• DocumentCode
    692054
  • Title

    Multi-view Human Action Recognition: A Survey

  • Author

    Iosifidis, Alexandros ; Tefas, Anastasios ; Pitas, Ioannis

  • Author_Institution
    Dept. of Inf., Aristotle Univ. of Thessaloniki, Thessaloniki, Greece
  • fYear
    2013
  • fDate
    16-18 Oct. 2013
  • Firstpage
    522
  • Lastpage
    525
  • Abstract
    While single-view human action recognition has attracted considerable research study in the last three decades, multi-view action recognition is, still, a less exploited field. This paper provides a comprehensive survey of multi-view human action recognition approaches. The approaches are reviewed following an application-based categorization: methods are categorized based on their ability to operate using a fixed or an arbitrary number of cameras. Finally, benchmark databases frequently used for evaluation of multi-view approaches are briefly described.
  • Keywords
    cameras; image recognition; application-based categorization; cameras; multiview human action recognition; single-view human action recognition; Biological system modeling; Cameras; Databases; Shape; Solid modeling; Three-dimensional displays; Visualization; Multi-view action recognition; review; survey;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Hiding and Multimedia Signal Processing, 2013 Ninth International Conference on
  • Conference_Location
    Beijing
  • Type

    conf

  • DOI
    10.1109/IIH-MSP.2013.135
  • Filename
    6846691