A method for architectural surveying based on aerial photography

Abstract

This invention relates to the field of architectural surveying technology and discloses an architectural surveying method based on aerial photography. The system includes: generating an initial building outline based on a building image dataset; determining the initial shooting interval of a camera based on basic dimension data; acquiring aerial image data of the building to be surveyed; performing 3D reconstruction of the initial building outline based on the aerial image data to generate an initial 3D point cloud model of the building; determining whether to adjust the initial shooting interval based on local density; when it is determined that the initial shooting interval should be adjusted, collecting coverage data of the building to be surveyed, calculating a shooting influence factor based on the coverage data and local density; comparing the shooting influence factor with historical data, adjusting the initial shooting interval based on the comparison results; and storing the shooting influence factor. This invention not only improves the efficiency of architectural surveying but also enhances the quality of surveying results, providing strong technical support for urban planning and construction.

Description

Technical Field

[0001] This invention relates to the field of architectural surveying technology, and more specifically, to an architectural surveying method based on aerial photography. Background Technology

[0002] Architectural surveying involves conducting on-site investigations and measurements of actual buildings. Using the principles of architectural plan, elevation, and section drawing, the actual measured object and its data are analyzed and organized, then expressed in plan, elevation, and section drawings. Through on-site investigation and surveying of actual buildings, theoretical knowledge is verified, consolidated, and enhanced, deepening the understanding of architectural plans, elevations, sections, space, and structure, and providing a preliminary understanding of the relationship between the building's interior space and its surrounding environment.

[0003] Building surveying plays a crucial role in urban planning and construction. It is the cornerstone for ensuring rational urban layout, building safety, and functional completeness. However, traditional building surveying methods often rely on significant human and time investment, which not only increases project costs but can also lead to inefficiency. Especially in areas with complex terrain or dense buildings, traditional surveying methods often prove inadequate and struggle to meet various challenges. Surveying work in these areas is not only time-consuming but also prone to errors, affecting the final planning and construction quality.

[0004] Therefore, it is necessary to design a building surveying method based on aerial photography to solve the problems existing in the current technology. Summary of the Invention

[0005] In view of this, the present invention proposes a building surveying method based on aerial photography, which aims to solve the problems of low efficiency and poor accuracy in current building surveying methods.

[0006] This invention proposes a building surveying method based on aerial photography, comprising the following steps:

[0007] S100: Determine the building to be surveyed, divide the surface of the building into several survey areas, collect image data of each survey area and establish a building image dataset, generate an initial building outline based on the building image dataset; obtain the basic dimension data of the building to be surveyed, and determine the initial shooting interval of the camera based on the basic dimension data;

[0008] S200: The camera mounted on the flight platform takes pictures of the building to be surveyed along a preset flight path and at the initial shooting interval to obtain aerial image data of the building to be surveyed; the initial building outline is reconstructed in three dimensions based on the aerial image data to generate an initial three-dimensional point cloud model of the building to be surveyed.

[0009] S300: Divide the initial three-dimensional point cloud model into several monitoring areas, collect the local density of each monitoring area, and determine whether to adjust the initial shooting interval based on the local density;

[0010] S400: When it is determined that the initial shooting interval needs to be adjusted, the coverage data of the building to be surveyed is collected, and the shooting influence factor is calculated based on the coverage data and local density; the shooting influence factor is compared with historical data, and the initial shooting interval is adjusted based on the comparison result;

[0011] S500: Stores the shooting influence factors.

[0012] Further, when generating the initial building outline based on the building image dataset, the process includes:

[0013] The edge information of the building to be surveyed is extracted from the image dataset, and the shape information of the building to be surveyed is identified by the image processing algorithm;

[0014] Based on the shape information, geometric shape fitting technology is used to determine the basic architectural outline of the building to be surveyed.

[0015] Extract the structural feature data of the building to be surveyed, and optimize the basic building outline based on the structural feature data to obtain the optimized building outline;

[0016] The optimized building outline is adjusted based on the basic dimensional data to obtain the initial building outline.

