Yao, X, Wang, S, Sun, W et al. (3 more authors) (2023) Crowd Simulation with Detailed Body Motion and Interaction. In: Magnenat-Thalmann, N, Zhang, J, Kim, J, Papagiannakis, G, Sheng, B, Thalmann, D and Gavrilova, M, (eds.) Advances in Computer Graphics. 39th Computer Graphics International Conference, CGI 2022, 12-16 Sep 2022, Online. Lecture Notes in Computer Science, 13443 . Springer , pp. 227-238. ISBN 978-3-031-23472-9
Abstract
Crowd simulation methods generally focus on high fidelity 2D trajectories but ignore detailed 3D body animation which is normally added in a post-processing step. We argue that this is an intrinsic flaw as detailed body motions affect the 2D trajectories, especially when interactions are present between characters, and characters and the environment. In practice, this requires labor-intensive post-processing, fitting individual character animations onto simulated trajectories where anybody interactions need to be manually specified. In this paper, we propose a new framework to integrate the modeling of crowd motions with character motions, to enable their mutual influence, so that crowd simulation also incorporates agent-agent and agent-environment interactions. The whole framework is based on a three-level hierarchical control structure to effectively control the scene at different scales efficiently and consistently. To facilitate control, each character is modeled as an agent governed by four modules: visual system, blackboard system, decision system, and animation system. The animation system of the agent model consists of two modes: a traditional Finite State Machine (FSM) animation mode, and a motion matching mode. So an agent not only retains the flexibility of FSMs, but also has the advantage of motion matching which adapts detailed body movements for interactions with other agents and the environment. Our method is universal and applicable to most interaction scenarios in various environments in crowd animation, which cannot be achieved by prior work. We validate the fluency and realism of the proposed method by extensive experiments and user studies.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2022 The Author(s). This is an author produced version of a conference paper published in Advances in Computer Graphics. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 17 Jun 2022 11:21 |
Last Modified: | 01 Jan 2024 01:13 |
Status: | Published |
Publisher: | Springer |
Series Name: | Lecture Notes in Computer Science |
Identification Number: | 10.1007/978-3-031-23473-6_18 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:187875 |