GPU-based offset surface computation using point samples - Wang, Charlie C.L.; Manocha, Dinesh (Computer aided design, 2013)
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 a GeForce GTX 580 GPU. We observe more than 100 times speedup over prior serial CPU-based approximate offset computation algorithms. ► A highly parallel algorithm based on structured point representation that is used to accelerate intersection computations between LDI rays and spheres centered at the sample points of LDI. ► An efficient load balancing algorithm that can distribute the merging operations on various GPU cores. ► The shape error of approximate offsetting on structured points is analyzed, and we show that the bound on shape approximation error converges as a monotonic function of the sampling rate.