• DocumentCode
    607490
  • Title

    Democratizing 3D dynamic gestures recognition

  • Author

    Caon, M. ; Yong Yue ; Tscherrig, J. ; Khaled, O.A. ; Mugellini, E.

  • fYear
    2013
  • fDate
    15-17 Jan. 2013
  • Firstpage
    7
  • Lastpage
    12
  • Abstract
    Developing vision-based 3D gestures recognition systems requires strong expertise and knowledge in computer vision and machine learning techniques. As human-computer interaction researchers do not generally have a thorough knowledge of these techniques, we developed Gesta. Gesta is a tool that enables non-experts in vision computing and artificial intelligence techniques to rapidly develop a 3D gestures recognition system prototype and to support the gesture design process. This tool works with up to two Microsoft Kinects, and integrates the depth cameras calibration algorithm and the hidden Markov models classifier. The users can manage these complex functions through a simple graphical user interface, even if they do not have any expertise in computer vision and machine learning domains. A usability test with 12 researchers with experience in human-computer interaction has been conducted in order to evaluate the overall usability of this tool. Results demonstrate that the testers appreciated the Gesta tool which scored 88.9 points out of 100 in the Brooke´s system usability scale.
  • Keywords
    calibration; computer vision; gesture recognition; graphical user interfaces; hidden Markov models; human computer interaction; image sensors; learning (artificial intelligence); object recognition; 3D dynamic gestures recognition democratization; Brooke system usability scale; Gesta; Microsoft Kinects; artificial intelligence techniques; computer vision; depth cameras calibration algorithm; gesture design process; graphical user interface; hidden Markov models classifier; human-computer interaction; machine learning domains; machine learning techniques; usability test; vision computing; vision-based 3D gestures recognition systems; Cameras; Gesture recognition; Graphical user interfaces; Hidden Markov models; Human computer interaction; Skeleton; Three-dimensional displays;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    User-Centered Computer Vision (UCCV), 2013 1st IEEE Workshop on
  • Conference_Location
    Tampa, FL
  • Print_ISBN
    978-1-4673-5675-6
  • Electronic_ISBN
    978-1-4673-5674-9
  • Type

    conf

  • DOI
    10.1109/UCCV.2013.6530800
  • Filename
    6530800