A method for extracting the height of a building main body based on a real scene 3D model

Abstract

The present invention relates to a method for extracting the height of a building main body based on a real - scene three - dimensional model. The specific steps are as follows: Step S1: Read the building contour data, discretize the elevation sampling points according to the building contour, record the plane coordinates and attribute IDs, and form sampling batches according to grids; Step S2: Load the real - scene three - dimensional data based on a three - dimensional platform, read the batch sampling file, perform elevation sampling on the sampling points within this batch from an orthographic view, and write back to the sampling batch file; Step S3: Perform elevation gradient stratification according to the elevation of the sampling points within each building contour, then search for boundaries and filter errors for each gradient, and extract the top height of the building main body according to the elevation, spatial topological relationship, and point density of each gradient; Step S4: Obtain the bottom height of the building in combination with the three - dimensional model of the building entity or DEM; Step S5: Obtain the height of the building main body according to the difference between the top height and the bottom height of the building main body. The present invention has good adaptability and reliability in quickly extracting the height of a building main body over a large range.

Description

Technical Field

[0001] The present invention relates to the technical field of three-dimensional geographic information data mining, and particularly to a method for extracting the height of a building main body based on a real-scene three-dimensional model. Background Art

[0002] The oblique photography real-scene three-dimensional model has characteristics such as rich ground object texture information, high resolution, and efficient and automated modeling production, and is widely used to obtain real-scene geographic information data. The real-scene three-dimensional model result based on oblique photography contains real building height information; in addition, the fine entity three-dimensional model established based on field surveying and mapping and photographing also contains some real space information, and real and rich geographic space information can be mined based on the real-scene three-dimensional model.

[0003] The building height is an important indicator in the regulatory detailed planning and urban design, and has an inescapable external impact on the urban spatial pattern, ecological environment, and historical features. Dense high-rise buildings have a negative external impact on the urban form, skyline, and landscape view of mountains and waters. Super high-rise buildings are also key objects for operation monitoring; in addition, the building height is an important basis for evaluating the building volume and floor area ratio. Therefore, the monitoring and control of the building height have important practical significance.

[0004] In the control of the building style, generally the height of the building main body is used as the standard, and accessory facilities such as parapets, water tanks, billboards, and decorative components need to be excluded. The extraction of the building main body height first needs to ensure the authenticity and reliability of the data source, and the influence of accessory facilities also needs to be excluded. In addition, for the convenience of regularly extracting and monitoring the building main body height, there are also requirements for the extraction efficiency and adaptability. Summary of the Invention

[0005] The purpose of the present invention is to solve the deficiencies in the prior art, and a method for extracting the height of a building main body based on a real-scene three-dimensional model is proposed, which can automatically batch extract the height according to the building contour and the real-scene three-dimensional model. The process includes generating discrete sampling points based on the building contour, organizing the sampling point grid, elevation sampling, stratifying the building elevation gradient, searching for the discrete point boundary, extracting the main body elevation gradient, obtaining the building bottom height, and calculating the building main body height.

[0006] In order to achieve the above purpose, the present invention adopts the following technical solutions:

[0007] Design a method for extracting the height of a building main body based on a real-scene three-dimensional model, and the specific steps are as follows:

[0008] Step S1, read the building contour data, discretize the elevation sampling points according to the building contour, record the plane coordinates and the attribute ID, and form a sampling batch according to the grid;

[0009] Step S2: Load the real - scene 3D data based on the 3D platform, read the batch sampling file, perform elevation sampling on the sampling points within this batch in the orthographic view, and write it back to the sampling batch file;

[0010] Step S3: Perform elevation - gradient stratification according to the elevation of the sampling points within each building contour, then search for boundaries and filter errors for each gradient, and extract the top height of the building main body based on the elevation, spatial topological relationship, and point density of each gradient;

[0011] Step S4: Obtain the bottom height of the building by combining the 3D model of the building entity or DEM;

[0012] Step S5: Obtain the height of the building main body according to the difference between the top height and the bottom height of the building main body.

