Perceived distance depends on the orientation of both the body and the visual environment
Bibliographic record
Abstract
Models of depth perception typically omit the orientation and height of the observer despite the potential usefulness of the height above the ground plane and the need to know about head position to interpret retinal disparity information. To assess the contribution of orientation to perceived distance, we used the York University Tumbled and Tumbling Room facilities to modulate both perceived and actual body orientation. These facilities are realistically decorated rooms that can be systematically arranged to vary the relative orientation of visual, gravity, and body cues to upright. To assess perceived depth we exploited size/distance constancy. Observers judged the perceived length of a visual line (controlled by a QUEST adaptive procedure) projected on to the wall of the facilities, relative to the length of an unseen iron rod held in their hands. In the Tumbled Room (viewing distance 337 cm) the line was set about 10% longer when participants were supine compared to when they were upright. In the Tumbling Room (viewing distance 114 cm), the line was set about 11% longer when participants were either supine or made to feel that they were supine by the orientation of the room. Matching a longer visual line to the reference rod is compatible with the opposite wall being perceived as closer. The effect was modulated by whether viewing was monocular or binocular at a viewing distance of 114 cm but not at 337 cm suggesting that reliable binocular cues can override the effect.
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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 | 0.002 |
| 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) | 0.003 | 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".