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

A point cloud data and principal curvature technology, applied in the fields of differential geometry and computational mathematics, can solve the problems of increased calculation time and storage space overhead, poor robustness of the method, and no use, etc., to achieve superior time and space performance and calculation results accurate effect

Inactive Publication Date: 2010-06-23
INST OF AUTOMATION CHINESE ACAD OF SCI
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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 that use the method Vector information, but they often combine the first type of method and use the normal vector as a constraint condition, which increases the calculation time and storage space overhead of the principal curvature and principal direction model solution

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

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Embodiment Construction

[0033] Various details involved in the technical solution of the present invention will be described in detail below in conjunction with the accompanying drawings. It should be pointed out that the described embodiments are only intended to facilitate the understanding of the present invention, rather than limiting it in any way.

[0034] 1. Overview of approach

[0035] Such as figure 1 Show the flow process of the whole algorithm of the present invention, the main steps of the algorithm of the present invention include:

[0036] 1), data preprocessing, create a kd tree, and calculate the normal vector of each point of the point cloud data;

[0037] 2), Calculate the principal curvature and principal direction point by point, including 7 sub-steps: (a) establish a local coordinate system, (b) search for neighboring points, (c) localize the coordinates of neighboring points, (d) calculate the The normal curvature of the corresponding normal section line, (e) linearly fit th...

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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...

Claims

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Application Information

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IPC IPC(8): G06T17/00G01B11/24
Inventor 张晓鹏李红军程章林
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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