• DocumentCode
    1312521
  • Title

    Crowd Density Analysis with Marked Point Processes [Applications Corner]

  • Author

    Ge, Weina ; Collins, Robert T.

  • Author_Institution
    Comput. Sci. & Eng. Dept., Penn State Univ., University Park, PA, USA
  • Volume
    27
  • Issue
    5
  • fYear
    2010
  • Firstpage
    107
  • Lastpage
    123
  • Abstract
    This article presents a Bayesian approach that estimates the count and location of individuals in a video frame. Crowds are modeled by a marked point process (MPP) that couples a spatial stochastic process governing number and placement of individuals with a conditional mark process for selecting body size, shape, and orientation. Given a noisy, binary mask image where pixels are labeled foreground or background, the approach seeks a configuration of cutout shapes that simultaneously "covers" as many foreground pixels and as few background pixels as possible.
  • Keywords
    stochastic processes; video signal processing; video surveillance; Bayesian approach; crowd density analysis; marked point processes; spatial stochastic process; video frame; Gaussian distribution; Legged locomotion; Pixel; Proposals; Prototypes; Surveillance; Video equipment;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1053-5888
  • Type

    jour

  • DOI
    10.1109/MSP.2010.937495
  • Filename
    5562669