A Triangulation Network Construction Method and System Based on Oblique Photogrammetry Modeling

Abstract

The present invention discloses a method and system for constructing a triangular network based on oblique photography modeling, which relates to the technical field of triangular network construction. Among them, the method for constructing the triangular network includes: collecting flight data of the flight route, evaluating the influence of the overlap degree on the construction accuracy of the triangular network based on the flight data of the flight route, collecting ground control point data, evaluating the influence of the distribution of ground control points on the construction accuracy of the triangular network based on the ground control point data, collecting point cloud data, evaluating the influence of the point cloud distribution on the construction accuracy of the triangular network based on the point cloud data, collecting data of the photographic equipment, evaluating the influence of the photographic equipment on the construction accuracy of the triangular network based on the data of the photographic equipment, predicting the construction accuracy of the triangular network based on the influence of the overlap degree, the distribution of ground control points, the point cloud distribution and the photographic equipment on the construction accuracy of the triangular network, and determining whether the triangular network meets the construction standard. The present invention improves the accuracy of prediction, thereby improving the quality of triangular network construction and solving the technical problem that the construction accuracy of the triangular network does not meet the standard.

Description

Technical Field

[0001] The present invention relates to the field of triangular network construction, and more specifically, to a method and system for triangular network construction based on oblique photography modeling. Background Art

[0002] A triangular network is a geometric model used to represent the surface of the earth or other three-dimensional space objects. It consists of a series of irregular triangles that together cover the entire area, and the vertices of each triangle contain information about the position of that point. The triangular network can achieve three-dimensional visualization of the terrain.

[0003] Currently, the judgment of the accuracy of triangular network construction in related technologies is mostly based on experience, lacking systematic accuracy prediction, which may lead to insufficient or excessive collection of photographic data, increasing unnecessary costs and time, thus reducing the accuracy of the prediction of triangular network construction accuracy, resulting in low construction quality and construction efficiency, and there is a problem that the accuracy of triangular network construction does not meet the standard.

[0004] In response to the above problems, no effective solution has been proposed yet. Therefore, the present invention provides a method and system for triangular network construction based on oblique photography modeling. Summary of the Invention

[0005] The present invention provides a method and system for triangular network construction based on oblique photography modeling. The present invention comprehensively judges the influence of flight line overlap, ground control point distribution, point cloud distribution, and photographic equipment on triangular network construction, and predicts the construction accuracy before triangular network construction, improving the accuracy of the prediction, thereby improving the quality of triangular network construction and solving the technical problem that the accuracy of triangular network construction does not meet the standard.

[0006] A method for triangular network construction based on oblique photography modeling provided by the first aspect of the present invention includes:

[0007] S1. Collect flight line data, evaluate the heading overlap and side overlap based on the flight line data, and then evaluate the influence of the overlap on the accuracy of triangular network construction based on the heading overlap and side overlap;

[0008] S2. Collect ground control point data and evaluate the influence of the ground control point distribution on the accuracy of triangular network construction based on the ground control point data;

[0009] S3. Collect point cloud data and evaluate the influence of the point cloud distribution on the accuracy of triangular network construction based on the point cloud data;

[0010] S4. Collect photographic equipment data and evaluate the influence of the photographic equipment on the accuracy of triangular network construction based on the photographic equipment data;

[0011] S5. Estimate the accuracy of triangular network construction based on the influence of overlap degree, distribution of ground control points, point cloud distribution, and photographic equipment on the accuracy of triangular network construction, and determine whether the triangular network meets the construction standards.

[0012] Optionally, the S1 includes the following specific steps:

[0013] S11. Collect flight data of the flight path, where the flight data of the flight path includes the heading side length of the image format, the lateral side length of the image format, the length of the heading overlap part, and the length of the lateral overlap part;

[0014] S12. Evaluate the heading overlap degree based on the heading side length of the image format and the length of the heading overlap part;

[0015] S13. Evaluate the lateral overlap degree based on the lateral side length of the image format and the length of the lateral overlap part;

[0016] S14. Evaluate the influence value of the overlap degree on the accuracy of triangular network construction based on the heading overlap degree and the lateral overlap degree.

