A 3D Point Cloud Registration Method with Low Overlap Rate
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A 3D point cloud and overlap rate technology, applied in image analysis, image enhancement, instruments, etc., can solve the problems of difficulty and low accuracy in the registration of two point clouds, achieve superior registration accuracy and time efficiency, narrow the search Scope, the effect of reducing the amount of calculation
Active Publication Date: 2022-04-12
ZHONGBEI UNIV
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[0005] Aiming at the problems of high difficulty and low precision in registration of two point clouds with low overlap rate, the present invention provides a 3D point cloud registration method with low overlap rate
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Embodiment 1
[0064] Such as figure 1 As shown, a low overlap rate 3D point cloud registration method includes the following steps:
[0065] Step 1, construct multi-scale descriptors based on curvature features and normal vectors;
[0066] Step 1.1, for each query point P in each neighborhood radius r l Build the covariance matrix,
[0067]
[0068] Among them, the scale l=1,...,L; the neighborhood radius corresponding to the scale is expressed as r 1 2 L , S l Indicates that the distance from the query point P is within the neighborhood radius r l The set S of points in the range l ={P i |||P i -P||≤r l};
[0069] Step 1.2, use the singular value decomposition algorithm SVD decomposition formula (1) to obtain three eigenvalues λ l1 ≥λ l2 ≥λ l3 and its corresponding eigenvector n l1 , n l2 , n l3 , the eigenvector n corresponding to the smallest eigenvalue l3 That is, the normal vector of the plane, denoted as n l ;Set the direction of the normal vector of the area to ...
Embodiment 2
[0108] The data comes from the 3D point cloud model published by Stanford University and the entity 3D scanning data from the geometryhub website. The environment is a 64-bit operating system of Windows 10 and a development platform of MATLAB 2018b.
[0109] When the overlap rate of the source point cloud and the target point cloud is lower than 60%, the degree of overlap of the two point clouds is low, and when their overlap rate is higher than 60%, the degree of overlap is high. In order to prove the effectiveness of the method proposed by the present invention, it is divided into two cases with high overlap rate and low overlap rate.
[0110] For the point cloud model, the point cloud data acquired under different viewing angles are used to reflect their overlapping ratio. Select several representative sets of data for the results display. Point cloud data with high overlap rate: Bunny000, Bunny045 and Dragon000, Dragon024 two sets of point cloud data, they have obvious o...
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Abstract
The invention discloses a three-dimensional point cloud registration method with a low overlap rate, and belongs to the technical field of machine vision. Aiming at the problems of difficulty and low precision in the registration of two point clouds with low overlap rate. First, use the curvature feature of the point cloud to establish a multi-scale descriptor to ensure the integrity of the point cloud data and minimize redundant data; secondly, use the angle difference of the multi-scale descriptor to cluster and block the corresponding relationship to obtain the source point cloud The overlapping area with the target point cloud; finally, the point cloud in the overlapping area and their corresponding relationship are substituted into the convex optimization problem, and the outliers are removed and the corresponding relationship is optimized, and the coarse registration is realized and the ICP algorithm is used for refinement. The invention can narrow the useful search range of point cloud registration, reduce the amount of registration calculation, and provide more advantageous registration accuracy and time efficiency for point cloud data with a low initial overlapping degree. The method can be widely used in three-dimensional model reconstruction, cultural heritage management, robot navigation and positioning and other fields.
Description
technical field [0001] The invention belongs to the technical field of machine vision, and in particular relates to a three-dimensional point cloud registration method with a low overlap rate. Background technique [0002] In recent years, 3D point cloud data has been widely used in 3D model reconstruction, cultural heritage management, robot navigation and positioning and other fields. Fast and accurate 3D point cloud registration technology is the key technology and research focus. The goal of 3D point cloud registration is to find the optimal rigid body transformation that aligns two input point clouds to a common coordinate system. In practical applications, the data may be heavily occluded, and the overlapping area between two point clouds is small, which makes the process of finding the optimal rigid body transformation challenging. Therefore, finding fast, accurate, and robust registration algorithms for point clouds with smaller overlapping ranges is an active rese...
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