• DocumentCode
    3447482
  • Title

    Static Human Gesture grading based on Kinect

  • Author

    Linwan Liu ; Xiaoyu Wu ; Linglin Wu ; Tianchu Guo

  • Author_Institution
    Dept. of Digital Media Technol., Commun. Univ. of China, Beijing, China
  • fYear
    2012
  • fDate
    16-18 Oct. 2012
  • Firstpage
    1390
  • Lastpage
    1393
  • Abstract
    We presented a static human gesture grading system based on the skeletal tracking module of Kinect sensor. We captured the 2-D skeleton wireframe of a poser´s body and represented the data as limb vectors. The distance metric is defined as the included angle array computed between the real-time and the standard gesture. We proposed a grading formula to simulate the gesture judging scenario, of which the parameters can be adaptively computed or manually set. The system worked efficiently under the low computational complexity and was robust to input noise.
  • Keywords
    gesture recognition; image classification; image sensors; pose estimation; target tracking; 2D skeleton wireframe; Kinect sensor; angle array; distance metric; gesture classification; gesture judging scenario; human pose recognition; limb vectors; low computational complexity; poser body; realtime gesture; skeletal tracking module; standard gesture; static human gesture grading system; Arrays; Humans; Legged locomotion; Real-time systems; Skeleton; Standards; Vectors; Kinect; gesture grading; limb vectors; skeleton data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing (CISP), 2012 5th International Congress on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4673-0965-3
  • Type

    conf

  • DOI
    10.1109/CISP.2012.6469917
  • Filename
    6469917