Object Speed Control with a Signed Distance Field for Distant Mid-Air Object Manipulation in Virtual Reality
Why this work is in the frame
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Bibliographic record
Abstract
In Virtual Reality (VR) applications, interacting with distant objects relies heavily on mid-air object manipulation. Yet, the inherent distance between the user and the object often restricts movement precision. This paper introduces the Signed Distance Field (SDF) method for mid-air object manipulation and combines it with the ray casting interaction technique to investigate its effect on user performance and user experience. To increase movement accuracy, we leverage the speed-accuracy trade-off to dynamically adjust object manipulation speed based on the SDF algorithm’s output. Our study with 18 participants examines the effects of SDF across three different tasks with different complexity. Our results showed that ray casting with SDF reduces the number of errors in complex tasks without slowing down the participants and improves the user experience. We hope that our proposed assistive system, designed for tasks and applications, can be used as an interaction technique to enable more accurate manipulation of distant objects in fields like surgical planning, architecture, and games.
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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 | 0.001 | 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