Destination Flow for Crowd Simulation

  • Stefano Pellegrini
  • Jürgen Gall
  • Leonid Sigal
  • Luc Van Gool
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7585)


We present a crowd simulation that captures some of the semantics of a specific scene by partly reproducing its motion behaviors, both at a lower level using a steering model and at the higher level of goal selection. To this end, we use and generalize a steering model based on linear velocity prediction, termed LTA. From a goal selection perspective, we reproduce many of the motion behaviors of the scene without explicitly specifying them. Behaviors like “wait at the tram stop” or “stroll-around” are not explicitly modeled, but learned from real examples. To this end, we process real data to extract information that we use in our simulation. As a consequence, we can easily integrate real and virtual agents in a mixed reality simulation. We propose two strategies to achieve this goal and validate the results by a user study.


Gall Cyan Terion 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Stefano Pellegrini
    • 1
  • Jürgen Gall
    • 2
  • Leonid Sigal
    • 3
  • Luc Van Gool
    • 1
  1. 1.ETH ZurichSwitzerland
  2. 2.MPI for Intelligent SystemsGermany
  3. 3.Disney Research PittsburghUSA

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