[0017] Optionally, the S2 includes the following specific steps:

[0018] S21. Collect ground control point data, where the ground control point data includes ground control point coordinates;

[0019] S22. Evaluate the coordinate residual value, coverage area, and coordinate distribution uniformity based on the ground control point coordinates;

[0020] S23. Evaluate the influence value of the distribution of ground control points on the accuracy of triangular network construction based on the coordinate residual value, coverage area, and coordinate distribution uniformity.

[0021] Optionally, the S3 includes the following specific steps:

[0022] S31. Collect point cloud data, where the point cloud data includes point cloud density and point cloud distribution uniformity;

[0023] S32. Evaluate the influence value of the point cloud distribution on the accuracy of triangular network construction based on the point cloud density and the point cloud distribution uniformity.

[0024] Optionally, the S4 includes the following specific steps:

[0025] S41. Collect photographic equipment data, where the photographic equipment data includes vibration data, and the vibration data includes vibration amplitude and vibration frequency;

[0026] S42. Evaluate the influence value of the photographic equipment on the accuracy of triangular network construction based on the vibration amplitude and the vibration frequency.

[0027] Optionally, the S5 includes the following specific steps:

[0028] S51. Obtain a preliminary estimate of the triangular network construction accuracy based on the influence value of the overlap degree on the triangular network construction accuracy, the influence value of the distribution of ground control points on the triangular network construction accuracy, the influence value of the point cloud distribution on the triangular network construction accuracy, and the influence value of the photographic equipment on the triangular network construction accuracy;

[0029] S52. Determine whether the triangular network meets the construction standard based on the preliminary estimate of the triangular network construction accuracy and the preset triangular network construction accuracy threshold. If the preliminary estimate of the triangular network construction accuracy is greater than or equal to the preset triangular network construction accuracy threshold, it is determined that the triangular network meets the construction standard; if the preliminary estimate of the triangular network construction accuracy is less than the preset triangular network construction accuracy threshold, it is determined that the triangular network does not meet the construction standard and the photography is readjusted.

[0030] A triangular network construction system provided in the second aspect of the present invention is implemented based on the above-mentioned triangular network construction method based on oblique photography modeling, and includes: a data acquisition module for acquiring flight data of the flight path, ground control point data, point cloud data, and photographic equipment data;

[0031] An overlap degree influence evaluation module for evaluating the heading overlap degree and the lateral overlap degree based on the flight data of the flight path, and then evaluating the influence of the overlap degree on the triangular network construction accuracy based on the heading overlap degree and the lateral overlap degree;

[0032] A ground control point influence evaluation module for evaluating the influence of the distribution of ground control points on the triangular network construction accuracy based on the ground control point data;

[0033] A point cloud influence evaluation module for evaluating the influence of the point cloud distribution on the triangular network construction accuracy based on the point cloud data;

[0034] A photographic equipment influence evaluation module for evaluating the influence of the photographic equipment on the triangular network construction accuracy based on the photographic equipment data;

[0035] An accuracy prediction module for predicting the triangular network construction accuracy based on the influence of the overlap degree, the distribution of ground control points, the point cloud distribution, and the photographic equipment on the triangular network construction accuracy;

[0036] A judgment module for judging whether the triangular network meets the construction standard based on the preliminary estimate of the triangular network construction accuracy.

[0037] An electronic device provided in the third aspect of the present invention includes a memory and a processor. When the computer program stored in the memory is executed by the processor, the processor executes the steps of the triangular network construction method based on oblique photography modeling as described in any one of the above.

