• DocumentCode
    1784137
  • Title

    Intention prediction approach to interact naturally with the microworld

  • Author

    Cohen, Lawrence ; Haliyo, S. ; Chetouani, Mohamed ; Regnier, Stephane

  • Author_Institution
    Inst. des Syst. Intell. et de Robot., Univ. Pierre et Marie Curie - Paris 6, Paris, France
  • fYear
    2014
  • fDate
    8-11 July 2014
  • Firstpage
    396
  • Lastpage
    401
  • Abstract
    Micromanipulation tools are not yet commonly used in the industry or in the research due to the lack of natural and intuitive human-computer interfaces. This work proposes a vision based approach using a Kinect RGB-Depth sensor to provide a “metaphor-free” interface. An intention prediction approach is proposed, based on a cognitive science computational model, to allow a more natural interaction without any prior instructions. This model is compared to a vision based gesture recognition approach in terms of naturalness and intuitiveness. It shows an improvement in user performance in terms of duration and success of the task, and a qualitative preference for the proposed approach evaluated by a user survey.
  • Keywords
    gesture recognition; haptic interfaces; image sensors; Kinect RGB-depth sensor; cognitive science computational model; intention prediction approach; metaphor-free interface; microworld; vision based gesture recognition approach; Adhesives; Computational modeling; Gesture recognition; Haptic interfaces; Predictive models; Solid modeling; Virtual reality;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Intelligent Mechatronics (AIM), 2014 IEEE/ASME International Conference on
  • Conference_Location
    Besacon
  • Type

    conf

  • DOI
    10.1109/AIM.2014.6878111
  • Filename
    6878111