• DocumentCode
    687465
  • Title

    A Hand Gesture Recognition System Based on GMM Method for Human-Robot Interface

  • Author

    Yihsin Ho ; Nishitani, Takashi ; Yamaguchi, Toru ; Sato-Shimokawara, Eri ; Tagawa, Norio

  • Author_Institution
    Fac. of Syst. Design, Tokyo Metropolitan Univ., Tokyo, Japan
  • fYear
    2013
  • fDate
    10-12 Dec. 2013
  • Firstpage
    291
  • Lastpage
    294
  • Abstract
    This paper proposes a hand gesture recognition system for human-robot interface. Our research aims to provide users user-friendly operations in a more intuitive manner. We use the stereo camera to capture images as the primary source of information retrieval, and adapt Gaussian mixture model (GMM) method as the main method of image analysis. The GMM method we applied in this paper is a precise, stable and computationally efficient foreground segment method. Our system is mainly with the following three steps: take video by camera, obtain user´s images based on GMM method, and recognize hand gesture. In this paper, we will focus on describing the system´s overall concepts and GMM method. An experiment result of our prototype will also be discussed to show the research potential of our system.
  • Keywords
    Gaussian processes; gesture recognition; human computer interaction; human-robot interaction; image capture; image segmentation; mixture models; stereo image processing; GMM method; Gaussian mixture model method; foreground segment method; hand gesture recognition system; human-robot interface; image analysis; image capture; information retrieval; stereo camera; user-friendly operation; Cameras; Educational institutions; Gaussian distribution; Gesture recognition; Robots; System analysis and design; Transforms; Gaussian Mixture Model; Hand gesture recognition; Human-robot interface;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robot, Vision and Signal Processing (RVSP), 2013 Second International Conference on
  • Conference_Location
    Kitakyushu
  • Print_ISBN
    978-1-4799-3183-5
  • Type

    conf

  • DOI
    10.1109/RVSP.2013.72
  • Filename
    6830032