• DocumentCode
    2851107
  • Title

    Study on fall detection based on intelligent video analysis

  • Author

    Ngo, Y.T. ; Nguyen, Hien ; Pham, Thuy V.

  • Author_Institution
    Electron. & Telecomm. Dept., Duc Minh Coll. of Econ. & Technol., Danang, Vietnam
  • fYear
    2012
  • fDate
    10-12 Oct. 2012
  • Firstpage
    114
  • Lastpage
    117
  • Abstract
    In this paper, a fall detection algorithm has been built using intelligent analysis of captured video signal. Five geometrical features are extracted from input video signal and are recognized by a trained feed-forward neural network. Experimental results on our self-built database show that the proposed fall detection system can detect fall events with quite high precision under different falling conditions.
  • Keywords
    feature extraction; feedforward neural nets; image segmentation; learning (artificial intelligence); video signal processing; visual databases; feature recognition; feedforward neural network training; geometrical feature extraction; input video signal; intelligent video analysis-based fall detection algorithm; self-built database; Databases; Training; Vectors; fall detection; feature extraction; neural network; recognition; segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Technologies for Communications (ATC), 2012 International Conference on
  • Conference_Location
    Hanoi
  • ISSN
    2162-1020
  • Print_ISBN
    978-1-4673-4351-0
  • Type

    conf

  • DOI
    10.1109/ATC.2012.6404242
  • Filename
    6404242