact that laboratory studies of fusion limits typically use simple isolated stimuli, while objects in the real world are more complex, with multiple connected components. We hypothesized that perceptual organization (via connectedness) modulates the perception of diplopia and used the method of adjustment to assess the impact of connectedness on fusion limits. Pairs of dots were presented stereoscopically at a fixed vertical separation either in isolation or connected by horizontal lines, at a range of disparities. Gaps were added in the lines to manipulate connectedness. Vergence demand was controlled by presenting the upper and lower dot pairs in both uncrossed and crossed directions, and by limiting stimulus duration to 100ms. Our results consistently show that increasing element connectedness significantly increases the disparity gradient limit; the fusion limit occurred at larger disparities when elements were connected by a continuous line, and intermediate when they were connected by discontinuous lines. These data suggest that the disparity gradient limit does not reflect a low-level constraint on fusion but is modulated by perceptual organization. From this work it appears that in addition to supporting figure/ground segmentation, perceptual grouping plays an important role in mitigating diplopia.
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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 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".