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Unsupervised fusion point cloud super voxelization method based on light spot divergence size

A super-voxel and fusion point technology, applied in 3D object recognition, character and pattern recognition, image data processing, etc., can solve the problems of forestry special equipment operation interruption, efficiency reduction, threat to driver safety, etc.

Pending Publication Date: 2020-08-04
BEIJING TECHNOLOGY AND BUSINESS UNIVERSITY
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Problems solved by technology

However, due to the complexity of the forestry environment and uncontrollable factors, the automation of forestry special equipment still faces great difficulties: during the driving and operation of plantation forests, the interruption of forestry special equipment operations due to the complexity of the forest environment and the difficulty in identifying targets. Problems such as reducing or even threatening driver safety occur frequently

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  • Unsupervised fusion point cloud super voxelization method based on light spot divergence size
  • Unsupervised fusion point cloud super voxelization method based on light spot divergence size
  • Unsupervised fusion point cloud super voxelization method based on light spot divergence size

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Embodiment Construction

[0103] Preferred embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although preferred embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0104] as attached figure 1 As shown, the flow chart of the unsupervised fusion point cloud supervoxelization method based on the spot divergence size of the exemplary embodiment includes the following steps:

[0105] Step 1: Divide the woodland environment fusion point cloud data acquired by 3D laser scanner, visible light camera and thermal infrared camera into super-voxel preset areas. The specific implementation steps are:

[0106]1....

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Abstract

The invention discloses an unsupervised fusion point cloud super voxelization method based on a light spot divergence size. The method comprises the steps: dividing forest land environment fusion point cloud into super voxel preset areas; completing voxelization processing of the fusion point cloud according to the laser spot divergence degree and the effective energy section area, and determiningthe real size of each voxel; determining an initial seed point, and removing discrete noise; extracting the color, temperature, spatial distribution and light spot size of each voxel, and constructing a super voxel feature vector; performing distance standard normalization processing on each component of the super voxel feature vector, and calculating the local density and the high-density distance difference value of each super voxel by applying density peak clustering; constructing a comprehensive evaluation function, and determining a division center point of the super voxel through ascending value sorting and threshold parameter screening; and carrying out neighborhood search on voxels around each center point to obtain a super voxel index, and completing unsupervised super voxel automatic division. The method can effectively improve the accuracy and robustness of forestry environment fusion point cloud super voxelization.

Description

technical field [0001] The invention relates to the field of digital signal processing, in particular to a super-voxelization processing method for unsupervised fusion point cloud data based on spot divergence size. Background technique [0002] In the development of modern forestry, the application of data fusion technology is very extensive. The application of multi-source information acquisition systems and processing systems including 3D laser scanners, high depth-of-field cameras and inertial sensors in forestry has promoted the development of forestry. Intelligent trend. However, due to the complexity of the forestry environment and uncontrollable factors, the automation of forestry special equipment still faces great difficulties: during the driving and operation of plantation forests, the interruption of forestry special equipment operations due to the complexity of the forest environment and the difficulty in identifying targets. Problems such as reducing or even t...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06T7/10
CPCG06T7/10G06T2207/10028G06V20/64G06F18/23
Inventor 孔建磊金学波王小艺王珍妮苏婷立
Owner BEIJING TECHNOLOGY AND BUSINESS UNIVERSITY
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