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Record W2985297325 · doi:10.1145/3359996.3364264

Is the Pen Mightier than the Controller? A Comparison of Input Devices for Selection in Virtual and Augmented Reality

2019· article· en· W2985297325 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsAugmented realitySelection (genetic algorithm)Computer scienceVirtual realityHuman–computer interactionController (irrigation)Computer graphics (images)Artificial intelligenceBiology

Abstract

fetched live from OpenAlex

Controllers are currently the typical input device for commercial Virtual Reality (VR) systems. Yet, such controllers are not as efficient as other devices, including the mouse. This motivates us to investigate devices that substantially exceed the controller’s performance, for both VR and Augmented Reality (AR) systems. We performed a user study to compare several input devices, including a mouse, controller, and a 3D pen-like device on a VR and AR pointing task. Our results show that the 3D pen significantly outperforms modern VR controllers in all evaluated measures and that it is comparable to the mouse. Participants also liked the 3D pen more than the controller. Finally, we show how 3D pen devices could be integrated into today’s VR and AR systems.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.485
Threshold uncertainty score0.140

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.314
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations110
Published2019
Admission routes1
Has abstractyes

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