Manhattan structure building automatic modeling method based on cuboid fitting scanning three-dimensional point cloud

Abstract

The invention provides a Manhattan structure building automatic modeling method based on cuboid fitting scanning three-dimensional point cloud. The method carried out modeling through plane extraction, cuboid-based space division and binary classification based on a graph-cut algorithm. The method enables modeling work to be converted into the binary classification problem based on a cuboid element structure; the method establishes coverage index for reflecting fitting efficiency and establishes a global optimization target energy equation by utilizing a point set on a plane and space relativeposition relation of each cuboid; the method solves the target equation through the graph-cut algorithm to obtain binary classification of the cuboids, and operation processing efficiency is high; each surface of the model is flat, the overall structure is compact and a comfortable visual effect is achieved; and since the model result only keeps cuboid vertexes and facet structure, compared withinput dense three-dimensional point cloud, data volume is compressed greatly, and model achieves obvious light weight, which has a good support function for modeling work in a large-scale building scene.

Description

technical field [0001] The invention relates to the field of computer automatic modeling, in particular to an automatic modeling method for Manhattan structure buildings based on cuboid fitting and scanning three-dimensional point cloud data. Background technique [0002] The three-dimensional geometric model of the city is one of the important basic data for building a digital city, and it has important application value for urban planning, intelligent traffic navigation, environmental monitoring, and disaster prevention and emergency response. There are many ways to collect spatial data, such as collecting 3D point cloud data through photogrammetry restoration or LiDAR scanning. This type of 3D point cloud data cannot meet specific operational requirements in many subsequent applications, such as parametric representation, computational analysis, rapid prototyping, rendering, and collision detection. Therefore, surface geometric modeling based on 3D point cloud data and g...

AI Technical Summary

Problems solved by technology

The present invention mainly solves some important problems of the prior art in the three-dimensional modeling of digital urbanization: strict requirements on input data; low automation efficiency of modeling processing; complex expression of model results; large amount of model result data, etc.

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