Contact network three-dimensional reconstruction method based on SIFT and LBP point cloud registration

Abstract

The invention provides a contact network three-dimensional reconstruction method based on SIFT and LBP point cloud registration. The method comprises the first step of obtaining initial three-dimensional point cloud data of the environment where parts of a contact network to be reconstructed are located through motion-sensing peripheral Kinect for Windows, and conducting denoising, simplifying, partitioning clustering, fusing and other preprocessing operations on the initial three-dimensional point cloud data to obtain single-view-angle point cloud data of the parts of the contact network to be reconstructed, the second step of extracting key points through an SIFT algorithm, constructing description vectors of the key points by means of LBP features of uniform patterns and determining the corresponding relations between the key points in different point clouds according to the distances between the vectors, the third step of completing point cloud registration through a rough registration method and an ICP fine registration method and obtaining the complete three-dimensional point cloud data of the parts of the contact network to be reconstructed, and the fourth step of completing three-dimensional reconstruction through the Poisson surface reconstruction method and obtaining a three-dimensional model. According to the method, the key factor is point cloud registration which is the key step influencing the three-dimensional reconstruction speed; the description vectors of the key points are constructed by means of the LBP features of the uniform patterns, so that vector dimensions are reduced, the matching speed of the corresponding relations is increased, registration is accelerated, and the three-dimensional reconstruction speed is increased.

Description

technical field [0001] The invention relates to the field of obtaining a three-dimensional model of an electrified railway suspension device, and considers a point cloud registration method in a three-dimensional reconstruction process. Background technique [0002] Catenary is the main structure of railway electrification engineering, and its 3D model has broad application prospects in personnel training, fault detection, and catenary parameter design [1,2,3] . At present, most of the 3D models of catenary components are obtained by using 3D software such as 3DMax and drawing with reference to various catenary parameters. It takes a long time to obtain the model, the workload is large, and the obtained model is quite different from the actual model. Therefore, a new automatic reconstruction method is necessary. The specific idea is: use an optical scanner to obtain the point cloud data of each component of the catenary, and use a certain point cloud registration algorithm ...

AI Technical Summary

Problems solved by technology

[0003] At present, the research on 3D reconstruction using depth data is relatively extensive, such as point cloud simplification, point cloud registr

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