Cues that determine the perceptual upright: Visual influences are dominated by high spatial frequencies
Bibliographic record
Abstract
INTRO: The perceived direction of upright - the preferred orientation for polarized objects to be recognized - depends on the relative orientations of the visual background, the body and gravity. The perceptual upright (PU) is distinct from the subjective visual vertical (SVV) which is dominated by the direction of gravity and which predicts the perceived effects of gravity on objects and the observer. The PU is highly sensitive to the orientation of the visual background: that is the preferred orientation for object recognition is critically influenced by the ambient visual environment. Which spatial frequency range carries the information that most influences the PU? METHOD: The PU is measured from the perceived identity of the character p/d. The orientations where one interpretation (p) changes to the other (d), are bisected to indicate the PU. Subjects were tested upright and supine whilst viewing the character against a highly polarized photograph of a natural scene displayed on a laptop computer whose screen was masked to a 42° circle viewed at 25 cms through a tube that obscured all peripheral vision. The influence of a tilted background picture was examined as a series of circular Gaussian blurs were applied to it at 2, 4, 8, 16 and 250 pixel widths. RESULTS: The influence of the visual background on the PU was initially about equal to that of gravity and about half that of the body. When we blurred the background image, the influence of the visual background on the PU systematically decreased at a rate independent of body posture, though the magnitude of effect remained reliably higher for supine observers. DISCUSSION: The systematic decrease of the influence of the visual environment as it is blurred suggests an important role for higher spatial frequencies and the detail they convey rather than the overall structure of the scene in providing cues that determine the perceptual 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 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".