• DocumentCode
    3137095
  • Title

    Monocular 3D Head Tracking to Detect Falls of Elderly People

  • Author

    Rougier, Caroline ; Meunier, Jean ; St-Arnaud, Alain ; Rousseau, Jacqueline

  • Author_Institution
    Dept. of Comput. Sci. & Oper. Res., Montreal Univ., Que.
  • fYear
    2006
  • fDate
    Aug. 30 2006-Sept. 3 2006
  • Firstpage
    6384
  • Lastpage
    6387
  • Abstract
    Faced with the growing population of seniors, Western societies need to think about new technologies to ensure the safety of elderly people at home. Computer vision provides a good solution for healthcare systems because it allows a specific analysis of people behavior. Moreover, a system based on video surveillance is particularly well adapted to detect falls. We present a new method to detect falls using a single camera. Our approach is based on the 3D trajectory of the head, which allows us to distinguish falls from normal activities using 3D velocities
  • Keywords
    biomechanics; computer vision; geriatrics; health care; safety; telemedicine; video cameras; video surveillance; 3D velocity characteristics; computer vision; elderly people; fall detection; healthcare system; monocular 3D head tracking; safety aspects; video surveillance; Cameras; Computer vision; Data mining; Face detection; Head; Iterative algorithms; Layout; Senior citizens; Shape; Tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
  • Conference_Location
    New York, NY
  • ISSN
    1557-170X
  • Print_ISBN
    1-4244-0032-5
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2006.260829
  • Filename
    4463271