Refined Adaptive Meshes from Scattered Point Clouds
Distributed Computing and Applications to Business, Engineering & Science(2013)
摘要
This paper presents a new method for adaptive mesh generation from scattered point clouds. We develop new techniques for extracting geometric features from scattered point clouds. In addition, we present how to incorporate these geometric features into implicit mathematical models for fitting scattered, noisy point clouds. This method is also well suited for large and potentially noisy scattered point clouds. Our numerical experiments show that the new adaptive mesh generation algorithms can improve the accuracy of the mesh generation from computed tomography (CT) images.
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关键词
adaptive mesh generation,scattered point cloud,adaptive mesh generation algorithm,computerised tomography,scattered cloud fitting,mesh generation,computed tomography,computational geometry,noisy scattered point cloud,mathematical model,refined adaptive meshes,curve fitting,noisy point cloud fitting,point clouds,scattered point clouds,feature extraction,scattered data,geometric feature,thresholding,new technique,new adaptive mesh generation,noisy point cloud,ct image,new method,geometric feature extraction
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