Sensitivity to Monocular Occlusions in Stereoscopic Imagery: Implications for S3D Content Creation, Distribution and Exhibition
Bibliographic record
Abstract
Since S3D requires two views of a scene, one for each eye, transformations such as reseating, 2D to S3D conversion, synthesis of multiview displays, coding and ADAT communications efficiency require generation of new views from 2D images. One of the main challenges to this process is the identification and treatment of monocularly occluded regions. In natural environments, monocular occlusions occur whenever objects are partially obstructed by other objects in a scene, giving rise to a region that is visible to only one eye. Experiments have shown that these regions influence depth percepts. Importantly, if monocular occlusion regions are presented with texture that is inconsistent with the surrounding regions, or with inappropriate geometry, depth is degraded. This paper will review the geometric basis of monocular occlusions and their role in natural depth perception. The analysis will be framed in the context of the reconstruction of novel and appropriate viewpoints from sequences of 2D images from one or more vantage points.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".