ColourID

Improving Colour Identification for People with Impaired Colour Vision

David Flatla, Alan R. Andrade, Ross D. Teviotdale, Dylan L. Knowles, Craig Stewart

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

    11 Citations (Scopus)

    Abstract

    Being able to identify colours is a fundamental human activity; colour identification helps us work, get dressed, prepare food, and keep safe. But for the 5% of the world with impaired colour vision (ICV), colour identification is often a challenge, resulting in frustration and confusion with sometimes dangerous consequences. Colour namer tools have been proposed as a solution, however these are often slow to use and imprecise. To address these shortcomings, we developed three new colour identification techniques (ColourNames, ColourMeters, ColourPopper) using a new colour name dictionary based on the largest colour naming experiment to date. We compared our techniques to colour namers using participants with ICV in desktop and mobile conditions, and found that ColourNames and ColourPopper resulted in ~99% colour identification accuracy (10% higher than the colour namer), ColourMeters and ColourPopper were three times faster, and ColourPopper had lower perceived effort and was ranked significantly higher. With the benefits provided by our new colour identification techniques, people with ICV are one step closer to seeing the world like everyone else.
    Original languageEnglish
    Title of host publicationCHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems
    PublisherAssociation for Computing Machinery
    Pages3543-3552
    Number of pages10
    ISBN (Print)9781450331456
    DOIs
    Publication statusPublished - 23 Apr 2015
    Event33rd Annual CHI Conference on Human Factors in Computing Systems - COEX, Seoul, Korea, Republic of
    Duration: 18 Apr 201523 Apr 2015
    http://chi2015.acm.org/

    Conference

    Conference33rd Annual CHI Conference on Human Factors in Computing Systems
    Abbreviated titleCHI 2015
    CountryKorea, Republic of
    CitySeoul
    Period18/04/1523/04/15
    Internet address

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    Color vision
    Color
    Glossaries

    Cite this

    Flatla, D., Andrade, A. R., Teviotdale, R. D., Knowles, D. L., & Stewart, C. (2015). ColourID: Improving Colour Identification for People with Impaired Colour Vision. In CHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (pp. 3543-3552). Association for Computing Machinery. https://doi.org/10.1145/2702123.2702578
    Flatla, David ; Andrade, Alan R. ; Teviotdale, Ross D. ; Knowles, Dylan L. ; Stewart, Craig. / ColourID : Improving Colour Identification for People with Impaired Colour Vision. CHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. Association for Computing Machinery, 2015. pp. 3543-3552
    @inproceedings{5bd850e1a52443deb9cb86ed25275671,
    title = "ColourID: Improving Colour Identification for People with Impaired Colour Vision",
    abstract = "Being able to identify colours is a fundamental human activity; colour identification helps us work, get dressed, prepare food, and keep safe. But for the 5{\%} of the world with impaired colour vision (ICV), colour identification is often a challenge, resulting in frustration and confusion with sometimes dangerous consequences. Colour namer tools have been proposed as a solution, however these are often slow to use and imprecise. To address these shortcomings, we developed three new colour identification techniques (ColourNames, ColourMeters, ColourPopper) using a new colour name dictionary based on the largest colour naming experiment to date. We compared our techniques to colour namers using participants with ICV in desktop and mobile conditions, and found that ColourNames and ColourPopper resulted in ~99{\%} colour identification accuracy (10{\%} higher than the colour namer), ColourMeters and ColourPopper were three times faster, and ColourPopper had lower perceived effort and was ranked significantly higher. With the benefits provided by our new colour identification techniques, people with ICV are one step closer to seeing the world like everyone else.",
    author = "David Flatla and Andrade, {Alan R.} and Teviotdale, {Ross D.} and Knowles, {Dylan L.} and Craig Stewart",
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    doi = "10.1145/2702123.2702578",
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    Flatla, D, Andrade, AR, Teviotdale, RD, Knowles, DL & Stewart, C 2015, ColourID: Improving Colour Identification for People with Impaired Colour Vision. in CHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. Association for Computing Machinery, pp. 3543-3552, 33rd Annual CHI Conference on Human Factors in Computing Systems, Seoul, Korea, Republic of, 18/04/15. https://doi.org/10.1145/2702123.2702578

    ColourID : Improving Colour Identification for People with Impaired Colour Vision. / Flatla, David; Andrade, Alan R.; Teviotdale, Ross D.; Knowles, Dylan L.; Stewart, Craig.

    CHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. Association for Computing Machinery, 2015. p. 3543-3552.

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

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    AU - Stewart, Craig

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    AB - Being able to identify colours is a fundamental human activity; colour identification helps us work, get dressed, prepare food, and keep safe. But for the 5% of the world with impaired colour vision (ICV), colour identification is often a challenge, resulting in frustration and confusion with sometimes dangerous consequences. Colour namer tools have been proposed as a solution, however these are often slow to use and imprecise. To address these shortcomings, we developed three new colour identification techniques (ColourNames, ColourMeters, ColourPopper) using a new colour name dictionary based on the largest colour naming experiment to date. We compared our techniques to colour namers using participants with ICV in desktop and mobile conditions, and found that ColourNames and ColourPopper resulted in ~99% colour identification accuracy (10% higher than the colour namer), ColourMeters and ColourPopper were three times faster, and ColourPopper had lower perceived effort and was ranked significantly higher. With the benefits provided by our new colour identification techniques, people with ICV are one step closer to seeing the world like everyone else.

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    Flatla D, Andrade AR, Teviotdale RD, Knowles DL, Stewart C. ColourID: Improving Colour Identification for People with Impaired Colour Vision. In CHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. Association for Computing Machinery. 2015. p. 3543-3552 https://doi.org/10.1145/2702123.2702578