[0017] Further, when acquiring the basic dimension data of the building to be surveyed, and determining the initial shooting interval of the camera based on the basic dimension data, the process includes:

[0018] The basic dimensional data includes the length, width, and height of the building to be measured;

[0019] The initial shooting interval is calculated based on the length, width, and height; the initial shooting interval is obtained using the following formula:

[0020]

[0021] Where I represents the initial shooting interval; L represents the length; W represents the width; h represents the flight altitude of the flight platform; and C represents a constant coefficient.

[0022] Further, when performing three-dimensional reconstruction of the initial building outline based on the aerial image data to generate an initial three-dimensional point cloud model of the building to be surveyed, the process includes:

[0023] All view feature data are extracted from the aerial image data, and all view feature data are aligned using image registration technology;

[0024] A stereo matching algorithm is used to extract the three-dimensional point data corresponding to all the aforementioned viewpoint feature data;

[0025] The three-dimensional point data is converted into the initial three-dimensional point cloud model using a point cloud generation algorithm.

[0026] Further, when collecting the local density of each of the monitored areas and determining whether to adjust the initial shooting interval based on the local density, the process includes:

[0027] The local density is obtained by the following formula:

[0028]

[0029] Where Di represents the local density of the i-th monitoring area; Ni represents the number of three-dimensional point data extracted from the i-th monitoring area; and Ai represents the area of ​​the i-th monitoring area.

[0030] Furthermore, when collecting the local density of each of the monitored areas and determining whether to adjust the initial shooting interval based on the local density, the method further includes:

[0031] The monitoring areas are classified to obtain important monitoring areas and non-important monitoring areas;

[0032] The local density of all the important monitoring areas is compared with the first local density threshold one by one, and the number of important monitoring areas with local density less than the first local density threshold is counted and recorded as the first monitoring number.

[0033] The local density of each of the non-critical monitoring areas is compared with the second local density threshold, and the number of non-critical monitoring areas whose local density is less than the second local density threshold is counted and recorded as the second monitoring number.

[0034] The weighted average of the first and second monitoring quantities is used to obtain the comprehensive quantity value.

[0035] Based on the comprehensive quantitative value, determine whether to adjust the initial shooting interval.

[0036] Furthermore, when determining whether to adjust the initial shooting interval based on the comprehensive quantity value, the process includes:

[0037] The overall quantity value is compared with the overall quantity value threshold, and the initial shooting interval is adjusted based on the comparison result.

[0038] When the overall quantity value is greater than or equal to the overall quantity value threshold, it is determined that the initial shooting interval should be adjusted.

[0039] When the overall quantity value is less than the overall quantity value threshold, it is determined that the initial shooting interval will not be adjusted.

[0040] Furthermore, when it is determined that the initial shooting interval needs to be adjusted, the coverage data of the building to be surveyed is collected, and the shooting influence factor is calculated based on the coverage data and local density, including:

[0041] The coverage data includes image overlap rate and surface coverage of the building to be mapped.

[0042] The shooting influence factor is calculated based on the image overlap rate and the surface coverage of the building to be mapped; the shooting influence factor is obtained by the following formula:

[0043]

[0044] Where If represents the shooting influence factor, R0 represents the image overlap rate, Rc represents the surface coverage of the building to be surveyed, and α represents the weighting coefficient.

[0045] Furthermore, when comparing the shooting impact factor with historical data and adjusting the initial shooting interval based on the comparison results, the process includes:

[0046] When there is a historical shooting factor in the historical data that is the same as the shooting impact factor, the initial shooting interval is adjusted according to the historical adjustment coefficient corresponding to the historical shooting factor, and the final shooting interval is obtained.

[0047] When there is no historical shooting factor in the historical data that is the same as the shooting impact factor, all historical shooting factors in the historical data that are greater than the shooting impact factor are obtained, and a historical shooting factor dataset is established. The initial shooting interval is then adjusted based on the historical shooting factor dataset.

[0048] Further, when adjusting the initial shooting interval based on the historical shooting factor dataset, the following steps are included:

[0049] The average value of historical shooting factors is calculated based on the historical shooting factor dataset and denoted as the shooting average value.

[0050] The average shooting value is compared with a first average shooting value threshold and a second average shooting value threshold. An adjustment coefficient for the initial shooting interval is determined based on the comparison result, and the initial shooting interval is adjusted according to the adjustment coefficient. Wherein, the first average shooting value threshold is less than the second average shooting value threshold.

