Model‐based Crowd Behaviours in Human‐solution Space

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dc.contributor.authorXiang, Weien_US
dc.contributor.authorWang, Heen_US
dc.contributor.authorZhang, Yuqingen_US
dc.contributor.authorYip, Milo K.en_US
dc.contributor.authorJin, Xiaogangen_US
dc.contributor.editorHauser, Helwig and Alliez, Pierreen_US
dc.date.accessioned2023-10-06T11:58:51Z
dc.date.available2023-10-06T11:58:51Z
dc.date.issued2023
dc.description.abstractRealistic crowd simulation has been pursued for decades, but it still necessitates tedious human labour and a lot of trial and error. The majority of currently used crowd modelling is either empirical (model‐based) or data‐driven (model‐free). Model‐based methods cannot fit observed data precisely, whereas model‐free methods are limited by the availability/quality of data and are uninterpretable. In this paper, we aim at taking advantage of both model‐based and data‐driven approaches. In order to accomplish this, we propose a new simulation framework built on a physics‐based model that is designed to be data‐friendly. Both the general prior knowledge about crowds encoded by the physics‐based model and the specific real‐world crowd data at hand jointly influence the system dynamics. With a multi‐granularity physics‐based model, the framework combines microscopic and macroscopic motion control. Each simulation step is formulated as an energy optimization problem, where the minimizer is the desired crowd behaviour. In contrast to traditional optimization‐based methods which seek the theoretical minimizer, we designed an acceleration‐aware data‐driven scheme to compute the minimizer from real‐world data in order to achieve higher realism by parameterizing both velocity and acceleration. Experiments demonstrate that our method can produce crowd animations that are more realistically behaved in a variety of scales and scenarios when compared to the earlier methods.en_US
dc.description.number6
dc.description.sectionheadersORIGINAL ARTICLES
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume42
dc.identifier.doi10.1111/cgf.14919
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.14919
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14919
dc.publisher© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd.en_US
dc.subjectcrowd simulation
dc.subjectdata‐driven
dc.subjectmulti‐granularity
dc.titleModel‐based Crowd Behaviours in Human‐solution Spaceen_US
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