Interactive Context-Preserving Color Highlighting for Multiclass Scatterplots

TL;DR

This paper introduces an interactive method for color highlighting in multi-class scatterplots that preserves context and perceptual separability, enhancing visual exploration without sacrificing discriminability.

Contribution

It proposes a novel interactive approach combining two contrastive color schemes to improve highlighting while maintaining color consistency and separability.

Findings

Effective in maintaining class separability during highlighting

Improves visual pop-out of points of interest

Validated through crowd-sourced experiments and case studies

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.