[0051] When the average shooting value is less than or equal to the first average shooting value threshold, the adjustment coefficient of the initial shooting interval is determined as the first adjustment coefficient, and the product of the first adjustment coefficient and the initial shooting interval is taken as the final shooting interval.

[0052] When the average shooting value is greater than the first average shooting value threshold and less than or equal to the second average shooting value threshold, the adjustment coefficient of the initial shooting interval is determined as the second adjustment coefficient, and the product of the second adjustment coefficient and the initial shooting interval is taken as the final shooting interval.

[0053] When the average shooting value is greater than the second average shooting value threshold, the adjustment coefficient of the initial shooting interval is determined to be the third adjustment coefficient, and the product of the third adjustment coefficient and the initial shooting interval is taken as the final shooting interval.

[0054] Wherein, the first adjustment coefficient is less than the second adjustment coefficient, and the second adjustment coefficient is less than the third adjustment coefficient.

[0055] Compared with existing technologies, the beneficial effects of this invention are as follows: The aerial photography-based architectural surveying method provided by this invention can effectively improve the efficiency and accuracy of architectural surveying. Aerial photography technology allows for the acquisition of detailed image data of buildings and their surrounding environment in a shorter time, thereby reducing manpower and time costs. The aerial photography-based architectural surveying method provided by this invention can adapt to the surveying needs of complex terrain and densely built-up areas. The initial 3D point cloud model generated through 3D reconstruction technology provides accurate data support for subsequent architectural planning and design. Simultaneously, by analyzing the local density of the monitoring area and calculating the shooting influence factor, the shooting interval can be dynamically adjusted to further optimize the surveying process and ensure the integrity and accuracy of the data. Ultimately, the aerial photography-based architectural surveying method provided by this invention not only improves the efficiency of architectural surveying but also enhances the quality of the surveying results, providing strong technical support for urban planning and construction. Attached Figure Description

[0056] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0057] Figure 1 A flowchart of a building surveying method based on aerial photography provided in an embodiment of the present invention. Detailed Implementation

[0058] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the disclosure to those skilled in the art. It should be noted that, unless otherwise specified, embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0059] See Figure 1 As shown in some embodiments of this application, this embodiment provides a building surveying method based on aerial photography, including the following steps:

[0060] S100: Determine the building to be surveyed, divide the surface of the building into several survey areas, collect image data of each survey area and establish a building image dataset, generate the initial building outline based on the building image dataset; obtain the basic dimension data of the building to be surveyed, and determine the initial shooting interval of the camera based on the basic dimension data;

[0061] S200: A flight platform equipped with a camera takes pictures of the building to be surveyed along a preset flight path at an initial shooting interval to obtain aerial image data of the building to be surveyed; the initial building outline is reconstructed in three dimensions based on the aerial image data to generate an initial three-dimensional point cloud model of the building to be surveyed.

[0062] S300: Divide the initial 3D point cloud model into several monitoring areas, collect the local density of each monitoring area, and determine whether to adjust the initial shooting interval based on the local density;

[0063] S400: When it is determined that the initial shooting interval needs to be adjusted, the coverage data of the building to be surveyed is collected, and the shooting impact factor is calculated based on the coverage data and local density; the shooting impact factor is compared with historical data, and the initial shooting interval is adjusted based on the comparison results;

[0064] S500: Stores shooting impact factors.

[0065] In this embodiment, the image data of the surveyed area was collected by a camera without being mounted on a flight platform.

[0066] Understandably, in step S100, the acquisition of basic dimensional data can be achieved in various ways, such as using laser rangefinders, ultrasonic rangefinders, or existing architectural drawings. When determining the initial shooting interval of the camera, the selection of the constant coefficient C depends on the camera resolution, the flight speed of the flight platform, and the desired mapping accuracy. The flight platform is a drone, helicopter, or other type of aircraft, and its onboard camera needs to have high resolution and stable performance to ensure the acquisition of high-quality aerial image data. The division of the monitoring area can be based on the structural characteristics and complexity of the building to ensure the accuracy and efficiency of the 3D reconstruction. The storage of the shooting influence factors adopts a database management system to facilitate subsequent data retrieval and analysis.

