Yinghao Li1,2,3, Renbo Xia1,2,*, Jibin Zhao1,2,*, Yueling Chen1,2, Liming Tao1,2,3, Hangbo Zou1,2,3, Tao Zhang1,2,3
CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 555-571, 2023, DOI:10.32604/cmes.2023.024470
Abstract As 3D acquisition technology develops and 3D sensors become increasingly affordable, large quantities of 3D point cloud data are emerging. How to effectively learn and extract the geometric features from these point clouds has become an urgent problem to be solved. The point cloud geometric information is hidden in disordered, unstructured points, making point cloud analysis a very challenging problem. To address this problem, we propose a novel network framework, called Tree Graph Network (TGNet), which can sample, group, and aggregate local geometric features. Specifically, we construct a Tree Graph by explicit rules, which consists of curves extending in all… More >
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