Simplification method used for point cloud data of large-scene high-precision three-dimension laser measurement

Abstract

The invention relates to a simplification method used for point cloud data of large-scene high-precision three-dimension laser measurement. The method can support fast simplification of the point cloud data of large-scene high-precision three-dimension laser scanning, and maintain key features in the point cloud data at the same time, and belongs to the field of three-dimension modeling technology. According to the method, a uniform grid method is adopted to carry out spatial uniform division on scattered point cloud, a grid index corresponding to the point cloud data is established, and spatial locations are utilized to fast find K neighborhoods of data points; point cloud feature points are extracted according to projection residual-values, surface variation values are utilized to carry out region division on the point cloud data; and region division and the surface variation values of the data points are utilized to simplify the original point cloud, and simplified point cloud data is finally obtained. According to the method of the invention, the data, of which a data amount is more than 100 million points, of high-precision scanning can be fast simplified, the execution speed is fast, key feature points in a scene can be maintained while the data capacity is effectively reduced, and carrying out latter three-dimension modeling and other works is facilitated.

Description

technical field [0001] The invention relates to a simplification method for high-precision three-dimensional laser measurement point cloud data in large scenes, which can support the rapid simplification of large scenes and high-precision three-dimensional laser scanning point cloud data, while maintaining key features in the point cloud data, and belongs to three-dimensional construction. mold technology. Background technique [0002] With the continuous improvement of the measurement accuracy of 3D scanners, the collected point clouds become denser and contain richer details. However, huge point cloud data brings a lot of inconvenience to subsequent processing, storage, display and transmission. If it is processed directly, it will inevitably take up a lot of hardware resources and time, and not all data points need to be used for subsequent processing, too dense point cloud data will affect the quality of 3D object reconstruction during the visualization process. The ex...

AI Technical Summary

Problems solved by technology

[0003] Aiming at the large scene, high-precision 3D laser scanning point cloud data is huge, direct storage takes up a lot of space, and cannot be directly transmitted, 3D modeling, display and other shortcomings, the present invention provides a simplified method for 3D laser measurement point cloud data , can support rapid simplification of large-scale, high-precision 3D laser scanning point cloud data, effectively reduce data redundancy, and maintain key features and details in point cloud data