Overall registering method for global optimization of multi-view three-dimensional laser point clouds

Abstract

The invention provides an overall registering method for carrying out automatic global optimization on registering initial values of existing multi-view laser point clouds. The overall registering method is characterized in that firstly, a multi-view laser point cloud registering global optimization overall adjustment model is established and detailedly deduced, and by estimating the density of the point cloud, all two-view clouds with a certain overlapping degree are automatically detected; then a K-D tree is used for searching for approximate homonymy points in the two-view clouds with the certain overlapping degree, the approximate homonymy points are used as observed values to be substituted into the global optimization overall adjustment model, respective optimal rotation and translation transformation parameters of the multi-view laser point clouds are obtained at the same time through iterative adjustment calculation, and therefore overall precise registering of the multi-view three-dimensional laser point clouds is achieved. The method lays emphasis on improvement of the overall registering precision of the multi-view three-dimensional laser point clouds, disordered and messy multi-view three-dimensional laser scanning point clouds can be treated at the same time, registering experiments are carried out through actual multi-view three-dimensional laser point cloud data, and results prove that on the basis of guaranteeing registering efficiency, the overall registering precision is improved effectively.

Description

technical field [0001] The invention belongs to the technical field of photogrammetry and computer vision, and in particular relates to a multi-view three-dimensional laser point cloud global optimization overall registration method. Background technique [0002] In recent years, 3D laser scanning measurement technology has developed rapidly and has been widely used in reverse engineering, industrial measurement, and digital protection of cultural relics. In practical applications, in order to obtain a complete 3D point cloud on the surface of the object, it is necessary to scan the measured object from multiple angles, and then it is necessary to register the multi-view laser point cloud into a unified coordinate system, so the registration accuracy will directly affect the final object. 3D reconstruction accuracy. Therefore, it is of great practical significance to globally optimize the overall registration of the 3D laser point cloud after the initial registration. [0...

AI Technical Summary

Problems solved by technology

This method has a high degree of automation, but it needs to obtain 3D point cloud data on the surface of the object with the help of a rotating platform, and at the same time needs to calibrate the relative positional relationship between the rotating platform and the scanner, so the applicability is relatively low

Liu Jun proposed a method for 3D registration of multi-viewpoint cloud based on sequence iteration. This method effectively suppresses the cumulative error of sequence registration, but the registration process is more manual and inefficient.

Images