Mug Shots: Systematic Biases in the Perception of Facial Orientation within Pictorial Spaces
Bibliographic record
Abstract
Pictures are 2-D projections of a 3-D world, so pictorial spaces behave differently than the 3-D visual spaces we inhabit. For instance, the angular orientation of a face pictured in half-profile view is systematically overestimated by the human observer – a 35° view is estimated to be approximately 45°. What is the cause for this perceptual orientation bias? We tested three different hypotheses. (1) The phenomenon is specific to pictorial projections due to the twofoldness of the medium and does not occur in 3-D space. (2) It can be explained with the depth compression expected when the vantage point of the observer is closer to the picture than the point of projection. (3) The visual system uses a shape prior that does not match the elliptical horizontal cross section of a typical head. Our results support the third hypothesis, and this effect can be mitigated through adding geometric information through structure-from-motion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".