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Method for automatically partitioning tree point cloud data

A point cloud data, automatic segmentation technology, applied in measurement devices, instruments, optical devices, etc., can solve problems such as insurmountable segmentation

Inactive Publication Date: 2012-03-21
INST OF AUTOMATION CHINESE ACAD OF SCI
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  • Abstract
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Problems solved by technology

[0008] The present invention intends to solve the technical problem that over-segmentation cannot be overcome during the segmentation process. The purpose of the present invention is to provide a laser scanning point cloud model that is accurate in line with the actual tree organ distribution for the tree point cloud data obtained by laser scanning in the real world. segmentation method

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  • Method for automatically partitioning tree point cloud data
  • Method for automatically partitioning tree point cloud data
  • Method for automatically partitioning tree point cloud data

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Embodiment Construction

[0045] 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.

[0046] 1. Overview of approach

[0047] Such as figure 1 Show the flow process of the whole method of the present invention, wherein the main steps of the algorithm of the present invention include:

[0048] 1) Calculation of local geometric quantities, including 6 sub-steps: (a) acquisition and preprocessing of point cloud, (b) normal direction estimation of point cloud, (c) construction of local coordinate system, (d) fitting using nearest neighbor points Quadric surface, (e) calculate principal curvature using quadric surface, (f) calculate axial distribution density.

[0049] 2) Segment the tree point cloud model, including 3 sub-steps: (g) u...

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Abstract

The invention relates to a method for automatically partitioning tree point cloud data. The method comprises the following steps: acquiring and preprocessing point cloud, estimating the direction by a point cloud process, constructing a local coordinate system, fitting a conicoid by using a closest point process, calculating the principal curvature by using the conicoid, defining and calculating the axial distribution density, distinguishing the branch point cloud and the leaf point cloud by using the axial distribution density, carrying out region growing on the branch point cloud, and carrying out region merging on the branch point cloud. By using the tree scanning data of a laser scanner and the estimated principal curvature, the invention partitions the tree scanning point cloud according with the actual organ distribution conditions. The method automatically partitions the tree point cloud scanning data among different organs through the local direction of principal curvature, and has the advantages of simple algorithm and accurate calculation result. The calculation result has important application value in the fields of tree point cloud 3D reconstruction, forest measurement, tree point cloud registration and the like.

Description

technical field [0001] The invention belongs to the technical fields of differential geometry, computational mathematics, computer graphics and computer vision, and relates to a method of using a three-dimensional laser scanner to measure trees to obtain tree point cloud data, and according to the point cloud data to perform automatic calculation of point clouds belonging to different organs. method of segmentation. It has important application value in the fields of virtual reality, computer games, data compression, feature extraction, forestry measurement, and plant 3D reconstruction. Background technique [0002] The point cloud model is an unorganized point cloud collection (Unorganized Points). In applications such as geometric compression and transmission, interactive editing, texture mapping, and parameterization, it is necessary to divide point cloud data into regions with single features and non-overlapping features, which requires the use of point cloud segmentati...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01B11/24
Inventor 张晓鹏代明睿李红军
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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