• DocumentCode
    3086843
  • Title

    Automatic understanding of human behavior in videos: A review

  • Author

    Bouzegza, Mourad ; Elarbi-Boudihir, M.

  • Author_Institution
    Coll. of Comput. Sci., Imam Univ., Riyadh, United Arab Emirates
  • fYear
    2013
  • fDate
    12-15 May 2013
  • Firstpage
    185
  • Lastpage
    190
  • Abstract
    Real-time understanding of human behavior in video streams is presently one of the most active areas of research in Computer Vision and Artificial Intelligence. Its purpose is to automatically detect, track and describe human activities in a sequence of image frames. Challenges in this topic of research are numerous and sometimes very difficult to work out. Consequently, the progress is very slow and the results are not very satisfactory. This paper aims to survey the methods used in human behavior understanding, showing their strengths and weaknesses. This small “toolbox” of methods and strategies could be very useful to the researcher and the engineer alike.
  • Keywords
    behavioural sciences; computer vision; image sequences; video signal processing; video streaming; artificial intelligence; automatic human behavior understanding; computer vision; human activities; image frame sequence; real-time human behavior understanding; video streams; Computational modeling; Computer vision; Grammar; Hidden Markov models; Taxonomy; Tracking; Videos; abnormal human behavior; behavior understanding; computer vision; surveillance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Signal Processing and their Applications (WoSSPA), 2013 8th International Workshop on
  • Conference_Location
    Algiers
  • Type

    conf

  • DOI
    10.1109/WoSSPA.2013.6602359
  • Filename
    6602359