• DocumentCode
    2798126
  • Title

    A robust fall detection system for the elderly in a Smart Room

  • Author

    Yu, Miao ; Naqvi, Syed Mohsen ; Chambers, Jonathon

  • Author_Institution
    Electron. & Electr. Eng. Dept., Loughborough Univ., Leicester, UK
  • fYear
    2010
  • fDate
    14-19 March 2010
  • Firstpage
    1666
  • Lastpage
    1669
  • Abstract
    In this paper, we propose a novel and robust fall detection system by using a density method for modeling a fall event as a function of certain video feature.3-D head velocity and human shape information are extracted as feature and three types of density model, single Gaussian, mixture of Gaussians and Parzen window method, are constructed for modeling the density of fall with respect to the extracted video feature. Falls are then detected according to the corresponding obtained density model and the success of the method is confirmed on real video sequences.
  • Keywords
    Gaussian processes; feature extraction; handicapped aids; shape recognition; 3-D head velocity; Parzen window method; density method; fall event; feature extraction; human shape information; robust fall detection system; single Gaussian; smart room; video feature; Cameras; Data mining; Feature extraction; Filtering; Head; Humans; Particle tracking; Robustness; Senior citizens; Shape; code-book background subtraction; density method; fall detection; head tracking; motion-based particle filtering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
  • Conference_Location
    Dallas, TX
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4244-4295-9
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2010.5495512
  • Filename
    5495512