• DocumentCode
    3434363
  • Title

    Automatic Fall Incident Detection in Compressed Video for Intelligent Homecare

  • Author

    Lin, Chia-Wen ; Ling, Zhi-Hong

  • Author_Institution
    Nat. Tsing Hua Univ., Hsinchu
  • fYear
    2007
  • fDate
    13-16 Aug. 2007
  • Firstpage
    1172
  • Lastpage
    1177
  • Abstract
    This paper presents a compressed-domain fall incident detection scheme for intelligent homecare applications. First, a compressed-domain object segmentation scheme is performed to extract moving objects based on global motion estimation and local motion clustering. After detecting the moving objects, three compressed-domain features of each object are then extracted for identifying and locating fall incidents. The proposed system can differentiate fall-down from squatting by taking into account the event duration. Our experiments show that the proposed method can correctly detect fall incidents in real time.
  • Keywords
    feature extraction; home computing; motion estimation; video coding; automatic fall incident detection; compressed-domain feature extraction; compressed-domain object segmentation scheme; global motion estimation; intelligent homecare applications; motion clustering; video compression; Application software; Cameras; Computer vision; Computerized monitoring; Event detection; Injuries; Senior citizens; Smoke detectors; Surveillance; Video compression; compressed-domain processing; fall detetcion; homecare; video surveillance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Communications and Networks, 2007. ICCCN 2007. Proceedings of 16th International Conference on
  • Conference_Location
    Honolulu, HI
  • ISSN
    1095-2055
  • Print_ISBN
    978-1-4244-1251-8
  • Electronic_ISBN
    1095-2055
  • Type

    conf

  • DOI
    10.1109/ICCCN.2007.4317978
  • Filename
    4317978