• DocumentCode
    250085
  • Title

    AdaPT: Real-time adaptive pedestrian tracking for crowded scenes

  • Author

    Bera, Aniket ; Galoppo, Nico ; Sharlet, Dillon ; Lake, Adam ; Manocha, Dinesh

  • Author_Institution
    Dept. of Comput. Sci., Univ. of North Carolina at Chapel Hill, Chapel Hill, NC, USA
  • fYear
    2014
  • fDate
    May 31 2014-June 7 2014
  • Firstpage
    1801
  • Lastpage
    1808
  • Abstract
    We present a novel realtime algorithm to compute the trajectory of each pedestrian in a crowded scene. Our formulation is based on an adaptive scheme that uses a combination of deterministic and probabilistic trackers to achieve high accuracy and efficiency simultaneously. Furthermore, we integrate it with a multi-agent motion model and local interaction scheme to accurately compute the trajectory of each pedestrian. We highlight the performance and benefits of our algorithm on well-known datasets with tens of pedestrians.
  • Keywords
    multi-agent systems; object tracking; pedestrians; probability; real-time systems; AdaPT; adaptive scheme; crowded scenes; deterministic tracker; local interaction scheme; multiagent motion model; probabilistic tracker; real-time adaptive pedestrian tracking; realtime algorithm; Accuracy; Adaptation models; Computational modeling; Histograms; Target tracking; Trajectory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation (ICRA), 2014 IEEE International Conference on
  • Conference_Location
    Hong Kong
  • Type

    conf

  • DOI
    10.1109/ICRA.2014.6907095
  • Filename
    6907095