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Record W4318605712 · doi:10.1109/aivr56993.2022.00030

Active Visualization of Visual Cues on Hand for Better User Interface Design Generalization in Mixed Reality

2022· article· en· W4318605712 on OpenAlexaff
Muhammad Hassan Raza, Derek Reilly, Joseph Malloch

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsDalhousie University
Fundersnot available
KeywordsComputer scienceHuman–computer interactionAugmented realitySensory cueVisualizationMixed realityGeneralizationVirtual realityComponent (thermodynamics)User interfaceInterface (matter)User experience designArtificial intelligence

Abstract

fetched live from OpenAlex

With the emergence of various unique augmented reality devices, researchers are exploring how mixed-reality applications can enhance user experience. We propose a working prototype emphasizing that mixed reality applications should consider incorporating visual cues on the user’s hand for better user experience, in our case representing selected color on the index fingertip. Such a design can assist users in being attentive regarding what color they are using. Eventually, reducing unintended errors occur when the active visual component is not visible in the field of view. Generally, we argue that representing visual cues on the user’s hand has major advantages, including defining a general platform for placing visual cues, immediate response, and preserving computational resources. Most importantly, developers can utilize the general platform to give or place visual feedback in mixed-reality applications. Moreover, we highlight the importance of interacting in mid-air compared to tactile feedback.

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.

How this classification was reachedexpand

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.850
Threshold uncertainty score0.381

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 head0.039
GPT teacher head0.338
Teacher spread0.299 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2022
Admission routes1
Has abstractyes

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