The Role of Binocular Vision in Avoiding Virtual Obstacles While Walking
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Bibliographic record
Abstract
Advances in Virtual Reality technology have enabled physical walking in virtual environments. While most Virtual Reality systems render stereoscopic images to users, the implication of binocular viewing with respect to the performance of human walking in virtual environments remains largely unknown. In the present study, we conducted two walking experiments in virtual environments using a linear treadmill and a novel projected display known as the Wide Immersive Stereo Environment (WISE) to study the role of binocular viewing in virtual locomotion. The first experiment investigated the walking performance of people stepping over obstacles while the second experiment focused on a scenario on stepping over gaps. Both experiments were conducted under both stereoscopic viewing and non-stereoscopic viewing conditions. By analysing the gait parameters, we found that binocular viewing helped people to make more accurate movements to step over obstacles and gaps in virtual locomotion.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it