Effects of Field of View on Dynamic Out-of-View Target Search in Virtual Reality
Bibliographic record
Abstract
We present a study of the effects of field of view (FOV), target movement, and number of targets on visual search performance in virtual reality. We compared visual search tasks in two FOVs (~65°, ~32.5°) under two target movement speeds (static, dynamic) while varying the visible target count, with targets potentially out of the user’s view. We examined the expected linear relationship between search time and number of items, to explore how moving and/or out-of-view targets affected this relationship. Overall, search performance increased with a wide FOV, but decreased when targets were moving and with more visible targets. FOV more strongly influenced search performance than target movement. Neither FOV nor target movement meaningfully altered the linear relationship between visual search time and number of items. Participants also rated perceived workload for each condition; FOV and target movement both negatively affected the perceived workload, with target movement being a more significant factor.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".