IEEE VIS 2024 Content: Dynamic Color Assignment for Hierarchical Data

Honorable Mention

Dynamic Color Assignment for Hierarchical Data

Jiashu Chen - Tsinghua University, Beijing, China

Weikai Yang - Tsinghua University, Beijing, China

Zelin Jia - Tsinghua University, Beijing, China

Lanxi Xiao - Tsinghua University, Beijing, China

Shixia Liu - Tsinghua University, Beijing, China

Room: Bayshore II

2024-10-16T18:09:00Z GMT-0600 Change your timezone on the schedule page
2024-10-16T18:09:00Z
Exemplar figure, described by caption below
Based on user exploration, our method dynamically selects the color range and assigns colors to classes within the range, which ensures high discriminability and harmony at each level and maintains consistency across different levels.
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Keywords

Color assignment, Hierarchical Visualization, Discriminability, Harmony.

Abstract

Assigning discriminable and harmonic colors to samples according to their class labels and spatial distribution can generate attractive visualizations and facilitate data exploration. However, as the number of classes increases, it is challenging to generate a high-quality color assignment result that accommodates all classes simultaneously. A practical solution is to organize classes into a hierarchy and then dynamically assign colors during exploration. However, existing color assignment methods fall short in generating high-quality color assignment results and dynamically aligning them with hierarchical structures. To address this issue, we develop a dynamic color assignment method for hierarchical data, which is formulated as a multi-objective optimization problem. This method simultaneously considers color discriminability, color harmony, and spatial distribution at each hierarchical level. By using the colors of parent classes to guide the color assignment of their child classes, our method further promotes both consistency and clarity across hierarchical levels. We demonstrate the effectiveness of our method in generating dynamic color assignment results with quantitative experiments and a user study.