Visual and vestibular orientation cues interact to influence perceived depth
Bibliographic record
Abstract
Models of depth perception typically omit orientation despite the potential usefulness of the ground plane and of head position information for interpreting disparity (Blohm et al., 2008). Perceived depth is shortened when visual cues to upright are rotated relative to gravity (Mander and Harris, 2012), suggesting a role of orientation in depth perception. Here we used the York University Tumbled and Tumbling Room facilities, realistically decorated rooms systematically arranged to vary the relative orientation of visual, gravity and body cues to upright. We exploited size/distance constancy to assess perceived depth. Observers matched the perceived length of a tactile rod to a visual line (controlled by a QUEST adaptive procedure) projected on the wall of the facilities. The line was consistently set longer when the room and subject were rotated 90° relative to gravity, compared to when subjects were upright suggesting that the opposite wall appeared closer. The effect was modulated by binocular cues, nearly doubling under monocular viewing. After systematically varying the room’s and subject’s orientation, the largest ‘expansion’ was obtained when observers were upright in a rotated room (looking at the ceiling), suggesting that the illusion is induced primarily by rotation of visual cues. The effect was reduced when subjects were rotated toward the ceiling in an upright room, suggesting that the perceived distance change induced by perceived body tilt is modulated by actual body tilt. Thus, vestibular orientation cues are a mediating factor when there is a mismatch between visual and gravitational upright.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".