A 3D point cloud registration method based on weighted principal component analysis and m estimation

A weighted principal component and 3D point cloud technology, applied in the field of 3D reconstruction, can solve the problems of ignoring the irregularities of 3D objects and failing to take into account the local structural characteristics of point clouds

Active Publication Date: 2020-10-27
XI AN JIAOTONG UNIV
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Problems solved by technology

Because PCA pays attention to the overall structural characteristics, the distance difference used in the implementation is the difference between the point cloud data and the center of gravity of the point cloud, ignoring the irregularity of the shape of the three-dimensional object itself, and unable to take into account the local structural characteristics of each point in the point cloud

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  • A 3D point cloud registration method based on weighted principal component analysis and m estimation
  • A 3D point cloud registration method based on weighted principal component analysis and m estimation
  • A 3D point cloud registration method based on weighted principal component analysis and m estimation

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Embodiment Construction

[0061] The invention provides a three-dimensional point cloud registration method based on weighted principal component analysis and M estimation,

[0062] First, the weighted PCA algorithm is used for rough registration, and the K nearest neighbor algorithm is used to calculate the K nearest neighbor points of each data point, and the adjacent points are sorted according to the distance between the neighbor points and the data point. Neighbors with small distances have a greater influence on the data points, while neighbors with greater distances have less influence on the data points. Therefore, different weights are given to adjacent points according to the distance between adjacent points and data points, so as to preserve the local characteristics of 3D point cloud data;

[0063] Secondly, due to the large amount of 3D point cloud data, it will take a lot of time to fine-register the data directly, so the simplification method is used to simplify the number of point cloud...

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Abstract

The invention discloses a three-dimensional point cloud registration method based on a weighted principal component analysis method and M estimation, and the method comprises the steps of firstly, obtaining a rough and initial conversion relation through a weighted PCA algorithm, and achieving the rough registration of an original point cloud and a target point cloud; then, in order to quickly obtain an accurate rotation translation matrix, using the BP neural network and the two-dimensional moving window for simplifying the number of point clouds of the rotation translation matrix; and finally, adopting a Cauchy function with resistance to noise as an objective function, calculating an accurate alignment relation according to an ICP algorithm, and realizing the accurate registration. According to the method, the time, the space complexity and the algorithm complexity of the registration algorithm can be effectively reduced, and an accurate conversion relation can be obtained for the original point cloud containing noise and abnormal points.

Description

technical field [0001] The invention belongs to the technical field of three-dimensional reconstruction, and in particular relates to a three-dimensional point cloud registration method based on weighted principal component analysis and M estimation. Background technique [0002] With the rapid development of depth sensing equipment, the research object of computer vision technology has gradually converted from two-dimensional images and LIDAR scanning data to three-dimensional point cloud data. Due to the limitation of the measurement range of the site or the measuring instrument, a three-dimensional object is often presented as several fragments of point cloud data from different perspectives. In order to obtain the complete point cloud data of the object, it needs to be transformed into the same coordinate system through the registration method. Point cloud registration methods can be divided into coarse registration and fine registration. The main purpose of coarse reg...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/33
CPCG06T2207/10028G06T7/344
Inventor 李兵辛美婷魏翔陈磊赵卓高飞
Owner XI AN JIAOTONG UNIV
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