@InProceedings{Sochman-sism2011,
  IS = { zkontrolovano 10 Jan 2012 },
  UPDATE  = { 2011-12-29 },
  author =      {{\v S}ochman, Jan and  Hogg, David C.},
  title =       {Who Knows Who -- Inverting the Social Force Model for Finding Groups},
  year =        {2011},
  pages =       {830--837},
  booktitle =   {2011 IEEE International Conference on Computer
                 Vision Workshops (ICCV Workshops)},
  publisher =   {IEEE Computer Society},
  address =     {Los Alamitos, USA},
  isbn =        {978-1-4673-0063-6},
  book_pages =  {2204},
  month =       {November},
  day =         {6-13},
  venue =       {Barcelona, Spain},
  annote =      {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 =    {social force model, social groups, 
    crowd monitoring, surveillance},
  authorship =  {50-50},
  note =        {CD-ROM},
  project =     {FP7-ICT-247022 MASH},
  psurl = {[PDF]},
}