End-to-end simulation process in lens design software for integral imaging-based 3D light field displays evaluation
Bibliographic record
Abstract
Currently, three-dimensional (3D) light field displays (LFDs) based on integral imaging (InIm) are one of the most interesting technologies in the field of 3D displays. The InIm principle consists of two key stages: the capture and reconstruction of the light field describing a specific 3D scene. However, these stages represent two distinct processes requiring different tools and resources, making the evaluation of InIm-based 3D LFDs a laborious and time consuming task. To address those problems, we propose an end-to-end simulation model developed in the commercial lens design software Ansys Zemax OpticStudio, that integrates the two stages of the InIm to facilitate the evaluation of the entire 3D image formation process. This work aims to provide a preliminary solution by ensuring that the targeted specifications are checked and achieved before embarking on the development of a costly and time-consuming prototype.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".