Canonical perspectives of rendered 3D objects are related to affordance
Bibliographic record
Abstract
Humans prefer to view objects from some but not other perspectives. Palmer, Rosch, and Chase (1981) were first to use the term “canonical perspectives” to describe these preferred viewing angles. More recently, this phenomenon has been studied as it relates to perspective invariance, object identification (human & algorithmic), and navigation. Contemporary studies rely on some of the foundational observations of early canonical perspective research. However, those original results are contradictory in several respects. Past literature includes contradictory findings on between-observer agreement on preferred perspectives, reaction time effects, and support for mental rotation theories of 3D object perception. To address those contradictions and improve our understanding of canonical perspectives, we constructed a digital dataset of three-dimensional objects from three categories: graspable familiar objects, non-graspable familiar objects, and graspable unfamiliar objects. We rendered the objects as viewed from 26 different orientations, covering the full range of viewing angles. We collected canonical perspective ratings via a pairwise comparison task, where participants indicated their preference between two displayed views in a two-alternative, forced-choice task. We presented 325 pairs of views of each object. Ratings were highly consistent between observers. Some viewing angles of graspable objects (e.g., coffee mug) were rated differently between left- and right-handed participants, based on experienced handle placement. This result indicates a significant connection between canonical perspective and affordance. We see a similar, although slightly weaker effect when comparing canonical viewing angles between participants of different body height. Taller participants are biased toward views from the top, smaller participants to views from the front. In summary, our results suggest that viewing angle influences people’s aesthetic preference for viewing objects, and that the preferred canonical perspective is frequently related to the individually specific affordance of a particular view.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".