Research on Optimal Down-Sampling Method of Segmental Beam Edge Based on Double Regions

Abstract

With the development of three-dimensional laser scanning technology, a large number of point cloud data generated has caused great computational pressure on storage, processing, and visualization. To this end, this paper proposes an edge-optimized voxel grid down-sampling method based on two regions, which aims to reduce the amount of data while preserving key geometric accuracy and details. By defining the two regions of point cloud data, this method proposes a two-region point cloud down-sampling model according to the different point cloud deviation characteristics of the two regions, so as to simplify the point cloud data volume and accurately identify and retain the edge contour feature points. The experimental results show that the proposed method performs well under both low-precision and high-precision conditions. It can maintain the geometric features and surface area of the point cloud while simplifying the point cloud. Compared with other methods, it has outstanding performance in the top surface contour deviation index and surface area change rate. It has a high accuracy retention ability and good simplification effect and is suitable for a variety of application scenarios.