公开(公告)号：US20230076092A1

公开(公告)日：2023-03-09

申请号：US17748185

申请日：2022-05-19

Applicant: Beijing University of Civil Engineering and Architecture

Inventor： Jianghong ZHAO ,  Xintong DOU ,  Yingxue ZHAO ,  Yinrui WANG ,  Ruiju ZHANG

IPC: G06V10/764 ,  G06T3/40 ,  G06V10/44 ,  G06V10/82 ,  G06V10/774

Abstract: A full-automatic classification method for a three-dimensional point cloud, including: acquiring a three-dimensional point cloud dataset; performing down-sampling on a three-dimensional point cloud represented by the three-dimensional point cloud dataset, selecting some points in the three-dimensional point cloud as sampling points, constructing a point cloud area group based on each sampling point, extracting a global feature of each point cloud area group, and replacing the point cloud area group where the sampling point is located with the sampling point; performing up-sampling on the three-dimensional point cloud, and performing splicing fusion on the global features of the point cloud area group where each point in the three-dimensional point cloud is located; performing category discrimination on each point in the three-dimensional point cloud; performing statistics on the number of points contained in each category, and selecting the category with the largest number of points as the category of the three-dimensional point cloud.