The DOI matches its Crossref record.
Continuum crowds
Abstract
We present a real-time crowd model based on continuum dynamics. In our model, a dynamic potential field simultaneously integrates global navigation with moving obstacles such as other people, efficiently solving for the motion of large crowds without the need for explicit collision avoidance. Simulations created with our system run at interactive rates, demonstrate smooth flow under a variety of conditions, and naturally exhibit emergent phenomena that have been observed in real crowds.
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Citations
Cited by
Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks
Gupta, A., Johnson, J., Fei-Fei, L., Savarese, S., & Alahi, A. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00240 · Cited by 2,466
Learning pedestrian dynamics from the real world
Scovanner, P., & Tappen, M. F. (2009) · 2009 IEEE 12th International Conference on Computer Vision · doi:10.1109/iccv.2009.5459224 · Cited by 135
Metadata
- Authors
- Treuille, A., Cooper, S., & Popović, Z.
- Venue
- ACM SIGGRAPH 2006 Papers on - SIGGRAPH '06
- Publisher
- ACM Press
- Published
- 2006
- Pages
- 1160
- OpenAlex
- W4239127346
- Cited by
- 170
- References
- 0
- Type
- conference abstract
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Continuum crowds. https://app.cochat.ai/papers/10.1145/1179352.1142008
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- Treuille, A., Cooper, S., & Popović, Z. (2006). Continuum crowds. ACM SIGGRAPH 2006 Papers on - SIGGRAPH '06. https://doi.org/10.1145/1179352.1142008
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
