Crowd space: A predictive crowd analysis technique

Ioannis Karamouzas, Nick Sohre, Ran Hu, Stephen J Guy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Over the last two decades there has been a proliferation of methods for simulating crowds of humans. As the number of different methods and their complexity increases, it becomes increasingly unrealistic to expect researchers and users to keep up with all the possible options and trade-offs. We therefore see the need for tools that can facilitate both domain experts and non-expert users of crowd simulation in making high-level decisions about the best simulation methods to use in different scenarios. In this paper, we leverage trajectory data from human crowds and machine learning techniques to learn a manifold which captures representative local navigation scenarios that humans encounter in real life. We show the applicability of this manifold in crowd research, including analyzing trends in simulation accuracy, and creating automated systems to assist in choosing an appropriate simulation method for a given scenario.

Original languageEnglish (US)
Title of host publicationSIGGRAPH Asia 2018 Technical Papers, SIGGRAPH Asia 2018
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450360081
DOIs
StatePublished - Dec 4 2018
EventSIGGRAPH Asia 2018 Technical Papers - International Conference on Computer Graphics and Interactive Techniques, SIGGRAPH Asia 2018 - Tokyo, Japan
Duration: Dec 4 2018Dec 7 2018

Publication series

NameSIGGRAPH Asia 2018 Technical Papers, SIGGRAPH Asia 2018

Conference

ConferenceSIGGRAPH Asia 2018 Technical Papers - International Conference on Computer Graphics and Interactive Techniques, SIGGRAPH Asia 2018
CountryJapan
CityTokyo
Period12/4/1812/7/18

Fingerprint

Learning systems
Navigation
Trajectories
Predictive analytics

Keywords

  • Crowd simulation
  • Entropy
  • Manifold learning
  • Validation

Cite this

Karamouzas, I., Sohre, N., Hu, R., & Guy, S. J. (2018). Crowd space: A predictive crowd analysis technique. In SIGGRAPH Asia 2018 Technical Papers, SIGGRAPH Asia 2018 [186] (SIGGRAPH Asia 2018 Technical Papers, SIGGRAPH Asia 2018). Association for Computing Machinery, Inc. https://doi.org/10.1145/3272127.3275079

Crowd space : A predictive crowd analysis technique. / Karamouzas, Ioannis; Sohre, Nick; Hu, Ran; Guy, Stephen J.

SIGGRAPH Asia 2018 Technical Papers, SIGGRAPH Asia 2018. Association for Computing Machinery, Inc, 2018. 186 (SIGGRAPH Asia 2018 Technical Papers, SIGGRAPH Asia 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Karamouzas, I, Sohre, N, Hu, R & Guy, SJ 2018, Crowd space: A predictive crowd analysis technique. in SIGGRAPH Asia 2018 Technical Papers, SIGGRAPH Asia 2018., 186, SIGGRAPH Asia 2018 Technical Papers, SIGGRAPH Asia 2018, Association for Computing Machinery, Inc, SIGGRAPH Asia 2018 Technical Papers - International Conference on Computer Graphics and Interactive Techniques, SIGGRAPH Asia 2018, Tokyo, Japan, 12/4/18. https://doi.org/10.1145/3272127.3275079
Karamouzas I, Sohre N, Hu R, Guy SJ. Crowd space: A predictive crowd analysis technique. In SIGGRAPH Asia 2018 Technical Papers, SIGGRAPH Asia 2018. Association for Computing Machinery, Inc. 2018. 186. (SIGGRAPH Asia 2018 Technical Papers, SIGGRAPH Asia 2018). https://doi.org/10.1145/3272127.3275079
Karamouzas, Ioannis ; Sohre, Nick ; Hu, Ran ; Guy, Stephen J. / Crowd space : A predictive crowd analysis technique. SIGGRAPH Asia 2018 Technical Papers, SIGGRAPH Asia 2018. Association for Computing Machinery, Inc, 2018. (SIGGRAPH Asia 2018 Technical Papers, SIGGRAPH Asia 2018).
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