Feature ball based classifying method of three-dimensional point-cloud data of outdoor scene

A three-dimensional point cloud and data technology, applied in image data processing, image analysis, instruments, etc., can solve the problems of imperfect point cloud feature vector structure, complex topology structure, inaccurate point cloud segmentation, etc.

Active Publication Date: 2015-04-08
DALIAN UNIV OF TECH
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Problems solved by technology

This method solves the problem of imperfect point cloud feature vector construction and inaccurate point cloud segmentation (i.e., clique structure) caused by factors such as the complex geometric topology of the outdoor scene, and greatly improves the classification method based on the conditional random field model. classification effect

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  • Feature ball based classifying method of three-dimensional point-cloud data of outdoor scene
  • Feature ball based classifying method of three-dimensional point-cloud data of outdoor scene
  • Feature ball based classifying method of three-dimensional point-cloud data of outdoor scene

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Embodiment Construction

[0038] The present invention will be further described below in conjunction with accompanying drawing.

[0039] Such as figure 1 As shown, a classification method for 3D point cloud data of outdoor scenes based on feature spheres, including the following steps:

[0040] Step 1. Construct a conditional random field model: the conditional random field model is log P ( l | f ) = Σ i = 1 N Σ k = 1 K ( w n k · f i ) l i k + Σ ( ...

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Abstract

The invention relates to a classifying method of three-dimensional point-cloud data, in particular to a feature ball based classifying method of three-dimensional point-cloud data of an outdoor scene. The method includes the steps of 1, constructing a conditional random field model; 2, constructing a three-dimensional point-cloud feature ball; 3, calculating point feature vectors; 4, calculating edge feature vectors; 5, calculating group feature vectors; 6, learning parameters of the conditional random field model; and 7, subjecting the three-dimensional point-cloud data to inference classification. The method has the advantages that feature vectors of all levels of three-dimensional point clouds are accurately and comprehensively calculated through construction of the three-dimensional point-cloud feature ball, the three-dimensional point cloud of the outdoor scene is accurately and reliably segmented, point cloud groups uniform in property are formed, the problem that imperfect structure of the point cloud feature vectors and inaccuracy of point cloud segmentation caused by the factors such as complex geometric topological structure of the outdoor scene are effectively solved, and the effect of classified recognition of the three-dimensional point-cloud data of the outdoor scene is greatly improved.

Description

technical field [0001] The present invention relates to a method for classifying three-dimensional point cloud data, and more specifically, relates to a method for classifying three-dimensional point cloud data of outdoor scenes based on characteristic spheres. Background technique [0002] With the development of 3D scanning ranging technology, 3D point cloud data is widely used in reverse engineering, industrial inspection, autonomous navigation and other fields. 3D point cloud data processing technology has played a vital role as the basis for realizing the above applications. In the 3D point cloud data processing technology, the classification and recognition of 3D point cloud data is a very important technology, especially for the classification and recognition of 3D point cloud data in outdoor scenes, which is very important for the target recognition, environment detection and autonomous navigation of mobile robots. , as well as the autonomous operation of various in...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/62
CPCG06F18/23213G06F18/29
Inventor 安毅宋立鹏李卓函
Owner DALIAN UNIV OF TECH
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