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Record W2620895479 · doi:10.1002/sdtp.11574

8‐3: <i>Invited Paper</i> : Light Steering Projection Systems and Attributes for HDR Displays

2017· article· en· W2620895479 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

VenueSID Symposium Digest of Technical Papers · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicColor Science and Applications
Canadian institutionsBC Innovation CouncilUniversity of British Columbia
Fundersnot available
KeywordsGamutLuminanceComputer scienceComputer graphics (images)ProjectorBrightnessComputer visionChromatic scaleBacklightArtificial intelligenceDigital Light ProcessingOpticsLiquid-crystal displayPhysics

Abstract

fetched live from OpenAlex

New light steering projectors in cinema form images by moving light away from dark regions into bright areas of an image. In these systems, the peak luminance of small features can far exceed full screen white luminance. In traditional projectors where light is filtered or blocked in order to give shades of gray (or colors), the peak luminance is fixed. The luminance of chromatic features benefit in the same way as white features, and chromatic image details can be reproduced at high brightness leading to a much wider overall color gamut coverage than previously possible. Projectors of this capability are desired by the creative community to aid in and enhance storytelling. Furthermore, reduced light source power requirements of light steering projectors provide additional economic and environmental benefits. While the dependency of peak luminance level on (bright) image feature size is new in the digital cinema space, display technologies with identical characteristics such as OLED, LED LCD and Plasma TVs are well established in the home. Similarly, direct view LED walls are popular in events, advertising and architectural markets. To enable consistent color reproduction across devices in today’s content production pipelines, models that describe modern projectors and display attributes need to evolve together with HDR standards and available metadata. This paper is a first step towards rethinking legacy display descriptors such as contrast, peak luminance and color primaries in light of new display technology. We first summarize recent progress in the field of light steering projectors in cinema and then, based on new projector and existing display characteristics propose the inclusion of two simple display attributes: Maximum Average Luminance and Peak (Color) Primary Luminance. We show that the proposed attributes allow a better prediction of content reproducibility on HDR displays. To validate this assertion, we test professional content on a commercial HDR television system and show that the proposed attributes better predict if a pixel value lies inside the capabilities of a display or not.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score0.455

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 studies0.0010.000
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 head0.013
GPT teacher head0.264
Teacher spread0.251 · 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