• DocumentCode
    3645232
  • Title

    Who knows who - Inverting the Social Force Model for finding groups

  • Author

    Jan Šochman;David C. Hogg

  • Author_Institution
    CMP, Dep. of Cyber., FEE, CTU, Czech
  • fYear
    2011
  • Firstpage
    830
  • Lastpage
    837
  • Abstract
    Social groups based on friendship or family relations are very common phenomena in human crowds and a valuable cue for a crowd activity recognition system. In this paper we present an algorithm for automatic on-line inference of social groups from observed trajectories of individual people. The method is based on the Social Force Model (SFM) - widely used in crowd simulation applications - which specifies several attractive and repulsive forces influencing each individual relative to the other pedestrians and their environment. The main contribution of the paper is an algorithm for inference of the social groups (parameters of the SFM) based on analysis of the observed trajectories through attractive or repulsive forces which could lead to such behaviour. The proposed SFM-based method shows its clear advantage especially in more crowded scenarios where other state-of-the-art methods fail. The applicability of the algorithm is illustrated on an abandoned bag scenario.
  • Keywords
    "Force","Trajectory","Clustering algorithms","Mathematical model","Computational modeling","Prediction algorithms","Inference algorithms"
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision Workshops (ICCV Workshops), 2011 IEEE International Conference on
  • Print_ISBN
    978-1-4673-0062-9
  • Type

    conf

  • DOI
    10.1109/ICCVW.2011.6130338
  • Filename
    6130338