IEEE Trans Vis Comput Graph - Moving Least-Squares Reconstruction of Large Models with GPUs.

Tópicos

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Resumo

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.

Resumo Limpo

modern laser rang scan campaign produc extrem larg point cloud reconstruct triangul surfac thus requir outofcor techniqu signific comput power present gpuacceler implement move least squar mls surfac reconstruct techniqu sever previous outofcor approach use sweepplan approach subdivid space cubic region process independ independ allow algorithm parallel use multipl gpus either singl machin cluster also allow data set billion point sampl process standard desktop pc show implement order magnitud faster cpubas implement use singl gpu scale well gpus

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