• DocumentCode
    2614247
  • Title

    Efficient Multi-target Human Motion Tracking

  • Author

    Abhyankar, Aditya

  • fYear
    2009
  • fDate
    17-20 April 2009
  • Firstpage
    571
  • Lastpage
    575
  • Abstract
    Effective human motion tracking is necessary for all surveillance based biometric applications. Human motion being highly non-linear and non-modular is always difficult to track. To make it more challenging, in real scenarios, there are always multiple targets to be tracked. In this work particle filter based multiple target tracking system is proposed. For performing actual tracking Markov chain Monte Carlo methods are used. The system was tested using moviedb and labdb databases and accuracy of 91.7% was obtained.
  • Keywords
    Markov processes; Monte Carlo methods; biometrics (access control); image motion analysis; particle filtering (numerical methods); surveillance; target tracking; Markov chain Monte Carlo method; labdb database; moviedb database; multitarget human motion tracking; particle filter; surveillance based biometric application; Biometrics; Humans; Integral equations; Motion analysis; Particle filters; Particle tracking; Springs; State-space methods; Surveillance; Target tracking; Markov Chains; Monte Carlo method; Motion Tracking; Multiple Targets; Particle filtering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Technology - Spring Conference, 2009. IACSITSC '09. International Association of
  • Conference_Location
    Singapore
  • Print_ISBN
    978-0-7695-3653-8
  • Type

    conf

  • DOI
    10.1109/IACSIT-SC.2009.100
  • Filename
    5169418