• DocumentCode
    1420742
  • Title

    Video-Based Abnormal Human Behavior Recognition—A Review

  • Author

    Popoola, Oluwatoyin P. ; Wang, Kejun

  • Author_Institution
    Pattern Recognition & Intell. Syst. Lab., Harbin Eng. Univ., Harbin, China
  • Volume
    42
  • Issue
    6
  • fYear
    2012
  • Firstpage
    865
  • Lastpage
    878
  • Abstract
    Modeling human behaviors and activity patterns for recognition or detection of special event has attracted significant research interest in recent years. Diverse methods that are abound for building intelligent vision systems aimed at scene understanding and making correct semantic inference from the observed dynamics of moving targets. Most applications are in surveillance, video content retrieval, and human-computer interfaces. This paper presents not only an update extending previous related surveys, but also a focus on contextual abnormal human behavior detection especially in video surveillance applications. The main purpose of this survey is to extensively identify existing methods and characterize the literature in a manner that brings key challenges to attention.
  • Keywords
    content-based retrieval; human computer interaction; inference mechanisms; pattern recognition; video retrieval; video surveillance; activity patterns; contextual abnormal human behavior detection; human-computer interfaces; intelligent vision systems; moving targets; scene understanding; semantic inference; video content retrieval; video surveillance applications; video-based abnormal human behavior recognition; Behavioral science; Feature extraction; Hidden Markov models; Human factors; Surveillance; Tracking; Anomaly detection; behavior modeling; human action recognition; video surveillance;
  • fLanguage
    English
  • Journal_Title
    Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1094-6977
  • Type

    jour

  • DOI
    10.1109/TSMCC.2011.2178594
  • Filename
    6129539