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Destination flow for crowd simulation

Stefano Pellegrini and Juergen Gall and Leonid Sigal and Luc Van Gool
3nd Workshop on Analysis and Retrieval of Tracked Events and Motion in Imagery Streams
2012

Abstract

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 xstudy.


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@InProceedings{eth_biwi_00935,
  author = {Stefano Pellegrini and Juergen Gall and Leonid Sigal and Luc Van Gool},
  title = {Destination flow for crowd simulation},
  booktitle = {3nd Workshop on Analysis and Retrieval of Tracked Events and Motion in Imagery Streams},
  year = {2012},
  keywords = {}
}