Contextual lighting cues can override the light-from-above prior
Bibliographic record
Abstract
When the direction of illumination is unknown, the human visual system uses a light-from-above prior to infer the shape of ambiguous shaded images. Can this prior be overridden by contextual lighting cues that indicate the true lighting direction in a specific scene? Previous studies have given mixed results. We re-examined this question using realistic renderings of complex scenes under a range of lighting conditions. METHODS: Stimuli were computer-rendered scenes of geometric objects. Simulated lighting in each scene consisted of a distant point source and an ambient source. The direction of the point source varied from scene to scene. The strength of the directional lighting cues was varied by modulating the relative strength of the point and ambient sources. Observers judged whether ambiguously shaded disks shown on the geometric objects at various orientations were convex or concave. We used these judgements to infer what lighting direction observers' shape-from-shading mechanisms assumed to be dominant in each scene. RESULTS: When scene lighting was direct (i.e. point source strong, ambient source weak), the lighting direction assumed by observers closely tracked the true lighting direction. When lighting was diffuse, large individual differences appeared: some observers' shape judgements of ambiguous shaded disks were independent of disk orientation, and some observers had preferred lighting directions that were neither directly above nor in the direction of the direct component of the light source. CONCLUSIONS: Strong directional lighting cues can override the light-from-above prior: observers interpret ambiguous shaded objects as if illuminated from the direction indicated by the lighting cues. Weak directional lighting can also override the light-from-above prior: surprisingly, the light-from-above prior does not guide shape judgements even in the presence of directional lighting cues that are insufficiently strong to guide observers' estimates of the dominant lighting direction in a scene.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".