English

Interactive Context-Preserving Color Highlighting for Multiclass Scatterplots

Human-Computer Interaction 2023-02-13 v1

Abstract

Color is one of the main visual channels used for highlighting elements of interest in visualization. However, in multi-class scatterplots, color highlighting often comes at the expense of degraded color discriminability. In this paper, we argue for context-preserving highlighting during the interactive exploration of multi-class scatterplots to achieve desired pop-out effects, while maintaining good perceptual separability among all classes and consistent color mapping schemes under varying points of interest. We do this by first generating two contrastive color mapping schemes with large and small contrasts to the background. Both schemes maintain good perceptual separability among all classes and ensure that when colors from the two palettes are assigned to the same class, they have a high color consistency in color names. We then interactively combine these two schemes to create a dynamic color mapping for highlighting different points of interest. We demonstrate the effectiveness through crowd-sourced experiments and case studies.

Keywords

Cite

@article{arxiv.2302.05368,
  title  = {Interactive Context-Preserving Color Highlighting for Multiclass Scatterplots},
  author = {Kecheng Lu and Khairi Reda and Oliver Deussen and Yunhai Wang},
  journal= {arXiv preprint arXiv:2302.05368},
  year   = {2023}
}

Comments

To appear in CHI'23: ACM Conference on Human Factors in Computing Systems

R2 v1 2026-06-28T08:37:14.102Z