Propagating Uncertainty in Petri Nets for Activity Recognition

  • Gal Lavee
  • Michael Rudzsky
  • Ehud Rivlin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6454)


Petri Nets is a formalism that has recently been proposed for the specification of models for use in activity recognition . This formalism is attractive because of its inherent ability to model partial ordering, concurrency, logical and temporal relations between the events that compose activities. The main novelty of this work is a probabilistic mechanism (based on the particle filter) for recognizing activities modeled as Petri Nets in video. This mechanism takes into account the observation and semantic uncertainty inherent in low-level events and propagates it into a probabilistic activity recognition.


Particle Filter Activity Recognition Proposal Distribution Reachable State Place Node 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Gal Lavee
    • 1
  • Michael Rudzsky
    • 1
  • Ehud Rivlin
    • 1
    • 2
  1. 1.Computer Science Department, TechnionIsrael Institute of TechnologyHaifaIsrael
  2. 2.Google Inc.Mountain ViewUSA

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