[0038] From the above technical solutions, it can be seen that the present invention has the following advantages:

[0039] The present invention collects flight data of a flight route, evaluates the heading overlap degree and the side overlap degree based on the flight data of the flight route, then evaluates the influence of the overlap degree on the accuracy of triangulation network construction based on the heading overlap degree and the side overlap degree, collects ground control point data, evaluates the influence of the distribution of ground control points on the accuracy of triangulation network construction based on the ground control point data, collects point cloud data, evaluates the influence of the point cloud distribution on the accuracy of triangulation network construction based on the point cloud data, collects data of a photographic device, evaluates the influence of the photographic device on the accuracy of triangulation network construction based on the data of the photographic device, estimates the accuracy of triangulation network construction based on the influence of the overlap degree, the distribution of ground control points, the point cloud distribution and the photographic device on the accuracy of triangulation network construction, and determines whether the triangulation network meets the construction standard. The present invention comprehensively judges the influence on the construction of the triangulation network through the flight route overlap degree, the distribution of ground control points, the point cloud distribution and the photographic device, estimates the construction accuracy before the construction of the triangulation network, improves the accuracy of the estimation, thereby improving the quality of the triangulation network construction, and solves the technical problem that the accuracy of the triangulation network construction does not meet the standard. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0041] Figure 1 It is a flowchart of the steps of a triangulation network construction method based on oblique photography modeling provided by an embodiment of the present invention;

[0042] Figure 2 It is a flowchart of the S1 step in a triangulation network construction method based on oblique photography modeling provided by an embodiment of the present invention;

[0043] Figure 3 It is a schematic diagram of the heading overlap provided by an embodiment of the present invention;

[0044] Figure 4 It is a schematic diagram of the side overlap provided by an embodiment of the present invention;

[0045] Figure 5 It is a schematic diagram of the overall framework of a triangulation network construction system based on oblique photography modeling provided by an embodiment of the present invention;

[0046] Figure 6 It is a block diagram of the structure of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0047] An embodiment of the present invention provides a method and system for constructing a triangular network based on oblique photography modeling. By comprehensively judging the influence of flight line overlap, ground control point distribution, point cloud distribution, and photographic equipment on the construction of the triangular network, the construction accuracy is estimated before the construction of the triangular network, improving the accuracy of the estimation, thereby improving the quality of the triangular network construction, and is used to solve the technical problem that the construction accuracy of the triangular network does not meet the standard.

[0048] In order to make the invention purpose, features, and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the embodiments described below are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present invention.

[0049] For easy understanding, the following terms are explained:

[0050] Image format: The image format is the image formation format size of the photo;

[0051] Forward overlap: Forward overlap refers to the overlap of the same image on adjacent photos. Among them, the overlap of two adjacent photos on the same flight line is called forward overlap. Forward overlap is also called "longitudinal overlap". In aerial photography, there is the same ground image part on adjacent photos along the same flight line;

[0052] Side overlap: Side overlap is also called "lateral overlap". Side overlap of photos refers to the overlap of the same image on adjacent photos. Among them, the overlap of two adjacent photos between adjacent flight lines is called side overlap;

[0053] Ground control point: A ground control point is a point with a precisely known position on the earth's surface, and is used to correct and calibrate spatial data in the fields of geographic information system (GIS), remote sensing, photogrammetry, and other geospatial data acquisition;

[0054] Oblique photography: It is an aerial photography technology that captures images of ground objects from multiple angles (usually angles other than directly downward). Compared with traditional vertical aerial photography, oblique photography can provide richer and more intuitive three-dimensional information and is commonly used in fields such as urban planning, disaster assessment, and architectural design.

[0055] Please refer to Figure 1 , Figure 1 which is a flowchart of the steps of a method for constructing a triangular network based on oblique photography modeling provided by an embodiment of the present invention.

