Colorimetric background estimation for color blending reduction of OST-HMD

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

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

    8 Citations (Scopus)

    Abstract

    In an augmented reality scenario, the perceived image of OST-HMD contains color distortion due to background color blending. In order to reduce color blending, accurate estimation of background color is necessary. In this paper, we perform colorimetric estimation of background using camera images, via local linear regression. Using the estimated background color, virtual image is compensated. Experimental results show that the proposed colorimetric background estimation closely estimates the background color within an error of 1.635 degrees, and that the color blending reduction error typically falls under 5 degrees in most cases.

    Original languageEnglish
    Title of host publication2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Electronic)9789881476821
    DOIs
    Publication statusPublished - 2017 Jan 17
    Event2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016 - Jeju, Korea, Republic of
    Duration: 2016 Dec 132016 Dec 16

    Publication series

    Name2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016

    Other

    Other2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016
    Country/TerritoryKorea, Republic of
    CityJeju
    Period16/12/1316/12/16

    Bibliographical note

    Publisher Copyright:
    © 2016 Asia Pacific Signal and Information Processing Association.

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Science Applications
    • Information Systems
    • Signal Processing

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