Three-dimensional TV: a novel method for generating surrogate depth maps using colour information
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
The ability to convert 2D video material to 3D would be extremely valuable for the 3D-TV industry. Such conversion might be achieved using depth maps extracted from the original 2D content. We previously demonstrated that surrogate depth maps with limited or imprecise depth information could be used to produce effective stereoscopic images. In the current study, we investigated whether gray intensity images associated with the Cr colour component of standard 2D-colour video sequences could be used effectively as surrogate depth maps. Colour component-based depth maps were extracted from ten video sequences and used to render images for the right-eye view. These were then combined with the original images for the left-eye view to form ten stereoscopic test sequences. A panel of viewers assessed the depth quality and the visual comfort of the synthesized test sequences and, for comparison, of monoscopic and camera-captured stereoscopic versions of the same sequences. The data showed that the ratings of depth quality for the synthesized test sequences were higher than those of the monoscopic versions, but lower than those of the camera-captured stereoscopic versions. For visual comfort, ratings were lower for the synthesized than for the monoscopic sequences but either equal to or higher than those of the camera-captured versions
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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 it