Exploring Pointing and Confirmation Techniques for Teleportation Across Varying Elevations in Virtual Reality
Bibliographic record
Abstract
Teleportation in Virtual Reality (VR) is a locomotion technique that allows users to navigate between locations within a virtual environment instantly. Traditionally, VR teleportation is performed using physical controllers, where users control a teleportation pointer — represented by a straight line or parabola — and activate the teleportation to the target destination by pressing a button. Recent advances in hand and eye-tracking capabilities in Head-Mounted Displays (HMDs) enable designers to leverage hand and eye-based interactions to enhance the immersion and naturalness of controller-free VR usage. However, there has been limited research on comparing different controller-free methods for VR teleportation across various elevations. To address this gap, we conducted a user study exploring three controller-free pointing techniques (gaze, hand, and head), four confirmation modalities (finger pinch, eye-blink, dwell, and voice), and two types of teleportation pointers (linear and parabolic) for VR teleportation across various elevations. Our results show that head-based pointing was faster and more accurate than other techniques, with head and gaze achieving higher throughput than hand-based methods. For confirmation, finger pinch yielded the best performance in terms of task completion time and throughput, followed by dwell, voice, and eye-blink; dwell was the most accurate. The linear pointer outperformed the parabolic pointer in some contexts. Based on these findings, we propose design guidelines to enhance controller-free VR teleportation using various input modalities.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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 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".