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Characteristic-maintained point cloud data compacting method

A point cloud data and feature preservation technology, applied in image data processing, 3D modeling, instruments, etc., can solve a large number of time-consuming problems

Inactive Publication Date: 2012-10-24
BEIJING INSTITUTE OF TECHNOLOGYGY
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  • Claims
  • Application Information

AI Technical Summary

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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  • Characteristic-maintained point cloud data compacting method
  • Characteristic-maintained point cloud data compacting method
  • Characteristic-maintained point cloud data compacting method

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Embodiment Construction

[0098] 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.

[0099] For example figure 1 The original point cloud data shown is simplified, and the total reduction rate of the point cloud data is set to 93%.

[0100] A feature-preserving point cloud data reduction method, the specific steps of which are as follows:

[0101] Step 1. The first streamlining of the original point cloud data, the operation process includes steps 1.1 to 1.7, specifically:

[0102] Step 1.1: Read raw point cloud data.

[0103] Step 1.2: Obtain the 8th order neighborhood of each data point and calculate the unit normal vector of each data point.

[0104] The method for obtaining the 8th-order neighborhood of each data point is an octree method.

[0105] The method for calculating the unit normal vector of each data point is principal component analys...

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Abstract

The invention relates to a characteristic-maintained point cloud data compacting method and belongs to the technical field of computer three-dimensional modeling. The compacting method comprises first performing primary compaction on original point cloud data according to sampling rate, then adjusting categories of remaining data points according to categories of current remaining data points and the number of removed points in k-order neighborhoods of the remaining data points, and carrying out secondary compaction on remaining point cloud according to sampling rate. Compared with a traditional method, the characteristic-maintained point cloud data compacting method has the advantages of being capable of maintaining detailed characteristics of the original point cloud data, avoiding time cost of complex quadric surface fitting and curvature estimation and being capable of effectively avoiding occurrence of holes in compacted point cloud.

Description

technical field [0001] The invention relates to a feature-preserving point cloud data reduction method, which 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, and it can be used to complete the reconstruction of the physical model after obtaining the 3D point cloud data of the 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 high sca...

Claims

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Application Information

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IPC IPC(8): G06T17/00
Inventor 李凤霞饶永辉王青云谢宝娣
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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