[0067] It is understood that the aerial photography-based architectural surveying method provided in this embodiment can effectively improve the efficiency and accuracy of architectural surveying. Aerial photography technology allows for the acquisition of detailed image data of buildings and their surrounding environment in a short time, thereby reducing manpower and time costs. The aerial photography-based architectural surveying method provided in this embodiment can adapt to the surveying needs of complex terrain and densely built-up areas. The initial 3D point cloud model generated through 3D reconstruction technology provides accurate data support for subsequent architectural planning and design. Simultaneously, by analyzing the local density of the monitoring area and calculating the shooting influence factor, the shooting interval can be dynamically adjusted to further optimize the surveying process and ensure the integrity and accuracy of the data. Ultimately, the aerial photography-based architectural surveying method provided in this embodiment not only improves the efficiency of architectural surveying but also enhances the quality of the surveying results, providing strong technical support for urban planning and construction.

[0068] Specifically, when generating the initial building outline based on the building image dataset, the process includes:

[0069] The edge information of the building to be surveyed is extracted from the image dataset, and the shape information of the building to be surveyed is identified by the image processing algorithm.

[0070] The basic architectural outline of the building to be surveyed is determined by using geometric shape fitting technology based on the shape information.

[0071] Extract the structural feature data of the building to be surveyed, and optimize the basic building outline based on the structural feature data to obtain the optimized building outline.

[0072] The building outline is adjusted based on the basic dimensional data to obtain the initial building outline.

[0073] Understandably, the shape information of the building to be mapped refers to features such as the building's outline, the location of doors and windows, and the shape of the roof. When extracting edge information, edge detection algorithms such as the Canny edge detector can be used to identify significant edges in the image. Geometric shape fitting techniques can include fitting basic geometric shapes such as lines, curves, and polygons to form a preliminary model of the building's outline. Extraction of structural feature data may involve identifying and classifying specific parts of the building, such as windows, doors, and balconies, to further refine the building outline. Adjusting the basic dimensional data ensures that the dimensions of the building outline match the actual building, providing an accurate reference for subsequent 3D reconstruction. Through these steps, an accurate initial building outline can be generated, laying a solid foundation for the 3D reconstruction of the building.

[0074] Specifically, when acquiring the basic dimensions of the building to be surveyed and determining the initial shooting interval of the camera based on the basic dimensions, the process includes:

[0075] Basic dimensional data includes the length, width, and height of the building to be measured;

[0076] The initial shooting interval is calculated based on the length, width, and height; the initial shooting interval is obtained using the following formula:

[0077]

[0078] Where I represents the initial shooting interval; L represents the length; W represents the width; h represents the flight altitude of the flight platform; and C represents a constant coefficient.

[0079] Understandably, the selection of C is related to the camera's resolution, the flight speed of the flight platform, and the desired mapping accuracy. For example, if the desired mapping accuracy is high, the constant coefficient C may be chosen to be small to ensure that the images captured by the camera can capture sufficient detail. Conversely, if the mapping accuracy requirement is not particularly high, or to improve shooting efficiency, the value of C can be appropriately increased, thereby reducing the number of shots. Furthermore, the flight altitude h of the flight platform also affects the calculation of the initial shooting interval I. The higher the flight altitude, the more likely the initial shooting interval may need to be increased to maintain the same mapping accuracy. Through such calculations and adjustments, high-quality aerial imagery data can be obtained under different flight altitudes and mapping accuracy requirements, providing a reliable foundation for subsequent 3D reconstruction.

[0080] Specifically, when performing 3D reconstruction of the initial building outline based on aerial imagery data to generate an initial 3D point cloud model of the building to be surveyed, the process includes:

[0081] Extract all viewpoint feature data from aerial imagery data and align all viewpoint feature data using image registration technology;

[0082] A stereo matching algorithm is used to extract the 3D point data corresponding to all viewpoint feature data;

[0083] The three-dimensional point data is converted into an initial three-dimensional point cloud model through a point cloud generation algorithm.

