Point cloud data quality automatic optimizing method and system

一种点云数据、自动优化的技术，应用在图像数据处理、仪器、计算机零部件等方向，能够解决多人工参与、硬件设备测量精度依赖很高等问题，达到减少依赖性的效果

Active Publication Date: 2014-01-01
SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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Problems solved by technology

It can be seen that most of the existing high-precision 3D modeling technologies are highly dependent on the measurement accuracy of hardware equipment, and at the same time require more manual participation

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  • Point cloud data quality automatic optimizing method and system
  • Point cloud data quality automatic optimizing method and system

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Embodiment Construction

[0018] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.

[0019] refer to figure 1 As shown, it is a flow chart of a preferred embodiment of the method for automatic optimization of point cloud data quality in the present invention.

[0020] Step S401, collecting initial point cloud data of the object to be reconstructed to obtain an initial discrete point cloud. Specifically, a 3D laser scanner is used to treat reconstructed objects, especially for reconstructed objects with larger volumes and complex geometric structures, such as exquisite sculptures and other handicrafts in museums. Omni-directional scan to the right. Wherein, the three-dimensional laser scanner may be a hand-held device, or an ordinary laser scanning device installed at the end of a multi-degree-of-freedom mechanical arm. Regardless of some measurement blind spots caused by the laser measurement accuracy or the comple...

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Abstract

The invention relates to a point cloud data quality automatic optimizing method and system. The point cloud data quality automatic optimizing method includes the following steps of firstly, collecting initial point cloud data for a target object to be reconstructed to obtain initial disperse point cloud; secondly, conducting primary data cleaning on the obtained initial disperse point cloud to obtain an LOP sampling model; thirdly, using a Possion surface reconstruction method on the obtained initial disperse point cloud to obtain a Possion reconstruction point cloud model; fourthly, conducting registration on the obtained Possion reconstruction point cloud model and the obtained initial disperse point cloud through the iterative closet point algorithm; fifthly, calculating the weights of surrounding points to each point on the current registered model, and comparing the weights with a threshold value to determine whether an area where each point is located needs to be scanned repeatedly or not, wherein the surrounding points are placed in the area of the obtained LOP sampling model, a position, corresponding to the point of the current registered model, of the obtained LOP sampling model serves as the circle center of the area, and a certain distance serves as the radius of the area. The invention further relates to the point cloud data quality automatic optimizing system.

Description

technical field [0001] The invention relates to a method and system for automatically optimizing the quality of point cloud data. Background technique [0002] Three-dimensional modeling is a hot problem in the field of computer science. Its modeling methods are mainly divided into two categories according to the source of data: modeling methods based on three-dimensional scattered point data and modeling methods based on images (single frame, multi-frame, sequence). The 3D laser scanning system can quickly obtain the 3D position and geometric texture information of the target object surface, and is widely used in the field of 3D modeling because of the relatively high accuracy of the data obtained. However, most of the existing modeling methods use a specific scanning instrument to scan the target object to obtain the original point cloud data required for modeling, and then use a series of artificially designed precision optimization algorithms in the later offline state ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T17/00G06T7/00G06V10/30
CPCG06T19/00G06T2207/10028G06T2210/56G06V20/653G06V10/30G06T5/70G06V20/64G06F18/2136G06T15/10G06T19/20
Inventor 黄惠陈楠
Owner SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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