[0013] Preferably, the specific steps of Step S1 are as follows:

[0014] Step S11: Read the building contour data, generate a rectangular bounding box according to the building contour, generate a sampling point set at a resolution of 2m, and then obtain the discretized elevation sampling points within the contour range through spatial intersection of the building contour;

[0015] Step S12: Divide the entire sampling area into 600m * 600m sampling grids. The building contour ID and the coordinate sequence of the batch sampling points are recorded in the grid sampling file. One grid is a sampling batch. Determine the grid where each sampling point is located according to the coordinates and write it to the corresponding sampling batch file.

[0016] Preferably, the specific steps of Step S3 are as follows:

[0017] Step S31: Traverse the batch file after sampling, and group the sampling points of the same building contour according to the contour ID;

[0018] Step S32: For the sampling points of a single building contour, stratify them according to the elevation gradient, remove the elevation gradients with less than 9 sampling points, and use 2√2m as the constraint for the sampling points of each gradient to search for the discrete point boundary along the grid edge;

[0019] Step S33: According to the spatial topological inclusion relationship, elevation relationship, and sampling point density constraint of each boundary, exclude the elevation gradients of parapets, water tanks, and external decorations, and use the elevation gradient with the largest area as the elevation gradient of the building main body;

[0020] Step S34: Perform mean - square error analysis on the gradient sampling points of the building main body, filter the discrete sampling points exceeding 2 times the mean - square error, and use the average value of the remaining points within this gradient as the top height of the building main body.

[0021] Preferably, the specific steps of Step S4 are as follows:

[0022] Step S41: If there is a three-dimensional building entity model based on field completion data, first perform an orthographic projection on the triangular faces of the building entity model, then perform topological fusion to obtain the two-dimensional contour of the building bottom surface, and use the lowest point of the model as the bottom height. By performing a spatial topological intersection with the discrete sampling points in S1, assign the bottom height to each sampling point, and use the lowest sampling point within the sampling contour as the bottom height of the building sampling;

[0023] Step S42: If there is no building entity model, perform elevation sampling on the discrete sampling points in S1 based on the DEM, and use the elevation of the lowest sampling point within the building contour as the bottom height of the building sampling.

[0024] Preferably, steps S3 to S5 complete the extraction of the height of a building main body. Traverse the sampling points of the building contour in sequence, and then loop through the steps of S3 to S5 until the height extraction of all building bottoms is completed.

[0025] A method for extracting the height of a building main body based on a real-scene three-dimensional model proposed by the present invention has the beneficial effects that: this method for extracting the height of a building main body based on a real-scene three-dimensional model is based on the bottom surface of the building contour, makes full use of the strong authenticity of the real-scene three-dimensional data, performs elevation sampling in the oblique photography real-scene three-dimensional scene, and after post-processing, it can reflect the elevation of the main body of the building roof excluding ancillary facilities such as parapets, water tanks, and decorative components. Then, by combining the building entity model or the DEM to obtain the bottom elevation of the building to get the height of the building main body, it has high accuracy and efficiency as a whole, and has good adaptability and reliability in quickly extracting the height of the building main body in a large area. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flowchart of a method for extracting the height of a building main body based on a real-scene three-dimensional model of the present invention.

[0027] Figure 2 It is a schematic diagram of a method for extracting the height of a building main body based on a real-scene three-dimensional model of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0028] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments.

[0029] Refer to Figure 1-2 , a method for extracting the height of a building main body based on a real-scene three-dimensional model, the specific steps are as follows:

[0030] Step S1: Read the building contour data, discretize the elevation sampling points according to the building contour, record the plane coordinates and attribute IDs, and form sampling batches according to the grid;

[0031] Step S2: Load the real - scene 3D data based on the 3D platform, read the batch sampling file, perform elevation sampling on the sampling points within this batch from the orthographic view, and write back to the sampling batch file;

[0032] Step S3: Perform elevation - gradient stratification according to the elevation of the sampling points within each building contour, then search for boundaries and filter errors for each gradient, and extract the top height h of the building main body based on the elevation, spatial topological relationship, and point density of each gradient 顶 ;

[0033] Step S4: Combine the 3D model of the building entity or DEM to obtain the bottom height h of the building 底 ;

[0034] Step S5: According to the difference between the top height and the bottom height of the building main body h = h 顶 -h 底 Obtain the height of the building main body.