[0084] Understandably, image registration is a crucial step in ensuring accurate alignment of images captured from different viewpoints. This typically involves complex image processing algorithms, such as feature point matching, image transformation, and error correction. Stereo matching algorithms extract depth information from the registered multi-view images, generating point data in three-dimensional space. Point cloud generation algorithms integrate this point data to form a continuous 3D point cloud model, providing the foundation for subsequent 3D modeling and analysis. During 3D reconstruction, the occlusion of buildings must also be considered to ensure all necessary details are captured and reconstructed. Through the comprehensive application of these technologies, a detailed and accurate 3D point cloud model can be generated, providing strong data support for architectural surveying and subsequent urban planning.

[0085] Specifically, when collecting local density data for each monitoring area and determining whether to adjust the initial shooting interval based on the local density, the process includes:

[0086] Local density is obtained by the following formula:

[0087]

[0088] Where Di represents the local density of the i-th monitoring area; Ni represents the number of three-dimensional point data extracted from the i-th monitoring area; and Ai represents the area of ​​the i-th monitoring area.

[0089] Specifically, when collecting local density data for each monitoring area and determining whether to adjust the initial shooting interval based on the local density, the process also includes:

[0090] The monitoring areas are classified into important monitoring areas and non-important monitoring areas;

[0091] Compare the local density of all important monitoring areas one by one with the first local density threshold, and count the number of important monitoring areas whose local density is less than the first local density threshold, which is recorded as the first monitoring number.

[0092] The local density of each non-critical monitoring area is compared with the second local density threshold, and the number of non-critical monitoring areas with a local density less than the second local density threshold is counted and recorded as the second monitoring quantity.

[0093] The comprehensive quantity value is obtained by weighted averaging the first and second monitoring quantities.

[0094] Determine whether to adjust the initial shooting interval based on the overall numerical values.

[0095] Specifically, when determining whether to adjust the initial shooting interval based on the overall quantity value, this includes:

[0096] The overall quantity value is compared with the overall quantity value threshold, and the initial shooting interval is adjusted based on the comparison result.

[0097] When the overall quantity value is greater than or equal to the overall quantity value threshold, it is determined that the initial shooting interval should be adjusted.

[0098] When the overall quantity value is less than the overall quantity value threshold, it is determined that the initial shooting interval will not be adjusted.

[0099] Understandably, when the overall quantity value exceeds the preset adjustment threshold, the initial shooting interval needs to be adjusted. The purpose of this adjustment is to ensure the quality of 3D reconstruction across all monitored areas, especially for areas with low local density, where increased shooting frequency is necessary to improve data integrity. During the adjustment process, the shooting interval can be appropriately reduced to obtain more detailed information.

[0100] Specifically, when it is determined that the initial shooting interval needs to be adjusted, the coverage data of the building to be surveyed is collected. The shooting impact factor is calculated based on the coverage data and local density, including:

[0101] Coverage data includes image overlap rate and surface coverage of the building to be mapped;

[0102] The image impact factor is calculated based on the image overlap rate and the surface coverage of the building to be mapped; the image impact factor is obtained by the following formula:

[0103]

[0104] Where If represents the shooting influence factor, R0 represents the image overlap rate, Rc represents the surface coverage of the building to be surveyed, and α represents the weighting coefficient.

[0105] In aerial photogrammetry, image overlap rate refers to the proportion of the overlapping area between two adjacent aerial images to the area of ​​a single image. The surface coverage rate of the building to be mapped refers to the proportion of the building's surface captured in the photograph to the actual building's surface area; it directly affects the integrity and accuracy of the 3D model. The weighting coefficient α is used to balance the contributions of image overlap rate and building surface coverage rate to the shooting influence factors. The value of α depends on the specific application scenario and accuracy requirements. By reasonably setting the α value, the shooting strategy can be optimized, ensuring that the quality of 3D reconstruction is maintained while minimizing the number of shots and improving work efficiency.

[0106] Specifically, when comparing the shooting impact factor with historical data and adjusting the initial shooting interval based on the comparison results, the following steps are included:

[0107] When there is a historical shooting factor in the historical data that is the same as the shooting impact factor, the initial shooting interval is adjusted according to the historical adjustment coefficient corresponding to the historical shooting factor, and the final shooting interval is obtained.

[0108] When there is no historical shooting factor that is the same as the shooting impact factor in the historical data, all historical shooting factors that are greater than the shooting impact factor in the historical data are obtained, and a historical shooting factor dataset is established. The initial shooting interval is then adjusted based on the historical shooting factor dataset.

