Point cloud registration method for three-dimensional reconstruction

Abstract

The invention discloses a point cloud registration method for three-dimensional reconstruction. The point cloud registration method comprises the steps of S101, acquiring three-dimensional point clouds at multiple view angles, and adopting three-dimensional point clouds at two view angles as a source point set and a target point set respectively; S102, constructing a KD-tree; S103, figuring out the normal vectors of all points in the source point set; S104, calculating an average value of the included angles of the normal vectors; S105, classifying points in the source point set and setting amaximum resolution, wherein the initial resolution is 1; S106, calculating the sampling proportion of each stage in the source point set at the current resolution and extracting a sampling point; S107, figuring out the matching point of the sampling point in the target point set on the basis of the matching degree in the method; S108, calculating a rotation matrix and a translation matrix by usinga quaternion method; S109, converting the source point set to obtain a new source point set; S110, repeating the steps from S107 to S109 until a objective function is the minimum; S111, if a preset condition is met, ending the process; otherwise, adding 1 to the current resolution, and returning to the step S106. According to the invention, low-resolution matching points are used for rapidly completing the registration. The high-resolution matching points are used for improving the precision. Meanwhile, matching points are searched for through the matching degree. The registration speed and the registration precision of large-scale point clouds are greatly improved.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a point cloud registration method for three-dimensional reconstruction. Background technique [0002] In recent years, with the increasing maturity of 3D scanning technology and the rapid development of computer vision technology, 3D reconstruction technology is being widely used in many fields such as 3D printing, machine vision, digital archaeology, medical development, etc. scholars' attention. [0003] Due to the limited scanning angle of view of the 3D scanning equipment, only a part of the point cloud data of the object can be obtained each time the object is measured. In the actual application process, the object is usually scanned multiple times from different angles of view and then registered to realize the reproduction of the 3D object. Therefore, point cloud registration is particularly important in the process of 3D object reconstruction. [00...

AI Technical Summary

Problems solved by technology

[0007] (1) The speed is fast, but the precision is low; the less key feature points are selected, the smaller the calculation amount is, and the faster the convergence speed is, but the precision is correspondingly lower

[0008] (2) The accuracy is high, but the speed is slow; the more key feature points are selected, the accuracy will be improved accordingly, but the speed is slow due to the increase in the amount of calculation

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