Implicit crowds: Optimization integrator for robust crowd simulation

Ioannis Karamouzas, Nick Sohre, Rahul Narain, Stephen J Guy

Research output: Contribution to journalConference articlepeer-review

56 Scopus citations


Large multi-agent systems such as crowds involve inter-agent interactions that are typically anticipatory in nature, depending strongly on both the positions and the velocities of agents. We show how the nonlinear, anticipatory forces seen in multi-agent systems can be made compatible with recent work on energy-based formulations in physics-based animation, and propose a simple and effective optimization-based integration scheme for implicit integration of such systems. We apply this approach to crowd simulation by using a state-of-the-art model derived from a recent analysis of human crowd data, and adapting it to our framework. Our approach provides, for the first time, guaranteed collision-free motion while simultaneously maintaining high-quality collective behavior in a way that is insensitive to simulation parameters such as time step size and crowd density. These benefits are demonstrated through simulation results on various challenging scenarios and validation against real-world crowd data.

Original languageEnglish (US)
Article number136
JournalACM Transactions on Graphics
Issue number4
StatePublished - 2017
EventACM SIGGRAPH 2017 - Los Angeles, United States
Duration: Jul 30 2017Aug 3 2017

Bibliographical note

Funding Information:
Œis work has been supported in part by the National Science Foundation, under grants CHS-1526693 and CNS-1544887. Rahul Narain and Stephen J. Guy are joint last authors. Author’s addresses: I. Karamouzas, School of Computing, Clemson University, Clemson, SC; email:; N. Sohre, R. Narain, and S.J. Guy, Department of Computer Science and Engineering, University of Minnesota, Twin Cities, MN; email: {sohre007,narain,sjguy} Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permiŠed. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from © 2017 Copyright held by the owner/author(s). Publication rights licensed to ACM. 0730-0301/2017/7-ART136 $15.00 DOI: hŠp://

Publisher Copyright:
© 2017 Copyright held by the owner/author(s).


  • Crowd simulation
  • Implicit integration
  • Physics-based animation


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