Gaze-Contingent Multiresolutional Displays: An Integrative Review
Bibliographic record
Abstract
Gaze-contingent multiresolutional displays (GCMRDs) center high-resolution information on the user's gaze position, matching the user's area of interest (AOI). Image resolution and details outside the AOI are reduced, lowering the requirements for processing resources and transmission bandwidth in demanding display and imaging applications. This review provides a general framework within which GCMRD research can be integrated, evaluated, and guided. GCMRDs (or "moving windows") are analyzed in terms of (a) the nature of their images (i.e., "multiresolution," "variable resolution," "space variant," or "level of detail"), and (b) the movement of the AOI (i.e., "gaze contingent," "foveated," or "eye slaved"). We also synthesize the known human factors research on GCMRDs and point out important questions for future research and development. Actual or potential applications of this research include flight, medical, and driving simulators; virtual reality; remote piloting and teleoperation; infrared and indirect vision; image transmission and retrieval; telemedicine; video teleconferencing; and artificial vision systems.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".