Method for automatically registering cloud data of laser dots based on three-dimensional line characters

Abstract

The invention discloses a method for automatically registering cloud data of laser dots based on three-dimensional line characters. The method comprising the steps that a line characteristic set is extracted from the cloud data of the laser dots from each site for two adjacent sites; two arbitrary nonparallel space-straight-lines are regarded as a straight line pair, and the included angle and the vertical distance of the straight line pair are regarded as two rotation invariants for any site of the two adjacent sites; when the rotation invariants are eligible, the referenced straight line pair and the straight line pair to be registered become a pair of candidate straight line pair of the same name; c initial transform relations are respectively calculated by c pairs of candidate straight line pair of the same name, one initial transform relation is chosen to be the optimal initial transform relation, and all the straight line pairs of the same name of the site to be registered and the referenced site are calculated; the transform relation between the site to be registered and the referenced site is calculated by all the straight line pairs of the same name. The method disclosed by the invention utilizes the linear characters comprised in a target object to automatically register the cloud data of the laser dots without a target and acquire a three-dimensional data model of high quality.

Description

technical field [0001] The invention relates to an automatic registration method for laser point cloud data, in particular to an automatic registration method for laser point cloud data based on three-dimensional line features. Background technique [0002] Although terrestrial laser has become a relatively mature and widely used technology, automatic registration of multi-station laser point cloud data (referred to as "automatic registration") is still a relatively popular research direction. When the object is difficult to approach or the target is difficult to lay out, it is of great significance to study how to use the characteristics of the object to realize the effective automatic registration of point cloud data. It helps to reduce the cost of time, manpower and material resources, and enables non-professional users to obtain high-quality 3D data models. [0003] In practice, the method of target or manual identification is often used for registration. When the targe...

AI Technical Summary

Problems solved by technology

In the actual 3D laser scanning of the ground, the single-site cloud data has the characteristics of uneven point density, incomplete data (occlusion, viewing angle, etc.), and is easily affected by noise. Therefore, it is difficult to obtain ideal results based on algorithms such as curvature and local description features.

In actual measurement, ICP is a high-precision point cloud registration method, but requires high-resolution laser point cloud data

When the resolution of laser point cloud data is low, it is difficult to obtain ideal results by applying ICP

In addition, ICP needs to be optimized on the basis of the initial registration to achieve fine registration, and cannot be used alone as a registration method

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