Individual models of color differentiation to improve interpretability of information visualization

David R. Flatla, Carl Gutwin

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    15 Citations (Scopus)

    Abstract

    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.

    Original languageEnglish
    Title of host publicationCHI '10 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
    Place of PublicationNew York, USA
    PublisherAssociation for Computing Machinery
    Pages2563-2572
    Number of pages10
    Volume4
    ISBN (Print)9781605589299
    DOIs
    Publication statusPublished - 10 Apr 2010
    Event28th Annual CHI Conference on Human Factors in Computing Systems, CHI 2010 - Atlanta, GA, United States
    Duration: 10 Apr 201015 Apr 2010

    Conference

    Conference28th Annual CHI Conference on Human Factors in Computing Systems, CHI 2010
    CountryUnited States
    CityAtlanta, GA
    Period10/04/1015/04/10

    Keywords

    • assistive technology
    • color blindness
    • color differentiation
    • color vision deficiency
    • visualization

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  • Cite this

    Flatla, D. R., & Gutwin, C. (2010). Individual models of color differentiation to improve interpretability of information visualization. In CHI '10 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Vol. 4, pp. 2563-2572). Association for Computing Machinery. https://doi.org/10.1145/1753326.1753715