• DocumentCode
    507771
  • Title

    Gesture Recognition System Based on Acceleration Data for Robocup Referees

  • Author

    Lo, Charles ; Cao, Qixin ; Zhu Xiao Xiao ; Zhang Zhen

  • Author_Institution
    Res. Inst. of Robot., Shanghai Jiaotong Univ., Shanghai, China
  • Volume
    2
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    149
  • Lastpage
    153
  • Abstract
    In this paper, we present a proof-of-concept gesture recognition based on artificial neural networks (ANN) for referees participating in the Robocup competitions. Here, we aim at recognizing gestures to interact with an application (Robocup referee box) and present the design and evaluation of our sensor-based gesture recognition. As input device we employ the Wii-controller (Wiimote) and the use of the iPhone, both of which recently gained much attention world-wide. We use both devices´ independent acceleration data for gesture recognition. The system allows the training of arbitrary gestures by users which can then be recalled for interacting with the systems. We exploit the devices´ sensor data and employ an artificial neural network model for training and recognizing user-chosen gestures. Our evaluation shows that our system is intuitive and easy to use.
  • Keywords
    artificial intelligence; gesture recognition; human computer interaction; mobile handsets; mobile robots; multi-robot systems; Robocup competitions; Robocup referee box; Wii-controller; artificial neural network model; device independent acceleration data; device sensor data; iPhone; proof-of-concept gesture recognition system; sensor-based gesture recognition; Acceleration; Application software; Artificial neural networks; Computer interfaces; Computer vision; Costs; Delay; Hardware; Mice; Robots; gesture recognition; iphone; robocup; wiimote;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2009. ICNC '09. Fifth International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-0-7695-3736-8
  • Type

    conf

  • DOI
    10.1109/ICNC.2009.691
  • Filename
    5362986