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dc.contributor.authorDiktas, Engin Denizen_US
dc.contributor.authorSahiner, Ali Vahiten_US
dc.contributor.editorIk Soo Lim and Wen Tangen_US
dc.date.accessioned2014-01-31T20:02:22Z
dc.date.available2014-01-31T20:02:22Z
dc.date.issued2008en_US
dc.identifier.isbn978-3-905673-67-8en_US
dc.identifier.urihttp://dx.doi.org/10.2312/LocalChapterEvents/TPCG/TPCG08/107-113en_US
dc.description.abstractPerformanceof static collision detection queries depends on the type of the hierarchy chosen as well as the relative positioning of the colliding objects. In order to evaluate the performance of bounding volume hierarchies, relevant criteria that affect the query performance need to be determined and the sample space should be generated accordingly. In this paper we present a benchmarking framework for evaluating the performance of various static collision detection algorithms. In this framework, instances of a moving rigid object are placed on the surface of another instance of the same object fixed at a certain position, where the contact occurs for the first time. Then by offsetting the surface inwards (outwards) we generate new surfaces that are at a certain fixed negative (positive) distance to the original surface. Placing the moving object on these offset surfaces makes the object penetrate (approach) the fixed object at a fixed distance. For offset surface generation we create a signed distance field and run marching cubes algorithm on it.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.5 [Computer Graphics]: Computational Geometry and Object Modelingen_US
dc.titleA Benchmarking Framework for Static Collision Detectionen_US
dc.description.seriesinformationTheory and Practice of Computer Graphicsen_US


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