Guidelines for an improved quality of experience in 3‐D TV and 3‐D mobile displays
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
Abstract Stereoscopic (3‐D) movies have become widely popular all over the world. In addition, 3‐D TVs and mobile devices have already been introduced to the consumer market. However, while some manufacturers are introducing 3‐D cameras and movie studios are using proprietary solutions, there are no guidelines for consistently capturing high‐quality stereoscopic content. In this paper, a comprehensive stereoscopic image and video database with content captured at various distances from the camera lenses and under different lighting conditions will be presented. Subjective tests to assess the perceived 3‐D quality of these videos and images, which were shown on displays of different sizes, have been conducted. In addition, the horizontal parallax of the content was adjusted to verify via subjective tests whether this change could increase the viewer's quality of experience. Finally, guidelines of acquisition distances between the cameras and the real scene will be published.
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 | 0.001 | 0.001 |
| 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 | 0.002 |
| 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