[0109] In this embodiment, historical data refers to the shooting impact factors and corresponding adjustment coefficients collected in previous mapping missions. This data is recorded and stored for analysis and comparison to guide current and future shooting interval adjustments. By comparing the current shooting impact factors with similar factors in historical data, it can be determined whether the initial shooting interval needs adjustment and how to adjust it.

[0110] Specifically, when adjusting the initial shooting interval based on a historical shooting factor dataset, the following is included:

[0111] The average value of historical shooting factors is calculated based on the historical shooting factor dataset and denoted as the shooting average value.

[0112] The average shooting value is compared with a first average shooting value threshold and a second average shooting value threshold. Based on the comparison result, an adjustment coefficient for the initial shooting interval is determined, and the initial shooting interval is adjusted according to the adjustment coefficient. The first average shooting value threshold is less than the second average shooting value threshold.

[0113] When the average shooting value is less than or equal to the first average shooting value threshold, the adjustment coefficient of the initial shooting interval is determined as the first adjustment coefficient, and the product of the first adjustment coefficient and the initial shooting interval is used as the final shooting interval.

[0114] When the average shooting value is greater than the first average shooting value threshold and less than or equal to the second average shooting value threshold, the adjustment coefficient of the initial shooting interval is determined as the second adjustment coefficient, and the product of the second adjustment coefficient and the initial shooting interval is used as the final shooting interval.

[0115] When the average shooting value is greater than the second average shooting value threshold, the adjustment coefficient of the initial shooting interval is determined as the third adjustment coefficient, and the product of the third adjustment coefficient and the initial shooting interval is used as the final shooting interval.

[0116] Among them, the first adjustment coefficient is less than the second adjustment coefficient, and the second adjustment coefficient is less than the third adjustment coefficient.

[0117] Understandably, by setting different adjustment coefficients, different shooting conditions and environmental changes can be flexibly addressed. The aerial photography-based architectural surveying method provided in this embodiment not only improves the efficiency of architectural surveying but also enhances the quality of surveying results, providing strong technical support for urban planning and construction.

[0118] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program goods. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program goods embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0119] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program goods according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0120] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0121] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0122] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A building surveying method based on aerial photography, characterized in that, The application relates to a method for generating a three-dimensional point cloud model of a building to be surveyed, comprising the following steps: determining a building to be surveyed, dividing a surface of the building to be surveyed into a plurality of surveying areas, collecting image data of each surveying area and establishing a building image data set, and generating an initial building contour according to the building image data set; obtaining basic size data of the building to be surveyed, and determining an initial shooting interval of a camera according to the basic size data, comprising: the basic size data comprises length, width and height of the building to be surveyed; the initial shooting interval is obtained according to the length, width and height by the following formula: wherein I represents the initial shooting interval, L represents the length, W represents the width, h represents the flight height of a flight platform, and C represents a constant coefficient; adopting the flight platform to carry the camera to shoot the building to be surveyed according to a preset flight path and the initial shooting interval, and obtaining aerial image data of the building to be surveyed; according to the aerial image data, three-dimensional reconstruction is performed on the initial building contour to generate an initial three-dimensional point cloud model of the building to be surveyed, comprising: extracting all visual feature data from the aerial image data, and aligning all the visual feature data through image registration technology; adopting a stereo matching algorithm to extract three-dimensional point data corresponding to all the visual feature data; the three-dimensional point data is converted into the initial three-dimensional point cloud model through a point cloud generation algorithm; dividing the initial three-dimensional point cloud model into a plurality of monitoring areas, collecting local density of each monitoring area, and judging whether the initial shooting interval is adjusted according to the local density; the local density is obtained by the following formula: wherein Di represents the local density of the i-th monitoring area, Ni represents the number of three-dimensional point data extracted in the i-th monitoring area, and Ai represents the area of the i-th monitoring area; when it is determined that the initial shooting interval is adjusted, collecting coverage data of the building to be surveyed, calculating a shooting influence factor according to the coverage data and the local density, comparing the shooting influence factor with historical data, and adjusting the initial shooting interval according to the comparison result; storing the shooting influence factor.

