• DocumentCode
    3405006
  • Title

    Simultaneous Human detection and action recognition employing 2DPCA-HOG

  • Author

    Naiel, Mohamed A. ; Abdelwahab, Moataz M. ; Elsaban, M. ; Mikhael, Wasfy B.

  • Author_Institution
    Nile Univ., Sixth October, Egypt
  • fYear
    2011
  • fDate
    7-10 Aug. 2011
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this paper a novel algorithm for Human detection and action recognition in videos is presented. The algorithm is based on Two-Dimensional Principal Components Analysis (2DPCA) applied to Histogram of Oriented Gradients (HOG). Due to simultaneous Human detection and action recognition employing the same algorithm, the computational complexity is reduced to a great deal. Experimental results applied to public datasets confirm these excellent properties compared to most recent methods.
  • Keywords
    computational complexity; object recognition; principal component analysis; video surveillance; 2DPCA-HOG; action recognition; computational complexity; histogram of oriented gradients; human detection; public datasets; two-dimensional principal components analysis; videos; Accuracy; Cameras; Humans;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems (MWSCAS), 2011 IEEE 54th International Midwest Symposium on
  • Conference_Location
    Seoul
  • ISSN
    1548-3746
  • Print_ISBN
    978-1-61284-856-3
  • Electronic_ISBN
    1548-3746
  • Type

    conf

  • DOI
    10.1109/MWSCAS.2011.6026441
  • Filename
    6026441