• DocumentCode
    22077
  • Title

    Lightweight generic random ferns for multi-target augmented reality on mobile devices

  • Author

    Suwon Lee ; Yang, Hyung Suk

  • Author_Institution
    Dept. of Comput. Sci., KAIST, Daejeon, South Korea
  • Volume
    49
  • Issue
    13
  • fYear
    2013
  • fDate
    June 20 2013
  • Firstpage
    800
  • Lastpage
    802
  • Abstract
    Proposed use lightweight generic random ferns (LGRF), a fast keypoint classifier designed for multi-target augmented reality (AR) on mobile devices. LGRF uses binary features of image patches for both object recognition and keypoint matching of multiple objects, and stores probabilities in a single bit representation to reduce memory requirements. As a result, LGRF can perform simultaneous object recognition and keypoint matching in real time with low memory consumption, making it suitable for multi-target AR on mobile devices.
  • Keywords
    augmented reality; image matching; mobile handsets; real-time systems; LGRF; binary features; fast keypoint classifier; image patches; keypoint matching; lightweight generic random ferns; memory requirements reduction; mobile devices; multiple objects; multitarget AR; multitarget augmented reality; object recognition; real time; single bit representation;
  • fLanguage
    English
  • Journal_Title
    Electronics Letters
  • Publisher
    iet
  • ISSN
    0013-5194
  • Type

    jour

  • DOI
    10.1049/el.2013.0754
  • Filename
    6553025
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=22077