A Window to Your Smartphone: Exploring Interaction and Communication in Immersive VR with Augmented Virtuality
Bibliographic record
Abstract
A major drawback of most Head Mounted Displays (HMDs) used in immersive Virtual Reality (VR) is the visual and social isolation of users from their real-world surroundings while wearing these headsets. This partial isolation of users from the real-world might hinder social interactions with friends and family. To address this issue, we present a new method to allow people wearing VR HMDs to use their smartphones or tablets without removing their HMDs. To do this, we augment the scene inside the VR HMD with a view of the user's device so that the user can interact with the device without removing the headset. The idea involves the use of additional cameras, such as the Leap Motion device or a high-resolution RGB camera to capture the user's real-world surrounding and augment the virtual world with the content displayed on the smartphone screen. This setup allows VR users to have a window to their smartphone from within the virtual world and afford all of the functionality provided by their smartphones, with the potential to reduce some of the undesirable isolation users may experience when using immersive VR systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".