Distortions of Space in Stereoscopic 3D Content
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
In S3D film, many factors affect the relationship between the depth in the acquired scene and depth eventually produced by the stereoscopic display. Many are geometric including camera interaxial, camera convergence, lens properties, viewing distance and angle, screen/projector properties and anatomy (interocular). Spatial distortions follow at least in part from geometry (including the cardboard cut-out effect, miniaturization/gigantism, space-size distortion, and object-speed distortion), and can cause a poor S3D experience. However, it is naïve to expect spatial distortion to be specified only by geometry — visual experience is heavily influenced by perceptual and cognitive factors. This paper will review geometrical predictions and present the results of experiments which assess S3D distortions in the context of content, cognitive and perceptual influences, and individual differences. We will suggest ways to assess the influence of acquisition and display parameters and to mitigate unwanted perceptual phenomena.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 it