• DocumentCode
    2508764
  • Title

    Slip and Fall Events Detection by Analyzing the Integrated Spatiotemporal Energy Map

  • Author

    Liao, Tim ; Huang, Chung-Lin

  • Author_Institution
    Electr. Eng. Dept., Nat. Tsing-Hua Univ., Hsinchu, Taiwan
  • fYear
    2010
  • fDate
    23-26 Aug. 2010
  • Firstpage
    1718
  • Lastpage
    1721
  • Abstract
    This paper presents a new method to detect slip and fall events by analyzing the integrated spatiotemporal energy (ISTE) map. ISTE map includes motion and time of motion occurrence as our motion feature. The extracted human shape is represented by an ellipse that provides crucial information of human motion activities. We use this features to detect the events in the video with non-fixed frame rate. This work assumes that the person lies on the ground with very little motion after the fall accident. Experimental results show that our method is effective for fall and slip detection.
  • Keywords
    image motion analysis; fall events detection; human motion activities; human shape; integrated spatiotemporal energy map; motion feature; motion occurrence; slip events detection; Event detection; Feature extraction; Humans; Motion segmentation; Shape; Spatiotemporal phenomena; Video sequences; Fall Event Detection; Integrated Spatiotemporal Energy (ISTE) map; Slip Event Detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2010 20th International Conference on
  • Conference_Location
    Istanbul
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4244-7542-1
  • Type

    conf

  • DOI
    10.1109/ICPR.2010.425
  • Filename
    5597479