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.