Reconstruction method of large-scale point cloud complex space surface based on distributed parallelism
A large-scale, distributed technology, applied in 3D modeling, image data processing, instruments, etc., can solve problems such as input data limitations, multiple interaction definitions, and long running time of point cloud data processing, so as to reduce construction time and improve efficiency effect
Active Publication Date: 2017-07-14
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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However, in the existing point cloud processing system, there are often deficiencies such as many interactive definitions and strict restrictions on input data. At the same time, the processing of large-scale point cloud data also has too long running time, and the scale of point cloud data has certain limitations, etc. question
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[0024] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.
[0025] Such as figure 1 As shown in FIG. 2 , it is a schematic flowchart of the large-scale point cloud complex space surface reconstruction method based on distributed parallelism in the present invention. Through the coordination and cooperation of the main control PC and the node PC, not only the memory required for large-scale point cloud data construction is met, but also the reconstruction efficiency of complex spatial surfaces is greatly improved. A large-scale point cloud complex spatial surface reconstruction method based on distributed parallelism, comprising the following steps:
[002...
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The invention discloses a large-scale point cloud complex space surface reconstruction method based on distributed parallelism. It includes the following steps: the main control PC reads in the initial details, divides the sub-blocks, puts the point cloud data into the sub-blocks, distributes the sub-blocks to the node PCs for preprocessing, grids the sub-blocks, and puts the point cloud data into the grid , Construct planar triangulation, construct planar constraint triangulation, construct spatial triangulation and smooth within block, global smooth and master PC to display reconstructed surface. The beneficial effect of the present invention is: the present invention adopts parallel scheme to provide enough memory space for large-scale point cloud data reconstruction curved surface, has reduced the memory space occupied by data and the construction time of plane Delauany triangulation in the curved surface construction process, has greatly improved The efficiency of surface construction.
Description
technical field [0001] The invention belongs to the technical field of spatial curved surface reconstruction methods, and in particular relates to a large-scale point cloud complex spatial curved surface reconstruction method based on distributed parallelism. Background technique [0002] Surface reconstruction of spatial points is an integral part of 3D geological modeling. It uses computer technology to reconstruct surfaces. Its essence is to use discrete points in 3D space to connect them into a surface in a certain order. Point-based point cloud processing technology is a subject that has developed rapidly with the development of data measurement technology. This technology uses points as the basis for reconstructing objects, improving the speed of object drawing and reconstruction, and strengthening large-scale data processing capabilities. It has huge advantages in terms of computer processing capacity and so on. It is a hot spot in reverse engineering research. At pre...
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IPC IPC(8): G06T17/30
Inventor 姚兴苗税凡胡光岷
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA