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dc.contributor.authorDyken, Christopheren_US
dc.contributor.authorZiegler, Gernoten_US
dc.contributor.authorTheobalt, Christianen_US
dc.contributor.authorSeidel, Hans-Peteren_US
dc.date.accessioned2015-02-21T13:21:51Z
dc.date.available2015-02-21T13:21:51Z
dc.date.issued2008en_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttp://dx.doi.org/10.1111/j.1467-8659.2008.01182.xen_US
dc.description.abstractWe present an implementation approach for Marching Cubes (MC) on graphics hardware for OpenGL 2.0 or comparable graphics APIs. It currently outperforms all other known graphics processing units (GPU)-based iso-surface extraction algorithms in direct rendering for sparse or large volumes, even those using the recently introduced geometry shader (GS) capabilites. To achieve this, we outfit the Histogram Pyramid (HP) algorithm, previously only used in GPU data compaction, with the capability for arbitrary data expansion. After reformulation of MC as a data compaction and expansion process, the HP algorithm becomes the core of a highly efficient and interactive MC implementation. For graphics hardware lacking GSs, such as mobile GPUs, the concept of HP data expansion is easily generalized, opening new application domains in mobile visual computing. Further, to serve recent developments, we present how the HP can be implemented in the parallel programming language CUDA (compute unified device architecture), by using a novel 1D chunk/layer construction.en_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltden_US
dc.titleHigh-speed Marching Cubes using HistoPyramidsen_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume27en_US
dc.description.number8en_US
dc.identifier.doi10.1111/j.1467-8659.2008.01182.xen_US
dc.identifier.pages2028-2039en_US


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