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Real-Time GPU Surface Curvature Estimation on Deforming Meshes and Volumetric Data Sets
Oct. 2012 (vol. 18 no. 10)
pp. 1603-1613
Wesley Griffin, University of Maryland, Baltimore County, Baltimore
Yu Wang, University of Maryland, Baltimore County, Baltimore
David Berrios, National Aeronautics and Space Administration, Greenbelt
Marc Olano, University of Maryland, Baltimore County, Baltimore
Surface curvature is used in a number of areas in computer graphics, including texture synthesis and shape representation, mesh simplification, surface modeling, and nonphotorealistic line drawing. Most real-time applications must estimate curvature on a triangular mesh. This estimation has been limited to CPU algorithms, forcing object geometry to reside in main memory. However, as more computational work is done directly on the GPU, it is increasingly common for object geometry to exist only in GPU memory. Examples include vertex skinned animations and isosurfaces from GPU-based surface reconstruction algorithms. For static models, curvature can be precomputed and CPU algorithms are a reasonable choice. For deforming models where the geometry only resides on the GPU, transferring the deformed mesh back to the CPU limits performance. We introduce a GPU algorithm for estimating curvature in real time on arbitrary triangular meshes. We demonstrate our algorithm with curvature-based NPR feature lines and a curvature-based approximation for an ambient occlusion. We show curvature computation on volumetric data sets with a GPU isosurface extraction algorithm and vertex-skinned animations. We present a graphics pipeline and CUDA implementation. Our curvature estimation is up to {\sim}18{\times} faster than a multithreaded CPU benchmark.

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Index Terms:
Graphics processing unit,Isosurfaces,Face recognition,Real time systems,ambient occlusion.,Real-time rendering,GPU,geometry shader,curvature,line drawing
Citation:
Wesley Griffin, Yu Wang, David Berrios, Marc Olano, "Real-Time GPU Surface Curvature Estimation on Deforming Meshes and Volumetric Data Sets," IEEE Transactions on Visualization and Computer Graphics, vol. 18, no. 10, pp. 1603-1613, Oct. 2012, doi:10.1109/TVCG.2012.113
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