Color Orchestra: Ordering Color Palettes for Interpolation and Prediction

Huy Phan, Hongbo Fu, Antoni Chan

Research output: Contribution to journalArticle

Abstract

Color theme or color palette can deeply influence the quality and the feeling of a photograph or a graphical design. Although color palettes may come from different sources such as online crowd-sourcing, photographs and graphical designs, in this paper, we consider color palettes extracted from fine art collections, which we believe to be an abundant source of stylistic and unique color themes. We aim to capture color styles embedded in these collections by means of statistical models and to build practical applications upon these models. As artists often use their personal color themes in their paintings, making these palettes appear frequently in the dataset, we employed density estimation to capture the characteristics of palette data. Via density estimation, we carried out various predictions and interpolations on palettes, which led to promising applications such as photo-style exploration, real-time color suggestion, and enriched photo recolorization. It was, however, challenging to apply density estimation to palette data as palettes often come as unordered sets of colors, which make it difficult to use conventional metrics on them. To this end, we developed a divide-and-conquer sorting algorithm to rearrange the colors in the palettes in a coherent order, which allows meaningful interpolation between color palettes. To confirm the performance of our model, we also conducted quantitative experiments on datasets of digitized paintings collected from the Internet and received favorable results.
LanguageEnglish
Pages1942-1955
Number of pages14
JournalIEEE Transactions on Visualization and Computer Graphics
Volume24
Issue number6
Early online date25 Apr 2017
DOIs
StatusPublished - 1 Jun 2018

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Color Orchestra : Ordering Color Palettes for Interpolation and Prediction. / Phan, Huy; Fu, Hongbo; Chan, Antoni.

In: IEEE Transactions on Visualization and Computer Graphics, Vol. 24, No. 6, 01.06.2018, p. 1942-1955.

Research output: Contribution to journalArticle

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