[0056] A method for constructing a triangular network based on oblique photography modeling provided by the present invention includes the following specific steps:

[0057] S1. Collect flight data of the flight path, evaluate the heading overlap degree and the side overlap degree based on the flight data of the flight path, and then evaluate the influence of the overlap degree on the accuracy of triangulation network construction based on the heading overlap degree and the side overlap degree;

[0058] Please refer to Figure 2 , Figure 2 which is the flowchart of step S1 in a triangulation network construction method based on oblique photography modeling provided by an embodiment of the present invention.

[0059] In this embodiment, S1 includes the following specific steps:

[0060] S11. Collect flight data of the flight path. The flight data of the flight path includes the heading side length of the image frame, the side side length of the image frame, the length of the heading overlap part, and the length of the side overlap part;

[0061] Please refer to Figure 3 , Figure 3 which is the schematic diagram of heading overlap provided by an embodiment of the present invention. It can be seen from Figure 3 that A and B are two adjacent photos on the same flight path. The solid circles represent the principal point positions of photos A and B, and the shaded part is the heading overlap area.

[0062] S12. Evaluate the heading overlap degree based on the heading side length of the image frame and the length of the heading overlap part. The heading overlap degree can be obtained through the following formula: , where in the formula, is the length of the heading overlap part, is the heading side length of the image frame;

[0063] Please refer to Figure 4 , Figure 4 which is the schematic diagram of side overlap provided by an embodiment of the present invention. It can be seen from Figure 4 that A and B are two photos at corresponding positions on adjacent flight paths. The solid circles represent the principal point positions of photos A and B, and the shaded part is the side overlap area.

[0064] S13. Evaluate the side overlap degree based on the side side length of the image frame and the length of the side overlap part. The side overlap degree can be obtained through the following formula: , where in the formula, is the length of the side overlap part, is the side side length of the image frame;

[0065] S14. Evaluate the influence value of the overlap degree on the accuracy of triangulation network construction based on the heading overlap degree and the side overlap degree. The influence value of the overlap degree on the accuracy of triangulation network construction can be obtained through the following formula: , where in the formula, is the standard value of the heading overlap degree, Let \(O\) be the standard value of the lateral overlap. In this embodiment, the ratio of the longitudinal overlap to the standard value of the longitudinal overlap is directly proportional to the ratio of the lateral overlap to the standard value of the lateral overlap.

[0066] As an alternative, the longitudinal overlap should be between 60% and 80%, and the minimum should not be less than 53%; the lateral overlap should be between 15% and 60%, and the minimum should not be less than 8%. In actual operation, the longitudinal overlap is generally above 65%, and the lateral overlap is generally above 45%. Therefore, in this embodiment, the standard value of the longitudinal overlap is 65%, and the standard value of the lateral overlap is 45%.

[0067] As an alternative, when performing oblique photography on a protected building, obtain the flight altitude and ground control points, measure the length of the projection of the image format on the ground on-site to calculate the longitudinal side length and the lateral side length of the image format, identify the homologous points on adjacent images, measure the actual length of the overlapping area to calculate the length of the longitudinal overlap part, identify the images of adjacent flight lines, measure the length of the overlapping area to calculate the length of the lateral overlap part, evaluate whether the objects on the ground are completely represented in adjacent images through the longitudinal overlap, so as to avoid information loss and provide more accurate topographic information, splice the images of different flight lines together through the lateral overlap to form a complete ground coverage map, which helps to adapt to the terrain undulation and provide more detailed ground information, and evaluate the integrity of the aerial photography data by calculating the longitudinal overlap and the lateral overlap.

[0068] S2. Collect ground control point data and evaluate the influence of the distribution of ground control points on the accuracy of triangulation network construction based on the ground control point data;

[0069] In this embodiment, S2 includes the following specific steps:

[0070] S21. Collect ground control point data, and the ground control point data includes the coordinates of ground control points;

[0071] As an alternative, when performing oblique photography on a protected building, obtain the specific three-dimensional coordinates of the ground control points through high-precision measurement equipment.

