Curve Skeleton Extraction From 3D Point Clouds Through Hybrid Feature Point Shifting and Clustering
Loading...
Date
2020
Journal Title
Journal ISSN
Volume Title
Publisher
© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd
Abstract
Curve skeleton is an important shape descriptor with many potential applications in computer graphics, visualization and machine intelligence. We present a curve skeleton expression based on the set of the cross‐section centroids from a point cloud model and propose a corresponding extraction approach. We first provide the substitution of a distance field for a 3D point cloud model, and then combine it with curvatures to capture hybrid feature points. By introducing relevant facets and points, we shift these hybrid feature points along the skeleton‐guided normal directions to approach local centroids, simplify them through a tensor‐based spectral clustering and finally connect them to form a primary connected curve skeleton. Furthermore, we refine the primary skeleton through pruning, trimming and smoothing. We compared our results with several state‐of‐the‐art algorithms including the rotational symmetry axis (ROSA) and ‐medial methods for incomplete point cloud data to evaluate the effectiveness and accuracy of our method.
Description
@article{10.1111:cgf.13906,
journal = {Computer Graphics Forum},
title = {{Curve Skeleton Extraction From 3D Point Clouds Through Hybrid Feature Point Shifting and Clustering}},
author = {Hu, Hailong and Li, Zhong and Jin, Xiaogang and Deng, Zhigang and Chen, Minhong and Shen, Yi},
year = {2020},
publisher = {© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd},
ISSN = {1467-8659},
DOI = {10.1111/cgf.13906}
}