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Record W4367300931 · doi:10.1117/12.2671432

Design and research of VR interactive game based on mirror elements

2023· article· en· W4367300931 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
FieldEngineering
TopicSimulation and Modeling Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer scienceHuman–computer interactionVirtual realityGame designMultimediaComputer graphics (images)

Abstract

fetched live from OpenAlex

It is well known that the reflection of mirrors can provide spatial perception, and this visual experience can increase immersion in VR. However, it is a challenge to integrate the mirror element, where reflection is the only feature, into an interactive VR game. This paper is a new attempt to put multiple mirror puzzles into VR environments using four game mechanics of mirrors, namely, single reflection, recursion, light path change, and duplicated spacing. Three major levels were designed using these mechanics, the Mirror Maze, the Laser Puzzle, and the Key to Yin and Yang. The findings of the game experience demonstrate that the combination of audio-visual interaction increases the immersion of the game, the easy-to-understand puzzle solutions meet the comfort level of the player experience, and the combination of east-west elements enriches the quality of the game. Overall, this is a game design attempt worthy of being studied, and it is feasible to disperse a single feature of the mirror into multiple mechanisms to add to the player experience for an interactive game.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.502
Threshold uncertainty score0.109

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 head0.181
GPT teacher head0.421
Teacher spread0.240 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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