Shape-from-Shading Depends on Visual, Gravitational, and Body-Orientation Cues
Bibliographic record
Abstract
The perception of shading-defined form results from an interaction between shading cues and the frames of reference within which those cues are interpreted. In the absence of a clear source of illumination, the definition of 'up' becomes critical to deducing the perceived shape from a particular pattern of shading. In our experiments, twelve subjects adjusted the orientation of a planar disc painted with a linear luminance gradient from one side to the other, until the disc appeared maximally convex-that is, until the luminance gradient induced the maximum perception of a three-dimensional shape. The vision, gravity, and body-orientation cues were altered relative to each other. Visual cues were manipulated by the York Tilted Room facility, and body cues were altered by simply lying on one side. The orientation of the disc that appeared maximally convex varied in a systematic fashion with these manipulations. We present a model in which the direction of perceptual 'up' is determined from the sum of three weighted vectors corresponding to the vision, gravity, and body-orientation cues. The model predicts the perceived direction of 'up', contributes to our understanding of how shape-from-shading is deduced, and also predicts the confidence with which the 'up' direction is perceived.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".