Estimating method of main curvature and main direction of point cloud data

Abstract

The invention relates to an estimating method of the main curvature and the main direction of point cloud data, which comprises the following steps of: preprocessing, estimating a normal transversal curvature, fitting a Weingarten matrix, computing the characteristic value and the characteristic vector of the Weingarten matrix and computing the main curvature and the main direction. In the method, the main curvature and the main direction faithful to an original object are obtained only by utilizing the scanning data and the estimated normal vector of a laser scanner. The main curvature and the main direction are computed by the method through least square linear fitting and the characteristic value and the characteristic vector of the matrix, the algorithm is simple, the computing result is accurate, and the time complexity is highly effective. The method is called as a normal transversal fitting method, and the computing result thereof has important application value in the fields of virtual reality, computer games, natural scene simulation, urban landscape design, data compression, characteristic extraction, object 3D reconstruction and the like.

Description

technical field [0001] The invention relates to a method in the technical fields of differential geometry, computational mathematics, computer graphics and computer vision, which uses a three-dimensional laser scanner to measure physical objects to obtain point cloud data, and calculates principal curvature and principal direction according to the point cloud data. It has important application value in the fields of virtual reality, computer games, natural scene simulation, urban landscape design, data compression, feature extraction, and physical 3D reconstruction. Background technique [0002] With the improvement of the accuracy of laser scanners, the information obtained by scanning is becoming more and more abundant, and the model data obtained by scanning is becoming larger and larger. People use these huge data for feature extraction, data compression or 3D reconstruction. However, the realization of these works often requires the estimation of some differential geom...

AI Technical Summary

Problems solved by technology

For the current results, when calculating directly from the point cloud, some methods only use the position information of the point, and do not use the normal vector information of each point, which will make the method less robust; there are also some methods t...

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