Rapid building three-dimensional reconstruction method based on two-dimensional vector diagram and small number of elevation points

Abstract

The invention discloses a quick building three-dimensional reconstruction method based on a two-dimensional vector diagram and a small number of elevation points, and the method comprises the steps: S100, extracting two-dimensional vector polygon data and the elevation points, wherein the elevation points comprise a ground point, an eave point and a ridge point; s200, judging the topological relation between the two-dimensional vector polygons and the corresponding relation between the two-dimensional vector polygons and the elevation points; s300, judging the main direction of the two-dimensional vector polygon and adjusting the boundary; s400, designing a building rule and judging a category of model elements; and S500, generating ridge lines and the top surfaces, the bottom surfaces andthe wall surfaces of the model elements. The two-dimensional vector data sources are diversified, and existing surveying and mapping field work, planning data, DOM data, DSM data, three-dimensional point cloud or grid data can be fully utilized; the difficulty and the efficiency of interactive editing are greatly improved, editing from two dimensions is simpler and more efficient than editing from three dimensions, and only a small number of elevation points need to be matched; the model is highly regularized and automatically regularized, and the generated model meets various constraints such as parallelism, verticality and the like.

Description

technical field [0001] The invention belongs to the technical field of photogrammetry, remote sensing, and three-dimensional reconstruction of buildings, and in particular relates to a fast three-dimensional reconstruction method of buildings based on two-dimensional vector graphics and a small number of elevation points. Background technique [0002] The current fully automatic 3D reconstruction methods for buildings are still difficult to meet the production needs. The semi-automatic reconstruction method is mainly based on LiDAR or multi-view image dense matching to obtain 3D point cloud or grid, and then edit and vectorize in 3D in software (such as sketchup or 3Dmax), and finally obtain a single model. The main problems are: 1. The cost of obtaining 3D point cloud or grid data is high; 2. Editing in 3D is much more difficult than 2D, and the efficiency is low; 3. Failure to reuse existing data, such as Two-dimensional planning data, DSM or DOM data. Contents of the i...

AI Technical Summary

Problems solved by technology

[0003] In order to solve the problems of limited efficiency and difficult operation of 3D editing commonly used in the existing 3D model reconstruction process

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