Browser based mass three-dimensional point cloud data release method

Abstract

The present invention provides a browser based mass three-dimensional point cloud data release method. The method comprises the following steps that S1. a bounding box of original three-dimensional point cloud data is calculated, and block division is carried out on the original three-dimensional point cloud data according to the bounding box and a regular grid division theory, so as to divide a plurality of block point cloud bounding boxes; S2. an octree is established for each block point cloud bounding box, and a description file is configured for each octree; S3. regular grid division is carried out on a point cloud octree, and a quadtree structure is established for the octree contained in each regular grid; and S4. a browser sends in real time a query request to a server, the server returns in real time an octree query result to the browser, the browser carries out visibility determination on the octree query result, and the visible octree is loaded, so as to complete dynamic loading and scheduling of mass three-dimensional point cloud data. According to the method disclosed by the present invention, web based release and visualization of mass large point cloud files are realized, and the problem that point cloud data is difficult to release is solved.

Description

technical field [0001] The invention relates to the field of three-dimensional point cloud data network publishing, in particular to a method for publishing massive three-dimensional point cloud data based on a browser. Background technique [0002] With the construction of digital cities and the continuous development of large-scale 3D data acquisition technology, 3D laser scanning technology has been widely used. It can collect the complete 3D coordinates of the target scene, perform automatic high-precision scanning in the 3D space, truly describe the overall structure and morphological characteristics of the target scene, and quickly obtain the point cloud data of the target scene. However, due to the multi-view integration of scanning devices, the complexity of the target scene, and the increasing fineness of the scene to be drawn, the scale of point cloud data is increasing day by day. In the face of massive city-level 3D point cloud data, how to effectively publish i...

AI Technical Summary

Problems solved by technology

[0005] ① In terms of data organization and spatial indexing of 3D point clouds, a single indexing method is mainly used, and there is a lack of research on hybrid indexes. At the same time, there is a lack of research on massive 3D point cloud data organization schemes;

[0006] ② Research on the dynamic loading and sche

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