Color Maker: a Mixed-Initiative Approach to Creating Accessible Color Maps

要旨

Quantitative data is frequently represented using color, yet designing effective color mappings is a challenging task, requiring one to balance perceptual standards with personal color preference. Current design tools either overwhelm novices with complexity or offer limited customization options. We present ColorMaker, a mixed-initiative approach for creating colormaps. ColorMaker combines fluid user interaction with real-time optimization to generate smooth, continuous color ramps. Users specify their loose color preferences while leaving the algorithm to generate precise color sequences, meeting both designer needs and established guidelines. ColorMaker can create new colormaps, including designs accessible for people with color-vision deficiencies, starting from scratch or with only partial input, thus supporting ideation and iterative refinement. We show that our approach can generate designs with similar or superior perceptual characteristics to standard colormaps. A user study demonstrates how designers of varying skill levels can use this tool to create custom, high-quality colormaps. ColorMaker is available at: https://colormaker.org

著者
Amey A. Salvi
Indiana University, Indianapolis, Indiana, United States
Kecheng Lu
Shandong University, Qingdao, Shandong, China
Michael E.. Papka
Argonne National Laboratory, Lemont, Illinois, United States
Yunhai Wang
Shandong University, Qingdao, China
Khairi Reda
Indiana University, Indianapolis, Indiana, United States
論文URL

https://doi.org/10.1145/3613904.3642265

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Colors

313B
5 件の発表
2024-05-15 01:00:00
2024-05-15 02:20:00