Effect of a Constant Camera Rotation on the Visibility of Transsaccadic Camera Shifts
Bibliographic record
Abstract
Often in 3D games and virtual reality, changes in fixation occur during locomotion or other simulated head movements. We investigated whether a constant camera rotation in a virtual scene modulates saccadic suppression. The users viewed 3D scenes from the vantage point of a virtual camera which was either stationary or rotated at a constant rate about a vertical axis (camera pan) or horizontal axis (camera tilt). During this motion, observers fixated an object that was suddenly displaced horizontally/vertically in the scene, triggering them to produce a saccade. During the saccade an additional sudden movement was applied to the virtual camera. We estimated discrimination thresholds for these transsaccadic camera shifts using a Bayesian adaptive procedure. With an ongoing camera pan, we found higher thresholds (less noticeability) for additional sudden horizontal camera motion. Likewise, during simulated vertical head movements (i.e. a camera tilt), vertical transsaccadic image displacements were better hidden from the users for both horizontal and vertical saccades. Understanding the effect of continuous movement on the visibility of a sudden transsaccadic change can help optimize the visual performance of gaze-contingent displays and improve user experience.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 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".