Effects of image intensifier halo on perceived layout
Bibliographic record
Abstract
Night vision devices (NVDs) or night-vision goggles (NVGs) based on image intensifiers improve nighttime visibility and extend night operations for military and increasingly civil aviation. However, NVG imagery is not equivalent to daytime vision and impaired depth and motion perception has been noted. One potential cause of impaired perceptions of space and environmental layout is NVG halo, where bright light sources appear to be surrounded by a disc-like halo. In this study we measured the characteristics of NVG halo psychophysically and objectively and then evaluated the influence of halo on perceived environmental layout in a simulation experiment. Halos are generated in the device and are not directly related to the spatial layout of the scene. We found that, when visible, halo image (i.e. angular) size was only weakly dependent on both source intensity and distance although halo intensity did vary with effective source intensity. The size of halo images surrounding lights sources are independent of the source distance and thus do not obey the normal laws of perspective. In simulation experiments we investigated the effect of NVG halo on judgements of observer attitude with respect to the ground during simulated flight. We discuss the results in terms of NVG design and of the ability of human operators to compensate for perceptual distortions.
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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 | 0.009 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".