• DocumentCode
    2155651
  • Title

    Graph-based sequential particle filtering in lossy networks: Single and multiple collaborative cameras

  • Author

    Huang, Jing ; Schonfeld, Dan

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Illinois at Chicago, Chicago, IL, USA
  • fYear
    2011
  • fDate
    22-27 May 2011
  • Firstpage
    1189
  • Lastpage
    1192
  • Abstract
    This paper presents a novel approach of multiple target tracking from multiple collaborative cameras. Firstly, particle filtering for conditional density propagation on graphs to address missing frames from one view is introduced. The Markov Properties and Separation Theorem are used to derive an exact solution for estimation on graphs with missing frames. Furthermore, a distributed multiple target tracking solution from multiple cameras is proposed by using collaborative particle filters. With epipolar geometry constraint, camera collaboration message is delivered between different views by particles. Results demonstrate that our system can deal with missing frames in the presence of occlusions.
  • Keywords
    Markov processes; graph theory; particle filtering (numerical methods); target tracking; video cameras; Markov properties; camera collaboration message; conditional density propagation; distributed multiple target tracking solution; epipolar geometry constraint; graph-based sequential particle filtering; lossy networks; multiple collaborative cameras; separation theorem; single collaborative cameras; Cameras; Collaboration; Geometry; Graphical models; Hidden Markov models; Markov processes; Target tracking; Graphical models; Missing frames; Multi-camera; Occlusion; Particle filtering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
  • Conference_Location
    Prague
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4577-0538-0
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2011.5946622
  • Filename
    5946622