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A perceptually-validated metric for crowd trajectory quality evaluation

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dc.contributor.author Cabrero Daniel, Beatriz
dc.contributor.author Marques, Ricardo
dc.contributor.author Hoyet, Ludovic
dc.contributor.author Pettré, Julien
dc.contributor.author Blat, Josep
dc.date.accessioned 2023-03-06T07:30:13Z
dc.date.available 2023-03-06T07:30:13Z
dc.date.issued 2021
dc.identifier.citation Cabrero Daniel B, Marques R, Hoyet L, Pettré J, Blat J. A perceptually-validated metric for crowd trajectory quality evaluation. Proc ACM Comput Graph Interact Tech. 2021;4(3):42. DOI: 10.1145/3480136
dc.identifier.issn 2577-6193
dc.identifier.uri http://hdl.handle.net/10230/56046
dc.description.abstract Simulating crowds requires controlling a very large number of trajectories and is usually performed using crowd motion algorithms for which appropriate parameter values need to be found. The study of the relation between parametric values for simulation techniques and the quality of the resulting trajectories has been studied either through perceptual experiments or by comparison with real crowd trajectories. In this paper, we integrate both strategies. A quality metric, QF, is proposed to abstract from reference data while capturing the most salient features that affect the perception of trajectory realism. QF weights and combines cost functions that are based on several individual, local and global properties of trajectories. These trajectory features are selected from the literature and from interviews with experts. To validate the capacity of QF to capture perceived trajectory quality, we conduct an online experiment that demonstrates the high agreement between the automatic quality score and non-expert users. To further demonstrate the usefulness of QF, we use it in a data-free parameter tuning application able to tune any parametric microscopic crowd simulation model that outputs independent trajectories for characters. The learnt parameters for the tuned crowd motion model maintain the influence of the reference data which was used to weight the terms of QF.
dc.description.sponsorship With partial support of the EU funded project PRESENT, H2020-ICT-2018-3-856879. As Serra Húnter Fellow, Ricardo Marques acknowledges the support of the Serra Húnter Programme to this work.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher ACM Association for Computer Machinery
dc.relation.ispartof Proceedings of the ACM on Computer Graphics and Interactive Techniques. 2021;4(3):42.
dc.rights © ACM, 2021. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the ACM on Computer Graphics and Interactive Techniques, Vol. 4, No. 3, September 2021. http://doi.acm.org/10.1145/10.1145/3480136
dc.title A perceptually-validated metric for crowd trajectory quality evaluation
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1145/3480136
dc.subject.keyword trajectory quality
dc.subject.keyword automatic simulation evaluation
dc.subject.keyword perception experiment
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/856879
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/acceptedVersion


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