[0072] S22. Evaluate the coordinate residual value, coverage area, and coordinate distribution uniformity based on the ground control point coordinates. The coordinate residual value can be obtained through the following formula: \(\Delta x_n = x_n - \overline{x}\), where \(x_n\) is the abscissa of the \(n\)th ground control point, \(y_n\) is the ordinate of the \(n\)th ground control point, \(z_n\) is the vertical coordinate of the \(n\)th ground control point, \(N\) is the number of ground control points, \(\overline{x}\) is the preset abscissa of the \(n\)th ground control point, is the preset vertical coordinate of the nth ground control point. is the preset vertical coordinate of the nth ground control point. The placement accuracy of the ground control point is evaluated by the coordinate residual value. The coverage area can be obtained by the following formula: where is the maximum value of the abscissa of the ground control point. is the minimum value of the abscissa of the ground control point. is the maximum value of the vertical coordinate of the ground control point. is the minimum value of the vertical coordinate of the ground control point. is the maximum value of the vertical coordinate of the ground control point. is the minimum value of the vertical coordinate of the ground control point. is the standard coverage volume, that is, the preset measurement range. In this embodiment, the coverage range of the ground control point is approximated as a cuboid. The accuracy of the geometric correction and registration of the photography range is evaluated by the coverage range. The coordinate distribution uniformity can be obtained by the following formula: where is the distance between the nth ground control point and its closest adjacent ground control point. is the average distance of the ground control points. The applicability of the ground control points is evaluated by the coordinate distribution uniformity.

[0073] S23. Evaluate the influence value of the ground control point distribution on the triangulation network construction accuracy based on the coordinate residual value, coverage area, and coordinate distribution uniformity. The influence value of the ground control point on the triangulation network construction accuracy can be obtained by the following formula: In this embodiment, the coverage area is inversely proportional to the product of the coordinate residual value and the coordinate distribution uniformity.

[0074] S3. Collect point cloud data and evaluate the influence of the point cloud distribution on the triangulation network construction accuracy based on the point cloud data.

[0075] In this embodiment, S3 includes the following specific steps:

[0076] S31. Collect point cloud data. The point cloud data includes point cloud density and point cloud distribution uniformity. The point cloud density can be obtained by the following formula: where is the number of points. is the volume occupied by the point cloud. The point cloud distribution uniformity can be obtained by the following formula: where is the number of points in the mth region. is the number of regions. is the average number of points in the region.

[0077] As an alternative solution, when performing oblique photography on a protected building, the photography range can be evenly divided into several regions, and the number of points within the regions can be collected.

[0078] S32. Evaluate the influence value of the point cloud distribution on the accuracy of triangular mesh construction based on the point cloud density and the uniformity of the point cloud distribution. The influence value of the point cloud distribution on the accuracy of triangular mesh construction can be obtained through the following formula: , a high density of the point cloud enables the constructed triangular mesh to accurately represent the original surface, and a uniform distribution of the point cloud makes the triangular mesh more regular and uniform.

[0079] S4. Collect data of the photographic equipment and evaluate the influence of the photographic equipment on the accuracy of triangular mesh construction based on the data of the photographic equipment;

[0080] In this embodiment, S4 includes the following specific steps:

[0081] S41. Collect data of the photographic equipment. The data of the photographic equipment includes vibration data, and the vibration data includes vibration amplitude and vibration frequency;

[0082] S42. Evaluate the influence value of the photographic equipment on the accuracy of triangular mesh construction based on the vibration amplitude and vibration frequency. The influence value of the photographic equipment on the accuracy of triangular mesh construction can be obtained through the following formula: , where is the duration of data collection of the photographic equipment, is the vibration frequency at time t, is the vibration amplitude at time t, is the standard vibration frequency, is the standard vibration amplitude, is the time integral. In this embodiment, the ratio of the vibration frequency to the standard vibration frequency is proportional to the ratio of the vibration amplitude to the standard vibration amplitude.

