Shape perception of thin transparent objects with stereoscopic viewing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Many materials, including water surfaces, jewels, and glassware exhibit transparent refractions. The human visual system can somehow recover 3D shape from refracted images. While previous research has elucidated various visual cues that can facilitate visual perception of transparent objects, most of them focused on monocular material perception. The question of shape perception of transparent objects is much more complex and few studies have been undertaken, particular in terms of binocular vision. In this article, we first design a system for stereoscopic surface orientation estimation with photo-realistic stimuli. It displays pre-rendered stereoscopic images and a real-time S3D (Stereoscopic 3D) shape probe simultaneously. Then we estimate people's perception of the shape of thin transparent objects using a gauge figure task. Our results suggest that people can consistently perceive the surface orientation of thin transparent objects, and stereoscopic viewing improves the precision of estimates. To explain the results, we present an edge-aware orientation map based on image gradients and structure tensors to illustrate the orientation information in images. We also decomposed the normal direction of the surface into azimuth angle and slant angle to explain why additional depth information can improve the accuracy of perceived normal direction.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 it