2. The photogrammetry-based building surveying method according to claim 1, characterized in that, when the initial building contour is generated according to the building image data set, comprising: extracting edge information of the building to be surveyed from the image data set, and recognizing shape information of the building to be surveyed through an image processing algorithm; determining a basic building contour of the building to be surveyed based on the shape information through a geometric shape fitting technology; extracting structure feature data of the building to be surveyed, performing contour optimization on the basic building contour according to the structure feature data, and obtaining an optimized building contour; adjusting the optimized building contour according to the basic size data to obtain the initial building contour.

3. The photogrammetry method according to claim 2, wherein when the local density of each monitoring area is collected and whether the initial shooting interval is adjusted is judged according to the local density, further comprising: classifying the monitoring areas to obtain important monitoring areas and non-important monitoring areas; The local density of each of the important monitoring areas is compared with the first local density threshold, and the number of important monitoring areas with a local density less than the first local density threshold is counted as a first monitoring number; The local density of each of the unimportant monitoring areas is compared with the second local density threshold, and the number of unimportant monitoring areas with a local density less than the second local density threshold is counted as a second monitoring number; The first monitoring number and the second monitoring number are weighted and averaged to obtain a comprehensive number value; The initial photographing interval is adjusted according to the comprehensive number value.

4. The photogrammetry method according to claim 3, wherein When it is determined whether to adjust the initial photographing interval according to the comprehensive number value, the following steps are included: The comprehensive number value is compared with a comprehensive number value threshold, and it is determined whether to adjust the initial photographing interval according to the comparison result; When the comprehensive number value is greater than or equal to the comprehensive number value threshold, it is determined to adjust the initial photographing interval; When the comprehensive number value is less than the comprehensive number value threshold, it is determined not to adjust the initial photographing interval.

5. The photogrammetry-based building surveying method according to claim 1, characterized in that, When it is determined to adjust the initial photographing interval, the coverage data of the building to be mapped is collected, and the photographing influence factor is calculated according to the coverage data and the local density, including: The coverage data includes an image overlap rate and a building-to-be-mapped surface coverage rate; The photographing influence factor is calculated according to the image overlap rate and the building-to-be-mapped surface coverage rate; the photographing influence factor is obtained by the following formula: Where If represents the photographing influence factor, R0 represents the image overlap rate, Rc represents the building-to-be-mapped surface coverage rate, and a represents a weight coefficient.

6. The photogrammetry method according to claim 5, wherein When the photographing influence factor is compared with the historical data, and the initial photographing interval is adjusted according to the comparison result, the following steps are included: When there is a historical photographing factor identical to the photographing influence factor in the historical data, the initial photographing interval is adjusted according to the historical adjustment coefficient corresponding to the historical photographing factor, and a final photographing interval is obtained; When there is no historical photographing factor identical to the photographing influence factor in the historical data, all historical photographing factors greater than the photographing influence factor in the historical data are obtained, a historical photographing factor dataset is established, and the initial photographing interval is adjusted according to the historical photographing factor dataset.

7. The photogrammetry method according to claim 6, wherein When the initial photographing interval is adjusted according to the historical photographing factor dataset, the following steps are included: An average value of the historical photographing factors is calculated according to the historical photographing factor dataset, and is recorded as a photographing average value; The photographing average value is compared with a first photographing average value threshold and a second photographing average value threshold, an adjustment coefficient of the initial photographing interval is determined according to the comparison result, and the initial photographing interval is adjusted according to the adjustment coefficient; the first photographing average value threshold is less than the second photographing average value threshold. when the shooting average value is less than or equal to the first shooting average threshold value, determining an adjustment coefficient of the initial shooting interval as a first adjustment coefficient, and taking a product value of the first adjustment coefficient and the initial shooting interval as a final shooting interval; when the shooting average value is greater than the first shooting average threshold value and less than or equal to the second shooting average threshold value, determining an adjustment coefficient of the initial shooting interval as a second adjustment coefficient, and taking a product value of the second adjustment coefficient and the initial shooting interval as the final shooting interval; when the shooting average value is greater than the second shooting average threshold value, determining an adjustment coefficient of the initial shooting interval as a third adjustment coefficient, and taking a product value of the third adjustment coefficient and the initial shooting interval as the final shooting interval; wherein the first adjustment coefficient is less than the second adjustment coefficient, and the second adjustment coefficient is less than the third adjustment coefficient.

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