Publication: Individual Models of Color Differentiation to Improve Interpretability of Information Visualization

Color is commonly used to represent categories and values in many computer applications, but differentiating these colors can be difficult in many situations (e.g., for users with color vision deficiency (CVD), or in bright light). Current solutions to this problem can adapt colors based on standard simulations of CVD, but these models cover only a fraction of the ways in which color perception can vary. To improve the specificity and accuracy of these approaches, we have developed the first ever individualized model of color differentiation (ICD). The model is based on a short calibration performed by a particular user for a particular display, and so automatically covers all aspects of the user's ability to see and differentiate colors in an environment. In this paper we introduce the new model and the manner in which differentiability limits are predicted. We gathered empirical data from 16 users to assess the model's accuracy and robustness. We found that the model is highly effective at capturing individual differentiation abilities, works for users with and without CVD, can be tuned to balance accuracy and color availability, and can serve as the basis for improved color adaptation schemes.

Downloads

PDF

Participants

David Flatla
University of Dundee
Carl Gutwin
University of Saskatchewan

Projects

Colour Blindness and Information Visualization
Colour-blindness and information visualization are common enough that the interaction between the two has a substantial impact on everyday life.

Citation

Flatla, D.R., Gutwin, C. 2010. Individual Models of Color Differentiation to Improve Interpretability of Information Visualization. In CHI '10: Proceedings of the 28th international conference on Human factors in computing systems, Atlanta, Georgia, USA. 2563-2572. Honorable Mention Award. DOI=10.1145/1753326.1753715.

BibTeX

@inproceedings {171-CHI-2010,
author= {David Flatla and Carl Gutwin},
title= {Individual Models of Color Differentiation to Improve Interpretability of Information Visualization},
booktitle= {CHI '10: Proceedings of the 28th international conference on Human factors in computing systems},
year= {2010},
address= {Atlanta, Georgia, USA},
pages= {2563-2572},
note= {Honorable Mention Award}
}