Parameter Estimation and Comparative Evaluation of Crowd Simulations

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dc.contributor.authorWolinski, Daviden_US
dc.contributor.authorGuy, Stephenen_US
dc.contributor.authorOlivier, Anne-Heleneen_US
dc.contributor.authorLin, Mingen_US
dc.contributor.authorManocha, Dineshen_US
dc.contributor.authorPettré, Julienen_US
dc.contributor.editorB. Levy and J. Kautzen_US
dc.date.accessioned2015-03-03T12:28:43Z
dc.date.available2015-03-03T12:28:43Z
dc.date.issued2014en_US
dc.description.abstractWe present a novel framework to evaluate multi-agent crowd simulation algorithms based on real-world observations of crowd movements. A key aspect of our approach is to enable fair comparisons by automatically estimating the parameters that enable the simulation algorithms to best fit the given data. We formulate parameter estimation as an optimization problem, and propose a general framework to solve the combinatorial optimization problem for all parameterized crowd simulation algorithms. Our framework supports a variety of metrics to compare reference data and simulation outputs. The reference data may correspond to recorded trajectories, macroscopic parameters, or artist-driven sketches. We demonstrate the benefits of our framework for example-based simulation, modeling of cultural variations, artist-driven crowd animation, and relative comparison of some widely-used multi-agent simulation algorithms.en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/cgf.12328en_US
dc.publisherThe Eurographics Association and John Wiley and Sons Ltd.en_US
dc.titleParameter Estimation and Comparative Evaluation of Crowd Simulationsen_US
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33-Issue 2
Full Papers 2014 - CGF 33-Issue 2