• DocumentCode
    529534
  • Title

    Human motion recognition using directional motion history images

  • Author

    Murakami, Makoto ; Tan, Joo Kooi ; Kim, Hyoungseop ; Ishikawa, Seiji

  • Author_Institution
    Dept. of Mech. & Control Eng., Kyusyu Inst. of Technol., Kitakyusyu, Japan
  • fYear
    2010
  • fDate
    18-21 Aug. 2010
  • Firstpage
    1512
  • Lastpage
    1514
  • Abstract
    Nowadays many persons are needed to observe images from surveillance cameras, because many surveillance cameras are installed in a town or in buildings. They are working under stress, because they must always watch the images from surveillance cameras to find a person with abnormal motion. Therefore reduction of the load is necessary. Many existing researches on human motion recognition are only recognition and the information of the result is not used. We assume that human motion is a set of basic motions. So, we think we are able to translate an overall motion using the recognition result of basic motions. The goal of the present research is to develop a method of human motion representation and translation using directional motion history images (DMHIs). In this paper, we describe a method of recognizing basic motions using the DMHIs. We perform the recognition by matching of a graph. When the matching of the graph is performed, the intervals of chosen image frames are changed and the most suitable interval is inspected.
  • Keywords
    cameras; image matching; image motion analysis; image recognition; image representation; video surveillance; directional motion history images; graph matching; human motion recognition; human motion representation; human motion translation; image frames; image motion; surveillance cameras; Cameras; History; Humans; Image motion analysis; Optical imaging; Pixel; Surveillance; DMHI; MHI; PCA; graph matching; human motion recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SICE Annual Conference 2010, Proceedings of
  • Conference_Location
    Taipei
  • Print_ISBN
    978-1-4244-7642-8
  • Type

    conf

  • Filename
    5602857