[0035] The specific steps of Step S1 are as follows:

[0036] Step S11: Read the building contour data, generate a rectangular bounding box according to the building contour, generate a sampling point set at a resolution of 2m, and then obtain the discretized elevation sampling points within the contour range through spatial intersection of the building contour;

[0037] Step S12: Divide the entire sampling area into 600m * 600m sampling grids. The building contour ID and the coordinate sequence of the batch sampling points are recorded in the grid sampling file. One grid is a sampling batch. Calculate the row and column numbers of the grid where each sampling point is located according to the coordinates by the following formula and write them to the corresponding sampling batch file. The algorithm formula is as follows:

[0038]

[0039] where (x, y) are the coordinates of the sampling point, (x0, y0) are the starting points of the grid, and (row, col) are the row and column numbers of the grid.

[0040] The specific steps of Step S3 are as follows:

[0041] Step S31: Traverse the sampled batch file and group the sampling points of the same building contour according to the contour ID;

[0042] Step S32: For a single building contour sampling point, first search for stratification by moving a 3.5m window from low to high elevation of the sampling points. Then calculate the mean square error for each layer of points as follows. Select the average elevation of the sampling points within twice the mean square error as the new intermediate value. If the difference between the intermediate values of two layers is less than 2m, merge them. Re-stratify the elevation points according to a threshold of 1.5m from the intermediate value. If the mean square error of all strata is less than 2m, terminate. Otherwise, split the layer with a mean square error greater than 2m into two layers and continue to cycle through the 1.5m threshold for stratification. Finally, remove the elevation gradients with fewer than 9 sampling points. The algorithm formula is as follows:

[0043]

[0044] where h i is the i-th sampling point, n represents the number of sampling points, represents the average value;

[0045] Step S33: Search for the discrete point boundary along the grid edge for each gradient. First, filter out the points surrounded in all eight directions. Then select the point with the smallest y value among the points with the smallest x value as the starting point. Select the point with the largest counterclockwise angle with the X axis within a range of 2√2m as the next point. Use these two points as the starting edge and the new point as the corner point. Select the point with the largest counterclockwise angle with the starting edge within a range of 2√2m as the next point and cycle until returning to the starting point to close. The algorithm formula is as follows:

[0046]

[0047] where PT represents the set of sampling points within the original stratified gradient, and n represents the number of sampling points;

[0048] Step S34: According to the spatial topological inclusion relationship, elevation relationship, and sampling point density constraint of each boundary, the density calculation formula is as follows. Exclude the height gradients of parapets, water tanks, external decorations, etc. Take the elevation gradient with the largest area as the elevation gradient of the building main body. The algorithm formula is as follows:

[0049]

[0050] where S represents the area of the gradient boundary, and n represents the number of sampling points within the gradient;

[0051] Step S35: Conduct a mean square error analysis on the gradient sampling points of the building main body. Filter out the discrete sampling points exceeding twice the mean square error. Take the average value of the remaining points within this gradient as the top height h 顶 ;

[0052] The specific steps of Step S4 are as follows:

[0053] Step S41: If there is a three-dimensional building entity modeled based on field completion data, first perform an orthographic projection on the triangular faces of the building entity model, then conduct topological fusion to obtain the two-dimensional contour of the building base, and use the lowest point of the model as the base height. By performing a spatial topological intersection with the discrete sampling points in S1, assign the base height to each sampling point, and use the lowest sampling point within the sampling contour as the base height h of the building sampling. 底 ;

[0054] Step S42: If there is no building entity model, perform elevation sampling on the discrete sampling points in S1 based on the DEM, and use the elevation of the lowest sampling point within the building contour as the base height h of the building sampling. 底 , and the algorithm formula is as follows:

[0055] h 底 = min(h s1 , h s2 , h s3 , …, h s(n-1) , h sn )

[0056] where h si represents the elevation sampled by the i-th sampling point on the DEM;

[0057] Steps S3 to S5 complete the extraction of the height of a building main body. Traverse the sampling points of the building contour in sequence, and then loop through the steps of S3 to S5 until the height extraction of all building bases is completed.

