Chromaticity Based Local Linear Regression for Color Distortion Estimation of Optical See-Through Displays

Kang Kyu Lee, Jae Woo Kim, Je Ho Ryu, Jong-Ok Kim

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

    5 Citations (Scopus)

    Abstract

    Optical See-Through displays (OST Displays) require the appearance of the virtual content to closely resemble that of the real world. However, current OST displays typically show color distortion due to hardware limitations. To overcome this problem, we propose a chromaticity based local linear regression model for color distortion estimation of OST displays. From our initial experiments, it was observed that local samples with similar chromaticity can be modeled more linearly rather than simple nearest neighbors in a color space. We argue that the accuracy of local linear regression can be further improved by placing emphasis on similarity of chromaticity. Experimental results showed that the proposed chromaticity based color correction achieves higher accuracy compared to the nearest neighbor method, for any training set size or neighborhood size as well as global regression. It confirms that chromaticity based nearest neighbors can be modeled more linearly together than simple nearest neighbors in a color space.

    Original languageEnglish
    Title of host publicationAdjunct Proceedings of the 2016 IEEE International Symposium on Mixed and Augmented Reality, ISMAR-Adjunct 2016
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages151-153
    Number of pages3
    ISBN (Electronic)9781509037407
    DOIs
    Publication statusPublished - 2017 Jan 30
    Event15th Adjunct IEEE International Symposium on Mixed and Augmented Reality, ISMAR-Adjunct 2016 - Merida, Yucatan, Mexico
    Duration: 2016 Sept 182016 Sept 23

    Other

    Other15th Adjunct IEEE International Symposium on Mixed and Augmented Reality, ISMAR-Adjunct 2016
    Country/TerritoryMexico
    CityMerida, Yucatan
    Period16/9/1816/9/23

    Keywords

    • augmented reality
    • color correction
    • color distortion model
    • local linear regression
    • OST Display

    ASJC Scopus subject areas

    • Computer Science Applications
    • Human-Computer Interaction
    • Media Technology
    • Computer Graphics and Computer-Aided Design

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