Image-Driven Harmonious Color Palette Generation for Diverse Information Visualization

Liu, Shuqi; Tao, Mingtian; Huang, Y.; Wang, Changbo; Li, Chenhui

doi:10.1109/tvcg.2022.3226218

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Tools For Designing Sequential Colormaps1

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2024

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“…Therefore, AIassisted tools have leveraged existing examples to guide colormap construction. For example, deep learning can enable colormap style transfer from existing images to new charts [37,64,76,77]. However, users may not have quality example images.…”

Section: Tools For Designing Sequential Colormapsmentioning

confidence: 99%

Cieran: Designing Sequential Colormaps via In-Situ Active Preference Learning

Hong,

Sunberg,

Szafir

2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

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Figure 1: Cieran's preference learning interface used with Altair [71]. Cieran supports efficient colormap selection within an analyst's workflow through integration with Jupyter Notebooks. Cieran first interpolates example colormaps through a chosen color (e.g., #186E8D, a teal blue shown in the progress bar). People iteratively input preferences to Cieran by making value judgements across pairs of examples, and Cieran uses the preference data to induce a context-specific model of aesthetic utility. This model used to rank and create colormaps.

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Section: Tools For Designing Sequential Colormapsmentioning

confidence: 99%