[0083] As an alternative solution, before performing oblique photography on a protected building, first use a photographic equipment that has passed the test for testing. During the testing process, collect the vibration data of the photographic equipment, collect the average value of the obtained vibration data respectively, use the average value of the vibration frequency as the standard vibration frequency of this embodiment, and use the average value of the vibration amplitude as the standard vibration amplitude of this embodiment.

[0084] S5. Estimate the accuracy of triangular mesh construction based on the overlap degree, the distribution of ground control points, the point cloud distribution, and the influence of the photographic equipment on the accuracy of triangular mesh construction, and determine whether the triangular mesh meets the construction standard.

[0085] In this embodiment, S5 includes the following specific steps:

[0086] S51. Obtain the predicted value of the triangular network construction accuracy based on the influence value of the overlap degree on the triangular network construction accuracy, the influence value of the distribution of ground control points on the triangular network construction accuracy, the influence value of the point cloud distribution on the triangular network construction accuracy, and the influence value of the photographic equipment on the triangular network construction accuracy. The predicted value of the triangular network construction accuracy can be obtained through the following formula: , where in the formula, is the preset triangular network construction accuracy, is the influence weight of the overlap degree, is the influence weight of the distribution of ground control points, is the influence weight of the point cloud distribution, is the influence weight of the photographic equipment, ;

[0087] As an optional solution, before performing oblique photography on a protected building, collect relevant data of the historical protected building, including overlap degree data, ground control point data, point cloud data, photographic equipment data, and the final triangular network construction data. Let experts in the field of photographic modeling analyze the influence of different data on the final triangular network construction based on historical relevant data and give appropriate weights as the influence weights of the overlap degree, the distribution of ground control points, the point cloud distribution, and the photographic equipment in this embodiment.

[0088] S52. Judge whether the triangular network meets the construction standard based on the predicted value of the triangular network construction accuracy and the preset triangular network construction accuracy threshold. If the predicted value of the triangular network construction accuracy is greater than or equal to the preset triangular network construction accuracy threshold, it is judged that the triangular network meets the construction standard; if the predicted value of the triangular network construction accuracy is less than the preset triangular network construction accuracy threshold, it is judged that the triangular network does not meet the construction standard and the photography is readjusted.

[0089] Please refer to Figure 5 , Figure 5 , which is the overall framework schematic diagram of a triangular network construction system based on oblique photography modeling provided by the embodiment of the present invention.

[0090] A triangular network construction system based on oblique photography modeling provided by the present invention is implemented based on the above-mentioned triangular network construction method based on oblique photography modeling, and includes: a data acquisition module for acquiring route flight data, ground control point data, point cloud data, and photographic equipment data;

[0091] An overlap degree influence evaluation module for evaluating the heading overlap degree and the side overlap degree based on the route flight data, and then evaluating the influence of the overlap degree on the triangular network construction accuracy based on the heading overlap degree and the side overlap degree;

[0092] A ground control point influence evaluation module for evaluating the influence of the distribution of ground control points on the triangular network construction accuracy based on the ground control point data;

[0093] A point cloud impact assessment module, configured to assess the impact of point cloud distribution on the accuracy of triangular network construction based on point cloud data;

[0094] A photographic equipment impact assessment module, configured to assess the impact of photographic equipment on the accuracy of triangular network construction based on photographic equipment data;

[0095] An accuracy prediction module, configured to predict the accuracy of triangular network construction based on the impact of overlap degree, ground control point distribution, point cloud distribution, and photographic equipment on the accuracy of triangular network construction;

[0096] A judgment module, configured to judge whether the triangular network meets the construction standard based on the predicted value of the accuracy of triangular network construction.

[0097] Please refer to Figure 6 , Figure 6 , which is a structural block diagram of a computer device provided by an embodiment of the present invention.

