A Perceptually-Validated Metric for Crowd Trajectory Quality Evaluation

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dc.contributor.authorDaniel, Beatriz Cabreroen_US
dc.contributor.authorMarques, Ricardoen_US
dc.contributor.authorHoyet, Ludovicen_US
dc.contributor.authorPettré, Julienen_US
dc.contributor.authorBlat, Josepen_US
dc.contributor.editorNarain, Rahul and Neff, Michael and Zordan, Victoren_US
dc.date.accessioned2022-02-07T13:32:36Z
dc.date.available2022-02-07T13:32:36Z
dc.date.issued2021
dc.description.abstractSimulating 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.en_US
dc.description.number3
dc.description.sectionheaderspapers
dc.description.seriesinformationProceedings of the ACM on Computer Graphics and Interactive Techniques
dc.description.volume4
dc.identifier.doi10.1145/3480136
dc.identifier.issn2577-6193
dc.identifier.urihttps://doi.org/10.1145/3480136
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1145/3480136
dc.publisherACMen_US
dc.subjectComputing methodologies
dc.subjectSimulation evaluation
dc.subjectMotion path planning
dc.subjectAgent / discrete models
dc.subjectMulti
dc.subjectagent systems
dc.subjectMathematics of computing
dc.subjectDimensionality reduction Additional KeyWords and Phrases
dc.subjecttrajectory quality
dc.subjectautomatic simulation evaluation
dc.subjectperception experiment
dc.titleA Perceptually-Validated Metric for Crowd Trajectory Quality Evaluationen_US
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SCA 2021: Eurographics/SIGGRAPH Symposium on Computer Animation