High‐speed Marching Cubes using HistoPyramids |
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| Authors: | Christopher Dyken Gernot Ziegler Christian Theobalt Hans‐Peter Seidel |
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| Affiliation: | 1. Centre of Mathematics for Applications, University of Oslo, Norway;2. SINTEF ICT Applied Mathematics, Norway;3. Max‐Planck‐Institut für Informatik, Germany;4. Max Planck Center for Visual Computing and Communication, Stanford University, Palo Alto, CA, USA |
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| Abstract: | We 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. |
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| Keywords: | volume processing marching cubes real‐time GPU GPGPU histopyramids OpenGL gather‐only data expansion geometry shader I 3 5 [Computer Graphics]: Computational Geometry and Object Modelling I 3 7 [Computer Graphics]: Three‐Dimensional Graphics and Realism |
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