[0098] An electronic device according to an embodiment of the present invention, the electronic device includes: a memory and a processor, and a computer program is stored in the memory; when the computer program is executed by the processor, the processor is caused to execute a method for constructing a triangular network based on oblique photography modeling according to any one of the above embodiments, specifically including: collecting route flight data, assessing the heading overlap degree and side overlap degree based on the route flight data, and then assessing the impact of the overlap degree on the accuracy of triangular network construction based on the heading overlap degree and side overlap degree; collecting ground control point data, assessing the impact of ground control point distribution on the accuracy of triangular network construction based on the ground control point data; collecting point cloud data, assessing the impact of point cloud distribution on the accuracy of triangular network construction based on the point cloud data; collecting photographic equipment data, assessing the impact of photographic equipment on the accuracy of triangular network construction based on the photographic equipment data; predicting the accuracy of triangular network construction based on the impact of overlap degree, ground control point distribution, point cloud distribution, and photographic equipment on the accuracy of triangular network construction and judging whether the triangular network meets the construction standard.

[0099] The memory can be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read-only memory), an EPROM, a hard disk, or a ROM. The memory has a storage space for program code for executing any of the method steps in the above methods. For example, the storage space for program code can include respective program codes for implementing the various steps in the above methods. These program codes can be read from or written into one or more computer program products. These computer program products include program code carriers such as hard disks, compact discs (CDs), memory cards, or floppy disks. The program code can be compressed in an appropriate form, for example. When these codes are run by a computing processing device, they cause the computing processing device to execute the respective steps in the methods described above. These program codes can be read from or written into one or more computer program products. These computer program products include program code carriers such as hard disks, compact discs (CDs), memory cards, or floppy disks. The program code can be compressed in an appropriate form, for example. When these codes are run by a computing processing device, they cause the computing processing device to execute the respective steps in a method for constructing a triangular network based on oblique photography modeling described above.

[0100] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0101] In several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of devices or units can be in electrical, mechanical, or other forms.

[0102] The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0103] In addition, in each embodiment of the present invention, each functional unit may be integrated into a processing unit, may exist separately physically for each unit, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of a software functional unit.

[0104] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in each embodiment of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0105] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of each embodiment of the present invention.

Claims

1. A triangulated network construction method based on oblique photography modeling, characterized in that: The specific steps include: S1. Collect flight data, evaluate heading overlap and lateral overlap based on the flight data, and then evaluate the impact of overlap on the accuracy of triangulation based on heading overlap and lateral overlap. The impact of overlap on the accuracy of triangulation is obtained by the following formula: , where is the heading overlap, is the lateral overlap, is the standard value of heading overlap, is the standard value of lateral overlap; S2. Collect ground control point data and evaluate the influence of ground control point distribution on the accuracy of triangulation network construction based on the ground control point data. The influence of ground control point distribution on the accuracy of triangulation network construction is obtained by the following formula: , where is the coverage area, is the coordinate residual value, is the uniformity of coordinate distribution; S3. Collect point cloud data and evaluate the influence of point cloud distribution on the accuracy of triangulation construction based on the point cloud data. The influence of point cloud distribution on the accuracy of triangulation construction is obtained by the following formula: , where is the point cloud density, is the uniformity of point cloud distribution; S4. Collect the data of photographic equipment, and evaluate the influence of photographic equipment on the accuracy of triangulation construction based on the data of photographic equipment. The influence of photographic equipment on the accuracy of triangulation construction is obtained by the following formula: , where is the data collection time of the photographic equipment, is the vibration frequency at time t, is the vibration amplitude at time t, is the standard vibration frequency, is the standard vibration amplitude, is the time integral; S5. Estimate the accuracy of triangulation construction based on the overlap, distribution of ground control points, distribution of point clouds and the influence of photographic equipment on the accuracy of triangulation construction and determine whether the triangulation meets the construction standards.

