Point cloud registering method based on iterative closest point algorithm

A point cloud registration and iterative technology, applied in the computer field, can solve the problems of being easily affected by noise data, low registration accuracy, and underutilization, etc., and achieves high accuracy, high robustness, robustness and high precision effect

Inactive Publication Date: 2015-06-10
XIDIAN UNIV
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Problems solved by technology

However, the shortcomings of this method are that the registration elements of this method are boundary feature points and prominent feature points, which ar

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  • Point cloud registering method based on iterative closest point algorithm
  • Point cloud registering method based on iterative closest point algorithm
  • Point cloud registering method based on iterative closest point algorithm

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Embodiment Construction

[0056] The present invention will be further described below in conjunction with the drawings.

[0057] Reference figure 1 The specific implementation steps of the present invention are as follows:

[0058] Step 1. Obtain the point cloud.

[0059] Choose different scene scanning methods according to the scene to obtain the point cloud of the object to be scanned. Specifically, ensure that the laser point cloud data of two adjacent stations have an overlapping area in the scanning angle of the scanner. The actual scanning should ensure that the angle of view is at least greater than 90°, for these different scanning scenes and scanning parameters of the scanner, adjust the viewing angle of each scan and the data collection distance of the two stations. The scene scanning method is as follows: if the scene is centered around the object to be scanned To move the scanner, select multi-view scanning, scan from multiple directions around the object to be scanned, and obtain a point cloud ...

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Abstract

The invention discloses a point cloud registering method based on an iterative closest point algorithm. The point cloud registering method based on the iterative closest point algorithm is implemented through the steps of (1) obtaining a point cloud; (2) preprocessing the point cloud; (3) obtaining a reference space to be expanded and a target space to be expanded; (4) obtaining a reference space to be registered and a target space to be registered; (5) registering a reference point cloud and a target point cloud; (6) if determining that all segmented point clouds complete registration, performing the step (7), if not, returning to the step (2); (7) outputting a registration result. According to the point cloud registering method based on the iterative closest point algorithm, the point cloud to be registered is obtained according to scenes and through different scanning manners; then through the steps of rough registration, precise registration, corresponding point maximization and the like as well as registration score correction, the possibility of falling into local solution can be reduced, and the robustness and the registering precision can be improved. Therefore, the point cloud registering method based on the iterative closest point algorithm can be applied to registering point clouds of complex scenes.

Description

Technical field [0001] The present invention belongs to the field of computer technology, and further relates to a point cloud registration method based on an iterative closet point (ICP) algorithm in the field of computer vision technology. The present invention can be applied to specific application scenarios such as 3D printing and 3D reconstruction. Aiming at the limitations of the existing iterative nearest point algorithm, according to different point cloud scanning methods, different point cloud registration processes are adopted to realize a unified coordinate system for three-dimensional data. Conversion to construct a complete 3D point cloud model. Background technique [0002] Point cloud registration is to convert several pieces of 3D point cloud data scanned from different angles and different positions into a unified coordinate system to obtain a complete 3D model. The existing automatic point cloud registration methods can be roughly divided into three categories:...

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Application Information

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IPC IPC(8): G06T17/00
CPCG06T17/00
Inventor 刘惠杜军朝刘杰姚士民李国雄代小飞宋尧
Owner XIDIAN UNIV
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