[0058] The beneficial effects of the present invention are as follows: Based on the building contour base, it makes full use of the strong authenticity of real-scene three-dimensional data, performs elevation sampling in the oblique photography real-scene three-dimensional scene, and after post-processing, it can reflect the elevation of the main body of the building roof excluding accessory facilities such as parapets, water tanks, and decorative components. Then, by combining the building entity model or DEM to obtain the building bottom elevation, the height of the building main body is obtained, and overall, it has high accuracy and efficiency;

[0059] The present invention aims at the demand for obtaining the height of the building main body in building style control. According to the existing building contour base, discrete sampling points are organized into grids according to their spatial positions, elevation sampling is performed in the real-scene three-dimensional scene, and then post-processing such as elevation layering, boundary search, spatial analysis, and error filtering is carried out. Finally, the elevation of the top of the building main body is obtained, and by combining the building base height data, the height of the building main body is obtained, which has good adaptability and reliability in quickly extracting the height of the building main body in a large range.

[0060] The above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, makes equivalent substitutions or changes, and all should be covered within the protection scope of the present invention.

Claims

1. A method for extracting the height of a building main body based on a real - scene three - dimensional model, characterized in that, The specific steps are as follows: Step S1: Read the building contour data, discretize the elevation sampling points according to the building contour, record the plane coordinates and attribute IDs, and form sampling batches by grid; Step S2: Load the real scene 3D data based on the 3D platform, read the batch sampling file, perform elevation sampling on the sampling points within this batch from the orthographic view, and write back to the sampling batch file; Step S3: Perform elevation gradient stratification according to the elevation of the sampling points within each building contour, then search for boundaries and filter errors for each gradient, and extract the top height of the building main body according to the elevation, spatial topological relationship, and point density of each gradient. The specific steps are as follows: Step S31: Traverse the sampled batch file and group the sampling points of the same building contour according to the contour ID; Step S32: For the sampling points of a single building contour, stratify them according to the elevation gradient, remove the elevation gradients with less than 9 sampling points, and use 2√2m as the constraint for the sampling points of each gradient to search for the discrete point boundary along the grid edge; Step S33: According to the spatial topological inclusion relationship, elevation relationship, and sampling point density constraint of each boundary, exclude the elevation gradients of parapets, water tanks, and external decorations, and use the elevation gradient with the largest area as the elevation gradient of the building main body; Step S34: Perform mean square error analysis on the gradient sampling points of the building main body, filter out the discrete sampling points exceeding 2 times the mean square error, and use the average value of the remaining points within this gradient as the top height of the building main body; Step S4: Combine the building entity 3D model or DEM to obtain the building bottom height; Step S5: Obtain the building main body height according to the difference between the top height and the bottom height of the building main body.

2. The method for extracting the height of a building main body based on a real-scene three-dimensional model according to claim 1, wherein The specific steps of Step S1 are as follows: Step S11: Read the building contour data, generate a rectangular bounding box according to the building contour, generate a sampling point set at a resolution of 2m, and then obtain the discretized elevation sampling points within the contour range through spatial intersection of the building contour; Step S12: Divide the entire sampling area into 600m * 600m sampling grids. Record the building contour ID and the batch sampling point coordinate sequence in the grid sampling file. One grid is a sampling batch. Determine the grid where each sampling point is located according to the coordinates and write it to the corresponding sampling batch file.

3. The method for extracting the height of a building main body based on a real - scene three - dimensional model according to claim 2, wherein, The specific steps of Step S4 are as follows: Step S41: When there is a building entity 3D model built based on the field completion data, first perform orthographic projection on the triangular faces of the building entity model, then perform topological fusion to obtain the two-dimensional contour of the building bottom surface, and use the lowest point of the model as the bottom height. Through spatial topological intersection with the discrete sampling points in S1, assign the bottom height to each sampling point, and use the lowest sampling point within the sampling contour as the bottom height of the building sampling; Step S42: If there is no building entity model, perform elevation sampling on the discrete sampling points in S1 based on the DEM, and use the elevation of the lowest sampling point within the building contour as the building sampling bottom height.

4. The method for extracting the height of a building main body based on a real scene 3D model according to claim 3, wherein Steps S3 to S5 complete the extraction of the height of a building main body. Traverse the building contour sampling points in sequence, and then loop through the steps of S3 to S5 until the height extraction of all building bottom surfaces is completed.

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