Herds From Video: Learning a Microscopic Herd Model From Macroscopic Motion Data

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dc.contributor.authorGong, Xianjinen_US
dc.contributor.authorGain, Jamesen_US
dc.contributor.authorRohmer, Damienen_US
dc.contributor.authorLyonnet, Sixtineen_US
dc.contributor.authorPettré, Julienen_US
dc.contributor.authorCani, Marie-Pauleen_US
dc.contributor.editorWimmer, Michaelen_US
dc.contributor.editorAlliez, Pierreen_US
dc.contributor.editorWestermann, RĂĽdigeren_US
dc.date.accessioned2025-11-07T08:33:50Z
dc.date.available2025-11-07T08:33:50Z
dc.date.issued2025
dc.description.abstractWe present a method for animating herds that automatically tunes a microscopic herd model based on a short video clip of real animals. Our method handles videos with dense herds, where individual animal motion cannot be separated out. Our contribution is a novel framework for extracting macroscopic herd behaviour from such video clips, and then deriving the microscopic agent parameters that best match this behaviour. To support this learning process, we extend standard agent models to provide a separation between leaders and followers, better match the occlusion and field-of-view limitations of real animals, support differentiable parameter optimization and improve authoring control. We validate the method by showing that once optimized, the social force and perception parameters of the resulting herd model are accurate enough to predict subsequent frames in the video, even for macroscopic properties not directly incorporated in the optimization process. Furthermore, the extracted herding characteristics can be applied to any terrain with a palette and region-painting approach that generalizes to different herd sizes and leader trajectories. This enables the authoring of herd animations in new environments while preserving learned behaviour.en_US
dc.description.number6
dc.description.sectionheadersMajor Revision from Eurographics Conference
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume44
dc.identifier.doi10.1111/cgf.70225
dc.identifier.issn1467-8659
dc.identifier.pages16 pages
dc.identifier.urihttps://doi.org/10.1111/cgf.70225
dc.identifier.urihttps://diglib.eg.org/handle/10.1111/cgf70225
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectanimation
dc.subjectbehavioural animation
dc.subjectComputing methodologies→Simulation by animation
dc.subjectPhysical simulation
dc.titleHerds From Video: Learning a Microscopic Herd Model From Macroscopic Motion Dataen_US
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