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dc.contributor.authorKammaje, Ravi P.en_US
dc.contributor.authorMora, Benjaminen_US
dc.contributor.editorR. Laramee and I. S. Limen_US
dc.date.accessioned2014-02-06T15:37:13Z
dc.date.available2014-02-06T15:37:13Z
dc.date.issued2011en_US
dc.identifier.issn1017-4656en_US
dc.identifier.urihttp://dx.doi.org/10.2312/EG2011/posters/045-046en_US
dc.description.abstractRay tracing random rays has been a challenge. Due to their reduced coherence, the normal methods of acceleration like packet tracing that make use of coherence of the rays do not work well. These random rays are encountered in global illumination methods. 5D ray classification, first introduced by Arvo and Kirk [AK87], can classify these rays into coherent groups. We introduce a method that builds a hierarchical structure identifying coherence in random rays very quickly using the increased processing power of the GPU.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): Comp. Graph. [I.3.6]: Methodology and Techniquesen_US
dc.titleAccelerated 5D Ray Tree construction on the GPUen_US
dc.description.seriesinformationEurographics 2011 - Postersen_US


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