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Point cloud dynamic hash division method and device

A point cloud and dynamic technology, applied in the point cloud field, can solve the problems of low efficiency of hash table insertion and query, high frequency of hash conflicts, etc., and achieve the effect of optimizing access performance and improving efficiency

Pending Publication Date: 2021-12-28
PENG CHENG LAB
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AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide a point cloud dynamic hash division method and device for the above-mentioned defects of the prior art, aiming to solve the problem of hash table insertion and query caused by the high frequency of hash collisions in the prior art The problem of inefficiency

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  • Point cloud dynamic hash division method and device
  • Point cloud dynamic hash division method and device
  • Point cloud dynamic hash division method and device

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Embodiment Construction

[0058] In order to make the object, technical solution and advantages of the present invention more clear and definite, the present invention will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0059] Please also see Figure 1-Figure 3 , the present invention provides some embodiments of a point cloud dynamic hash division method.

[0060]The inventors found that in the test platform PCEM, the geometric information in the 3D point cloud is quantized, converted into Morton codes, and organized into an octree according to the Morton codes. Before encoding a certain layer of the octree, create a new hash table, and put all the nodes in this layer into the hash table. During the encoding process, when establishing a context reference, the node occupancy of a certain position can ...

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Abstract

The invention discloses a point cloud dynamic Hash division method and equipment, and the method comprises the steps: determining the total number of division times according to the total number of occupied nodes of a current node layer of a tree structure and an average node number threshold value in a single Hash table after division; determining the number of hash tables corresponding to the current node layer; determining the division times of each coordinate component; and determining a hash table corresponding to the node according to the number of hash tables corresponding to the current node layer, the division times of the coordinate component and the occupied node position data of the current node layer, and adding the node into the hash table corresponding to the node. A plurality of hash tables is configured on each node layer, the serial numbers of the hash tables corresponding to the nodes are determined according to the position data of the occupied nodes of the current node layer, the nodes are added to the hash tables corresponding to the nodes, and the nodes in the different hash tables do not have hash conflicts, so that when that the performance is not lost, the access performance of the hash tables is optimized, and the insertion and query efficiency of the hash tables is improved.

Description

technical field [0001] The present invention relates to the field of point cloud technology, in particular to a point cloud dynamic hash division method and equipment. Background technique [0002] 3D point cloud is an important form of digitalization of the real world. With the rapid development of 3D scanning equipment (such as laser, radar, etc.), the accuracy and resolution of point clouds have become higher. High-precision point clouds are widely used in the construction of urban digital maps, and play a technical supporting role in many popular researches such as smart cities, unmanned driving, and cultural relics protection. The point cloud is obtained by sampling the surface of an object by a 3D scanning device. The number of points in a frame of point cloud is generally in the millions, and each point contains geometric information, color, reflectivity and other attribute information, and the amount of data is very large. The huge data volume of 3D point cloud bri...

Claims

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Application Information

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IPC IPC(8): G06F16/22
CPCG06F16/22G06F16/2255
Inventor 赵文博王静宋菲李革高文
Owner PENG CHENG LAB
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