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Record W2560216520 · doi:10.1117/1.jei.26.1.011014

Chromatic modulation in visual art: a computational perspective

2016· article· en· W2560216520 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

VenueJournal of Electronic Imaging · 2016
Typearticle
Languageen
FieldNeuroscience
TopicAesthetic Perception and Analysis
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsHuePalette (painting)Color spacePaintingComputer sciencePerspective (graphical)Artificial intelligenceComputer visionChromatic scaleColor visionColor imageMonochromatic colorLightnessRGB color modelFalse colorColor balanceFocus (optics)Computer graphics (images)ArtMathematicsImage processingImage (mathematics)Visual artsOptics

Abstract

fetched live from OpenAlex

This paper describes a computational approach for analyzing and visualizing the aesthetics of color from the perspective of color theory. Our study is grounded in the works of Johannes Itten, one of the most remarkable theorists of color aesthetics. Our focus lies on the computational analysis of a specific aspect of color usage in paintings, namely modulation. We, therefore, propose the three-dimensional (3-D) color palette, a visualization of the chromatic information of an image in the hue-saturation-lightness space. Using the proposed palette, we derive a set of simple hue-specific descriptors for color modulation. Our experimental results involve a selection of digital reproductions of paintings discussed extensively by Itten. They show that the proposed modulation measures yield results that are consistent with Itten’s comments and explanations. Future work involves further exploration of the proposed 3-D color palette, in terms of its ability to discriminate between different artists and painting styles.

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 score0.881
Threshold uncertainty score0.205

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 head0.009
GPT teacher head0.296
Teacher spread0.287 · 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