Addressable spatial light modulators for eye-tracking autostereoscopic three-dimensional display using a scanning laser
Bibliographic record
Abstract
A scanning laser-based back light three-dimensional (3D) display capable of rendering full-resolution, low crosstalk, and vivid 3D depth perception has been developed by incorporating time-sequential multiplexing and eye-tracking technologies. This system includes three main subsystems: a scanning laser module, a relay transfer unit created by combining multiple transmissive-type electrically addressed ferroelectric liquid crystal spatial light modulators (FLC-SLMs), and a dual-directional transmission screen (DDTS) unit that can produce different angular magnification factors in both the tangential and sagittal planes. The light beam is directed by the DDTS after transmission through FLC-SLMs, and left and right eye viewing zones are produced sequentially in accordance with the locations of clear apertures in the FLC-SLM that are controlled based on data from the eye-tracking system. Owing to the persistence of human vision, 3D images are formed as a result of the high-speed scanning backlight and fast response characteristics of the FLC-SLM. A prototype of the proposed 3D display was designed and built, and experiments were carried out. The experimental results verify the feasibility of the proposed scheme, and full-resolution images with natural 3D perception are demonstrated by the 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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".