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Behavioral Landmarks: Inferring Interactions from Data

dc.contributor.authorLemonari, Marilenaen_US
dc.contributor.authorCharalambous, Panayiotisen_US
dc.contributor.authorPanayiotou, Andreasen_US
dc.contributor.authorChrysanthou, Yiorgosen_US
dc.contributor.authorPettré, Julienen_US
dc.contributor.editorLiu, Lingjieen_US
dc.contributor.editorAverkiou, Melinosen_US
dc.date.accessioned2024-04-16T15:29:26Z
dc.date.available2024-04-16T15:29:26Z
dc.date.issued2024
dc.identifier.isbn978-3-03868-239-4
dc.identifier.issn1017-4656
dc.identifier.urihttps://doi.org/10.2312/egp.20241039
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/egp20241039
dc.description.abstractWe aim to unravel complex agent-environment interactions from trajectories, by explaining agent paths as combinations of predefined basic behaviors. We detect trajectory points signifying environment-driven behavior changes, ultimately disentangling interactions in space and time; our framework can be used for environment synthesis and authoring, shown by our case studies.en_US
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies → Image representations; Neural networks; Motion processing
dc.subjectComputing methodologies → Image representations
dc.subjectNeural networks
dc.subjectMotion processing
dc.titleBehavioral Landmarks: Inferring Interactions from Dataen_US
dc.description.seriesinformationEurographics 2024 - Posters
dc.description.sectionheadersPosters
dc.identifier.doi10.2312/egp.20241039
dc.identifier.pages2 pages


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Attribution 4.0 International License
Except where otherwise noted, this item's license is described as Attribution 4.0 International License