2. A triangulated network construction method based on oblique photography modeling as claimed in claim 1, characterized in that: The S1 comprises the following specific steps: S11, collecting route flight data, wherein the route flight data includes the heading side length of the image frame, the lateral side length of the image frame, the length of the heading overlapping part, and the length of the lateral overlapping part; S12, evaluating the heading overlap based on the heading side length of the image frame and the length of the heading overlap portion; S13, evaluating the lateral overlap based on the lateral side length of the image frame and the length of the lateral overlap portion; S14. Evaluate the influence of the overlap on the accuracy of triangulation construction based on the heading overlap and the lateral overlap.

3. A triangulated network construction method based on oblique photography modeling as claimed in claim 2, characterized in that: The S2 comprises the following specific steps: S21, collecting ground control point data, wherein the ground control point data includes ground control point coordinates; S22, evaluating coordinate residual values, coverage area and coordinate distribution uniformity based on the coordinates of the ground control points; S23. Evaluate the impact of ground control point distribution on the accuracy of triangulation construction based on coordinate residual values, coverage area and coordinate distribution uniformity.

4. A triangulated network construction method based on oblique photography modeling as claimed in claim 3, characterized in that: The S3 comprises the following specific steps: S31, collecting point cloud data, wherein the point cloud data includes point cloud density and point cloud distribution uniformity; S32. Evaluate the impact of point cloud distribution on the accuracy of triangulation construction based on point cloud density and point cloud distribution uniformity.

5. A triangulated network construction method based on oblique photography modeling as claimed in claim 4, characterized in that: The S4 comprises the following specific steps: S41, collecting photographic equipment data, wherein the photographic equipment data includes vibration data, and the vibration data includes vibration amplitude and vibration frequency; S42. Evaluate the influence of the photographic equipment on the accuracy of triangulation construction based on the vibration amplitude and vibration frequency.

6. A triangulated network construction method based on oblique photography modeling as claimed in claim 5, characterized in that: The S5 comprises the following specific steps: S51, obtaining an estimated value of triangulation network construction accuracy based on the influence value of overlap on triangulation network construction accuracy, the influence value of ground control point distribution on triangulation network construction accuracy, the influence value of point cloud distribution on triangulation network construction accuracy, and the influence value of photographic equipment on triangulation network construction accuracy; S52. Determine whether the triangulated network meets the construction standards based on the triangulated network construction accuracy estimate and the preset triangulated network construction accuracy threshold. If the triangulated network construction accuracy estimate is greater than or equal to the preset triangulated network construction accuracy threshold, then the triangulated network is judged to meet the construction standards; if the triangulated network construction accuracy estimate is less than the preset triangulated network construction accuracy threshold, then the triangulated network is judged to not meet the construction standards and the photography is readjusted.

7. A triangulated network construction system based on oblique photography modeling, used to implement the triangulated network construction method based on oblique photography modeling as claimed in any one of claims 1 to 6, characterized in that: include: Data acquisition module, used to collect route flight data, ground control point data, point cloud data and photography equipment data; Overlap impact assessment module, used to assess heading overlap and lateral overlap based on route flight data, and then assess the impact of overlap on triangulation accuracy based on heading overlap and lateral overlap; The ground control point impact assessment module is used to assess the impact of ground control point distribution on the accuracy of triangulation construction based on ground control point data; Point cloud impact assessment module, used to assess the impact of point cloud distribution on the accuracy of triangulation construction based on point cloud data; Photographic equipment impact assessment module, used to assess the impact of photographic equipment on triangulation accuracy based on photographic equipment data; The accuracy estimation module is used to estimate the accuracy of triangulation based on the overlap, distribution of ground control points, distribution of point clouds and the influence of photographic equipment on the accuracy of triangulation; The judgment module is used to judge whether the triangulated network meets the construction standard based on the estimated value of the triangulated network construction accuracy.

8. An electronic device, characterized in that: It comprises a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the processor executes the steps of a triangulated network construction method based on oblique photography modeling as described in any one of claims 1 to 6.

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