MétaCan
Menu
Back to cohort
Record W2610537832 · doi:10.5555/2383654.2383689

Real illumination from virtual environments

2005· article· en· W2610537832 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

VenueEurographics Symposium on Rendering Techniques · 2005
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Vision and Imaging
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer scienceAdaptation (eye)EntertainmentSoftwareComputer graphics (images)High dynamic rangeRange (aeronautics)Computer visionHuman–computer interactionDynamic rangeArtificial intelligenceEngineeringOptics

Abstract

fetched live from OpenAlex

We introduce a method for actively controlling the illumination in a room so that it is consistent with a virtual world. In combination with a high dynamic range display, the system produces both uniform and directional illumination at intensity levels covering a wide range of real-world environments. It thereby allows natural adaptation processes of the human visual system to take place, for example when moving between bright and dark environments. In addition, the directional illumination provides additional information about the environment in the user's peripheral field of view.We describe both the hardware and the software aspects of our system. We also conducted an informal survey to determine whether users prefer the dynamic illumination over constant room illumination in an entertainment setting.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.639
Threshold uncertainty score0.891

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 communication0.0000.001
Open science0.0010.000
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 head0.012
GPT teacher head0.258
Teacher spread0.246 · 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