Optimized Image Synthesis for Multi-Projector-Type Light Field Display
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
Conventional light field displays suffer from the problem that severe distortion is perceived when the scenes are reconstructed far from the focused screen, due to the angular information loss in the reconstruction process. We introduce a weighted average optimization to the image synthesis process, aiming to tradeoff the reconstructed depth range and the image sharpness without changing the hardware configuration, particularly for multi-projector-type light field displays. The proposed optimization evaluates the lost angular information and reallocates them in the rendering process. The RMSE evaluation on the optimization performance is implemented. The experimental results show that after the optimization the display offers more accurate reconstruction than before. Besides, a subjective experiment is implemented to further validate the effectiveness of the optimization. We envision this optimization being applied to various multi-projector-type light field displays, despite of the arrangement of projectors and the shape of the screen.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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