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Record W4232278619 · doi:10.19153/cleiej.16.3.8

Production Framework for Full Panoramic Scenes with Photorealistic Augmented Reality

2013· article· en· W4232278619 on OpenAlexafffund
Dalai Felinto, Aldo René Zang, Luiz Velho

Bibliographic record

VenueCLEI electronic journal · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topic3D Surveying and Cultural Heritage
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsComputer graphics (images)Computer scienceFilmmakingComputer graphicsNoveltyRepresentation (politics)Augmented realityComputer visionArtificial intelligenceReflection (computer programming)Visual artsArt

Abstract

fetched live from OpenAlex


 
 
 The novelty of our proposal is the end-to-end solution to combine computer generated elements and captured panoramas. This framework supports productions specially aimed at spherical dis- plays (e.g., fulldomes). Full panoramas are popular in the computer graphics industry. However their common usage on environment lighting and reflection maps are often restrict to conven- tional displays. With a keen eye in what may be the next trend in the filmmaking industry, we address the particularities of those productions, exploring a new representation of the space by storing the depth together with the light map, in a full panoramic light-depth map.
 
 

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)0.001
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 score0.480
Threshold uncertainty score0.773

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.019
GPT teacher head0.237
Teacher spread0.218 · 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 designObservational
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

Citations4
Published2013
Admission routes2
Has abstractyes

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