Indexing method and device for large-scale point cloud data, terminal equipment and medium

A technology of point cloud data and cloud data, which is applied in still image data indexing, still image data retrieval, special data processing applications, etc., can solve the problems of high computer memory requirements and low indexing efficiency, reduce processing pressure, and improve indexing efficiency effect

CN110457499AInactive Publication Date: 2019-11-15GUANGZHOU QILIANG INFORMATION TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2019-11-15
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention discloses an indexing method and device for large-scale point cloud data, terminal equipment and a medium. The indexing method comprises the following steps: reading point cloud data from a local hard disk, wherein the point cloud data is that a spatial feature data structure of a target file is stored in a local hard disk by taking a file name form as an entry of an index; calculating a minimum bounding box vertex of the point cloud data to obtain X-axis, Y-axis and Z-axis coordinates of the maximum bounding box and the minimum bounding box; constructing a file index table according to the coordinates; and directionally extracting target point cloud data from the file index table, the target point cloud data being that the processing pressure of a computer memory can be reduced, and the indexing efficiency of large-scale point cloud data is improved.
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Description

technical field

[0001] The invention relates to the technical field of computer data structures, in particular to an indexing method, device, terminal equipment and media for large-scale point cloud data. Background technique

[0002] Point cloud data has the characteristics of large data volume (massiveness), fine data expression (high spatial resolution), and no topological relationship (scatteredness) between spatial three-dimensional points. In subsequent data processing, frequent neighborhood searches are required. , so the octree structure or K-D tree data structure is often used for data organization to realize the indexing of point cloud data.

[0003] The octree data structure is in the form of continuously cutting the point cloud data into 8 sub-cubes according to the cube. When the computer memory is large enough, the super-large point cloud data can be indexed by using the octree data structure. However, each index needs to re-read the point cloud data into the...

Examples

no. 3 example

[0073] The third embodiment provides an indexing terminal device for large-scale point cloud data, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the memory and the The processor is coupled, and when the processor executes the computer program, the above-mentioned method for indexing large-scale point cloud data is realized, and has the same beneficial effect as the above-mentioned method.

no. 4 example

[0075] The fourth embodiment provides a computer-readable storage medium, the computer-readable storage medium includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the above-mentioned An indexing method for large point cloud data, and has the same beneficial effects as the above method.

[0076] To sum up, implementing the embodiment of the present invention can index large-scale point cloud data on the local hard disk, effectively reduce the processing pressure of computer memory, and improve the indexing efficiency of large-scale point cloud data.