Object velocity relative to the head and depth order from object-produced motion parallax
Bibliographic record
Abstract
The geometry underlying the recovery of depth order from motion is that the angular velocity originating from the rigid translation of objects relative to the observer is inversely proportional to the distance from the observer to the objects. Previous studies revealed that the calculation of angular velocity requires either retinal (Braunstein & Andersen, 1981, P&P, 29, 145–55; Naji & Freeman, 2004, Vision Res, 44, 3025–34) or extraretinal signals (Nawrot, 2003, Vision Res, 43, 1553–62). We explored how the visual system integrates retinal signals with extraretinal ones to determine depth order. We used a stimulus in which four rows of horizontally moving random-dots had a common motion component and a relative motion component. The direction of common motion relative to the moving pursuit point was opposite to that of the pursuit point, and the velocities of the common motion and of the pursuit point were manipulated independently. The relative motion component consisted of the dots in all four rows moving in the same direction but the dots in the first/third rows and the second/fourth rows had different speeds. Observers were required to report which rows appeared in front. Possible cues for scaling the amplitude of eye-movements were eliminated by presenting the stimulus on a black screen in a darkened room so that the frame of the screen was invisible. We tested the prediction that the depth order produced by retinal motion (i.e., dots moving faster on the retina appear closer) can be reversed by an eye-movement velocity signal that exceeds that of the retinal motion (i.e., dots moving slower on the retina now appear in front). The prediction was confirmed with three different velocities of common motion. The result suggests that object-velocity relative to the head is calculated by adding eye-movement velocity to retinal velocity and is processed for determining depth order from object-produced motion parallax.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".