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Point cloud data compacting method based on normal included angle

A technology of point cloud data and included angle, applied in image data processing, 3D modeling, instruments, etc., can solve time-consuming, large-scale and other problems

Inactive Publication Date: 2013-01-23
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

The establishment of the surface equation requires the use of the least squares method to approximate the fitting surface, and the curvature estimation of the surface requires a large number of matrix operations. Therefore, the curvature reduction method is time-consuming, especially when dealing with large-scale point cloud data, this defect is more obvious

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  • Point cloud data compacting method based on normal included angle
  • Point cloud data compacting method based on normal included angle
  • Point cloud data compacting method based on normal included angle

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Embodiment Construction

[0074] In order to better illustrate the technical solution of the present invention, the present invention will be further described below through an embodiment in conjunction with the accompanying drawings.

[0075] For example figure 2 The original point cloud data shown is simplified, and the total reduction rate of the set point cloud data is 73.55%.

[0076] A point cloud data reduction method based on the normal angle, the operation process includes steps 1 to 7, the operation process is as follows figure 1 As shown, specifically:

[0077] Step 1. Read as figure 2 Raw point cloud data shown.

[0078] Step 2: Obtain the 8th-order neighborhood of each data point, and calculate the unit normal vector of each data point. The method of obtaining the 8th-order neighborhood of each data point is the octree method; the method of calculating the unit normal vector of each data point is the principal component analysis method.

[0079] Step 3: Obtain the mean value V of th...

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Abstract

The invention relates to a point cloud data compacting method based on a normal included angle, and belongs to the technical field of computer three-dimensional modeling. The compacting method comprises the following steps of: (1) reading the original point cloud data; (2) acquiring a k-order neighborhood of each data point, and calculating a unit normal vector of each data point; (3) acquiring an average value V of dot products of the normal vector of each data point and normal vectors of k proximal points of the data point; (4) acquiring the curvature V' of a local region where each data point is positioned; (5) classifying all data points in a point cloud; (6) determining a sampling ratio of each class; and (7) compacting the point cloud data. Compared with the traditional method, the method has the advantages that the detail features of the original point cloud can be kept, and the time cost of complicated quadric surface fitting and curvature estimation is avoided.

Description

technical field [0001] The invention relates to a point cloud data simplification method based on normal angles, and belongs to the technical field of computer three-dimensional modeling. Background technique [0002] In reverse engineering, the 3D scanner is widely used as a main tool, which can be used to obtain the 3D point cloud data of the model, so as to complete the reconstruction of the physical model. A point cloud can also be called an unorganized data set. There is no relationship between data points. It is a collection of pure three-dimensional points, which are defined by x, y, and z coordinates. The current point cloud data obtained by the scanning measurement method is dense and scattered data with a huge amount of data, and there is no corresponding and explicit geometric topology relationship between the measurement point data. [0003] Traditional 3D scanners are optical 3D scanners, which are more suitable for accurate 3D modeling of small objects, have h...

Claims

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Application Information

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IPC IPC(8): G06T17/00
Inventor 李凤霞陈宇峰饶永辉李仲君赵三元谢宝娣
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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