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dc.contributor.authorMao, Tianluen_US
dc.contributor.authorWang, Jien_US
dc.contributor.authorMeng, Ruoyuen_US
dc.contributor.authorYan, Qinyuanen_US
dc.contributor.authorLiu, Shaohuaen_US
dc.contributor.authorWang, Zhaoqien_US
dc.contributor.editorDominik L. Michelsen_US
dc.contributor.editorSoeren Pirken_US
dc.description.abstractThis paper proposes a novel crowd simulation method which integrates not only modelling ideas but also advantages from both data-driven methods and crowd dynamics methods. To seamlessly integrate these two different modelling ideas, first, a fusion crowd motion model is developed. In this model the motion of crowd are driven dynamically by different forces. Part of the forces are modeled under a universal interaction mechanism, which describe the common parts of crowd dynamics. Others are modeled by examples from real data, which describe the personality parts of the agent motion. Second, a construction method for example dataset is proposed to support the fusion model. In the dataset, crowd trajectories captured in the real world are decomposed and re-described under the structure of the fusion model. Thus, personality parts hidden in the real data could be locked and extracted, making the data understandable and migratable for our fusion model. A comprehensive crowd motion generation workflow using the fusion model and example dataset is also proposed. Quantitative and qualitative experiments and user studies are conducted. Results show that the proposed fusion crowd simulation method can generate crowd motion with the great motion fidelity, which not only match the macro characteristics of real data, but also has lots of micro personality showing the diversity of crowd motion.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectCCS Concepts: Computing methodologies --> Multi-agent planning; Applied computing --> Law, social and behavioral sciences
dc.subjectComputing methodologies
dc.subjectagent planning
dc.subjectApplied computing
dc.subjectsocial and behavioral sciences
dc.titleA Fusion Crowd Simulation Method: Integrating Data with Dynamics, Personality with Commonen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersMotion I
dc.identifier.pages12 pages

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  • 41-Issue 8
    ACM SIGGRAPH / Eurographics Symposium on Computer Animation 2022

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