GPU-based Offset Surface Computation using Point Samples

Charlie C. L. Wang, Dinesh Manocha
Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong
Symposium on Solid and Physical Modeling, 2012


   title={GPU-based Offset Surface Computation using Point Samples},

   author={Wang, C.C.L. and Manocha, D.},



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We present an efficient algorithm to perform approximate offsetting operations on geometric models using GPUs. Our approach approximates the boundary of an object with point samples and computes the offset by merging the balls centered at these points. The underlying approach uses Layered Depth Images (LDI) to organize the samples into structured points and performs parallel computations using multiple cores. We use spatial hashing to accelerate intersection queries and balance the workload among various cores. Furthermore, the problem of offsetting with a large distance is decomposed into successive offsetting using smaller distances. We derive bounds on the accuracy of offset computation as a function of the sampling rate of LDI and offset distance. In practice, our GPU-based algorithm can accurately compute offsets of models represented using hundreds of thousands of points in a few seconds on GeForce GTX 580 GPU. We observe more than 100 times speedup over prior serial CPU-based approximate offset computation algorithms.
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