Moving Least-Squares Reconstruction of Large Models with GPUs

Merry, Bruce and Gain, James and Marais, Patrick (2014) Moving Least-Squares Reconstruction of Large Models with GPUs, IEEE Transactions on Visualization and Computer Graphics, 20, 249-261, IEEE Computer Society.

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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.

Item Type: Journal article (paginated)
Uncontrolled Keywords: moving least squares, surface reconstruction, GPU, out of core
Subjects: Computing methodologies > Computer graphics
Alternate Locations:
Date Deposited: 03 Sep 2014
Last Modified: 10 Oct 2019 15:32

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