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A point cloud automatic registration method based on a local curved surface feature histogram

A feature histogram and automatic registration technology, applied in the field of computer vision, can solve problems such as large amount of calculation and low computational efficiency

Active Publication Date: 2019-06-14
HARBIN ENG UNIV
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Problems solved by technology

The FPFH feature needs to calculate the angular features of any point and its k-adjacent points connected to each other in pairs, the calculation amount is relatively large, and the calculation efficiency is low

Method used

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  • A point cloud automatic registration method based on a local curved surface feature histogram
  • A point cloud automatic registration method based on a local curved surface feature histogram
  • A point cloud automatic registration method based on a local curved surface feature histogram

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Embodiment Construction

[0064] The present invention will be further described below in conjunction with the accompanying drawings.

[0065] The point cloud used in the present invention is obtained by a laser triangulation ranging scanner. The implementation is given using four sets of point cloud data of bunny, cheff, dragon and armadillo. When collecting point clouds, due to equipment or human reasons, there is a large gap between the resolution and the number of points in the collected point clouds, resulting in the need to manually set filtering and registration parameters during the registration process. At the same time, if there are too many points in the point cloud , will greatly prolong the registration time, and the registration often does not require excessively dense point clouds. rate adaptive adjustment of filter parameters. First, loop voxel filtering is performed on the source point cloud, the source point cloud is down-sampled to a specified number of points, and the target point...

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Abstract

The invention belongs to the technical field of computer vision, and particularly relates to a point cloud automatic registration method based on a local curved surface feature histogram. The method comprises the following steps: carrying out cyclic voxel filtering on a source point cloud, downsampling the source point cloud to a designated point number, and carrying out voxel filtering on a target point cloud according to the size of an obtained voxel; carrying out key point searching and feature description on the basis of points with the maximum neighborhood curvature mean value of pre-keypoints, detecting the points with the curvature larger than 0.02 and serve as the pre-key points, calculating the curvature mean value of the neighborhood points of the points, and classifying the points with the maximum local curved surface curvature mean value as the key points; calculating a feature descriptor of the local curved surface histogram according to the relationship between the center of gravity of the point cloud in the neighborhood of the key point and the normal and distance of each point in the neighborhood; and calculating a mutual corresponding relation between the source point cloud feature descriptor and the target point cloud feature descriptor, removing an error corresponding relation according to random sampling consistency, and estimating an optimal coordinate transformation matrix according to SVD. Application prospect is wide.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and in particular relates to an automatic point cloud registration method based on a local curved surface feature histogram. Background technique [0002] Reverse engineering technology is a new technology in the field of CAD today. It has brought a revolution to CAD technology by its unique means of directly constructing computer models from physical models. The data collected from the physical model in reverse engineering generally exist in the form of point cloud. With the rapid development of 3D scanning technology, the amount of point cloud data has become extremely large, which puts forward higher requirements for the performance of point cloud computing. Therefore, how to effectively improve the execution efficiency of the algorithm has always been a research hotspot and difficulty in this field. The mainstream registration idea is to find corresponding points by calculating poin...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/33
Inventor 陆军华博文乔鹏飞王伟陈万夏桂华
Owner HARBIN ENG UNIV
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