Point cloud reconstruction method and system based on three-dimensional point cloud data feature lightweight

Abstract

The invention relates to a point cloud reconstruction method and system based on three-dimensional point cloud data feature lightweight, high-precision mass three-dimensional point cloud data acquisition is carried out on a measured object, and a point cloud data result is closer to the real morphology of the measured object. According to the method, feature point cloud extraction is carried out on collected massive three-dimensional point cloud data, an outlier extraction method is adopted to process the surface topography of a measured object, feature point cloud data on the surface of the measured object are acquired, and a point cloud region growth segmentation method is adopted to acquire feature point cloud data at the edge of the measured object in combination with a normal includedangle criterion. On the premise of reserving the feature point cloud data, down-sampling is performed on the remaining point cloud data so that lightweight processing of the point cloud can be realized. According to the method, sliding least square fitting is carried out on the point cloud data after lightweight processing, so that the point cloud data can reserve fine features of the surface, and point cloud reconstruction is carried out on the fitted point cloud data, thereby generating a measured object entity model reserving key morphological features.

Description

technical field [0001] The present invention relates to a point cloud reconstruction method and system based on lightweight features of three-dimensional point cloud data, and is mainly a technology and method for feature lightweight and reconstruction of massive three-dimensional point cloud data. Background technique [0002] Three-dimensional point cloud is a collection of massive point space coordinates expressing spatial distribution and surface characteristics obtained by measuring instruments under the same spatial reference system. Point cloud processing technology is applied in reverse engineering, CAD / CAM, robotics, laser remote sensing measurement, machine Vision, virtual reality, human-computer interaction, stereoscopic 3D images and many other fields, involving computer science, graphics, artificial intelligence, pattern recognition, geometric computing, sensors and many other disciplines. [0003] At present, 3D point cloud measurement equipment can acquire ten...

AI Technical Summary

Problems solved by technology

[0003] At present, 3D point cloud measurement equipment can acquire tens of thousands or even hundreds of thousands of data points with high efficiency and high precision. On the one hand, massive point cloud data can represent more complex and fine surface topography of the measured object. Massive point cloud data will affect the efficiency of subsequent point cloud data processing and reconstruction

Images