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A voxelization method for point cloud data and a voxel occlusion clipping method

A point cloud data and voxelization technology, which is applied in image data processing, instruments, calculations, etc., can solve problems such as difficult network construction, difficult scene update, sensitive scene complexity, etc., and achieve the effect of reducing display difficulty

Active Publication Date: 2019-02-19
THE PLA INFORMATION ENG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] The organization of traditional point cloud data adopts the method based on building a triangulation network, which is an object-oriented organization method. The disadvantage of this method is that it is sensitive to the complexity of the scene. The more complex the scene, the more difficult it is to construct the network, and It is difficult to update the scene. Once the scene changes, it needs to be reorganized

Method used

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  • A voxelization method for point cloud data and a voxel occlusion clipping method
  • A voxelization method for point cloud data and a voxel occlusion clipping method
  • A voxelization method for point cloud data and a voxel occlusion clipping method

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Embodiment 1

[0031] combine figure 2 , Embodiment 1 of the present invention provides a voxelization method for point cloud data, including:

[0032] Step S101: According to the minimum and maximum values ​​of all point cloud data in the three coordinate directions of X, Y, and Z, determine the distribution range of point cloud data, that is, the smallest cuboid containing all point cloud data;

[0033] The minimum and maximum values ​​of all point cloud data in the three coordinate directions of X, Y, and Z can be determined by comparison method, that is, x min and x max ,y min and y max ,z min and z max , where x min 、x max Respectively, the minimum and maximum values ​​of all point cloud data in the X coordinate direction, y min 、y max are the minimum and maximum values ​​of all point cloud data in the Y coordinate direction, z min ,z max are the minimum and maximum values ​​of all point cloud data in the Z coordinate direction, respectively.

[0034] The size of the smalle...

Embodiment 2

[0044] combine image 3 , Figure 4 with Figure 5 , Embodiment 2 of the present invention provides a voxel occlusion and clipping method based on the voxelization method described in Embodiment 1, including:

[0045] Step S201: According to the distribution range of the point cloud data (that is, according to the minimum value x of all point cloud data in the three coordinate directions of X, Y, and Z min 、y min ,z min and the maximum value x max 、y max ,z max The obtained smallest cuboid containing point cloud data), calculate (x min ,y min ,z min ) and (x max ,y max ,z max ) coordinates corresponding to the two points in the screen coordinate system, and determine the distribution range of the pixel coordinates, thereby reducing the number of rays made from the viewpoint to the pixel points within the pixel coordinate distribution range, and reducing the calculation amount of geometry intersection of rays and voxel surfaces.

[0046] Step S202: Select a pixel p...

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Abstract

The invention discloses a voxelization method of point cloud data. The voxelization method comprises steps of: determining a minimum cuboid including all point cloud data according to the minimum value and the maximum value of all point cloud data in X, Y, and Z coordinate directions; setting the size of a voxel according to the size of the minimum cuboid and a resolution requirement and dividing the minimum cuboid into a plurality of voxels according to the size of the voxel; determining the voxel where each point in the point cloud data is located, and just displaying the voxels including the point cloud data after traversing all points of the point cloud data. The invention further discloses a voxel shielding cutting method. The voxelization method is insensitive to scenarios, capable of monitoring dynamic targets, and fast in intersection speed.

Description

technical field [0001] The present application relates to the field of point cloud data processing and virtual reality technology, in particular to a voxelization method of point cloud data and a voxel occlusion clipping method. Background technique [0002] At this stage, the organization and application of point cloud data is usually realized by building a triangulation network. There are many ways to construct a triangulation network, and the region growing method is used as an example to illustrate. The region growing method is mainly divided into two steps, one is the construction of the seed triangle, such as figure 1 The second is to grow according to the regional growth strategy. The region growing strategy is mainly to search the edges of the unfinished network to specify the candidate points within the range and determine the best candidate triangle. [0003] After organizing all the point cloud data in the scene (all 3D objects in 3D space form a scene) accordi...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T17/30
CPCG06T17/30
Inventor 赖广陵童晓冲秦志远丁璐汪滢韩硕范帅博
Owner THE PLA INFORMATION ENG UNIV
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