Moving Least-Squares Reconstruction of Large Models with GPUs

Bruce Merry, James Gain, Patrick Marais
Department of Computer Science, University of Cape Town, and South African Centre for High Performance Computing
Transactions on Visualization and Computer Graphics, 2013


   title={Moving least-squares reconstruction of large models with GPUs},

   author={Merry, Bruce and Gain, James and Marais, Patrick},




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Modern laser range scanning campaigns produce extremely large point clouds, and reconstructing a triangulated surface thus requires both out-of-core techniques and significant computational power. We present a GPU-accelerated implementation of the Moving Least Squares (MLS) surface reconstruction technique. While several previous out-of-core approaches use a sweep-plane approach, we subdivide the space into cubic regions that are processed independently. This independence allows the algorithm to be parallelized using multiple GPUs, either in a single machine or a cluster. It also allows data sets with billions of point samples to be processed on a standard desktop PC. We show that our implementation is an order of magnitude faster than a CPU-based implementation when using a single GPU, and scales well to 8 GPUs.
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