SteerFit: Automated Parameter Fitting for Steering Algorithms

dc.contributor.authorBerseth, Glenen_US
dc.contributor.authorKapadia, Mubbasiren_US
dc.contributor.authorHaworth, Brandonen_US
dc.contributor.authorFaloutsos, Petrosen_US
dc.contributor.editorVladlen Koltun and Eftychios Sifakisen_US
dc.date.accessioned2014-12-16T07:33:54Z
dc.date.available2014-12-16T07:33:54Z
dc.date.issued2014en_US
dc.description.abstractIn the context of crowd simulation, there is a diverse set of algorithms that model steering. The performance of steering approaches, both in terms of quality of results and computational efficiency, depends on internal parameters that are manually tuned to satisfy application-specific requirements. This paper investigates the effect that these parameters have on an algorithm's performance. Using three representative steering algorithms and a set of established performance criteria, we perform a number of large scale optimization experiments that optimize an algorithm's parameters for a range of objectives. For example, our method automatically finds optimal parameters to minimize turbulence at bottlenecks, reduce building evacuation times, produce emergent patterns, and increase the computational efficiency of an algorithm. We also propose using the Pareto Optimal front as an efficient way of modelling optimal relationships between multiple objectives, and demonstrate its effectiveness by estimating optimal parameters for interactively defined combinations of the associated objectives. The proposed methodologies are general and can be applied to any steering algorithm using any set of performance criteria.en_US
dc.description.seriesinformationEurographics/ ACM SIGGRAPH Symposium on Computer Animationen_US
dc.identifier.isbn978-3-905674-61-3en_US
dc.identifier.issn1727-5288en_US
dc.identifier.urihttps://doi.org/10.2312/sca.20141129en_US
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/sca.20141129.113-122
dc.publisherThe Eurographics Associationen_US
dc.titleSteerFit: Automated Parameter Fitting for Steering Algorithmsen_US
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