Coordinate conversion method and device for video GIS

Abstract

The application relates to a coordinate conversion method for video GIS, comprising the following steps: acquiring geographical space coordinates of a target point and three-dimensional space coordinates of a camera; converting the geographical space coordinates into image space coordinates by using a Bursa seven-parameter conversion model; converting the image space coordinates into theoretical imaging plane coordinates by using a spherical center oblique axis projection azimuth calculation model; and converting the theoretical imaging plane coordinates into screen imaging plane coordinates according to model ratio parameters. The application also provides another coordinate conversion method for video GIS, which is a reverse process of the above coordinate conversion method. Through the technical scheme, efficient bidirectional fusion of video data and geographical information can be realized.

Description

Technical Field

[0001] This application generally relates to the field of video GIS technology, and more particularly to a coordinate transformation method and apparatus for video GIS. Background Technology

[0002] With the development of science and technology, video surveillance networks are increasingly being used in smart cities, natural resource monitoring, and public place security. Video surveillance networks offer advantages such as high definition, realism, and real-time performance, and are measurable; however, the information is primarily expressed in image space, making spatial analysis difficult. Although video data is ubiquitous in our lives, how to further utilize the spatiotemporal information within it remains a challenge. Video GIS integrates video data with GIS technology. It can fuse video surveillance images into a geographic scene, stitching together the spatiotemporal information of multiple surveillance feeds in geographic space. This provides a more intuitive understanding of the precise location of the video surveillance image in the real world and its relationship to the surrounding environment. Furthermore, it enables functions such as storage, processing, and analysis of spatial video.

[0003] Currently, intelligent video analytics primarily relies on the video itself, lacking effective integration with geospatial data. This makes it difficult to perceive the location, size, speed, and spatial topology of dynamic targets, and its ability to couple and analyze with the geographic environment is insufficient, leading to numerous challenges in dynamic target recognition, tracking, and behavior understanding. Therefore, there is an urgent need in this field for solutions that efficiently integrate video data with geographic information. Summary of the Invention

[0004] To address the aforementioned technical problems in the prior art, this application provides a coordinate transformation method and apparatus for video GIS, aiming to efficiently and bidirectionally integrate video data with geographic information.

[0005] According to a first aspect of this application, a coordinate transformation method for video GIS is provided, comprising: acquiring the geospatial coordinates of a target point and the three-dimensional spatial coordinates of a camera, wherein the geospatial coordinates include latitude, longitude, and elevation; converting the geospatial coordinates into image space coordinates using a Bursa-Taylor seven-parameter transformation model based on the geospatial coordinates of the target point and the three-dimensional spatial coordinates of the camera; converting the image space coordinates into theoretical imaging plane coordinates using a spherically centered oblique projection azimuth calculation model; and converting the theoretical imaging plane coordinates into screen imaging plane coordinates based on a model ratio parameter, wherein the model ratio parameter is an imaging scaling factor between the theoretical imaging plane and the screen imaging plane at different magnifications of the camera, wherein... , Here are the model ratio parameters for the camera at magnification n. R is the imaging distance at magnification n, and R is the theoretical imaging distance.

[0006] In one embodiment, converting the image space coordinates into theoretical imaging plane coordinates using the sphere-centered oblique projection azimuth calculation model includes: converting the image space coordinates into PT values, wherein the PT values ​​include a horizontal angle and a vertical angle; correcting the horizontal angle to obtain a corrected horizontal angle; obtaining the PTZ value of the center point of the camera in its current pose; and calculating the theoretical imaging plane coordinates using the sphere-centered oblique projection azimuth calculation model based on the PTZ value, the corrected horizontal angle, and the vertical angle.

[0007] In one embodiment, correcting the horizontal angle includes: acquiring multiple corresponding points of the target point; and correcting the horizontal angle according to the following formula. ,in n This indicates the number of points with the same name as the target point that have been collected. i Indicates the first i A point with the same name, express n The average calibration value of the horizontal angle at corresponding points is used as the corrected horizontal angle. Indicates the first i The angle between the line connecting the corresponding point to the camera coordinates and the north direction in the geospatial coordinate system. Indicates the first i The angle between the line connecting the corresponding point to the camera coordinates and the north direction in the image space coordinate system.

[0008] In one embodiment, the Bursa seven-parameter conversion model is calculated as follows: map point calibration and camera PT value calibration are performed respectively to obtain map point calibration values ​​and camera PT calibration values ​​of multiple corresponding points; the error between the map point calibration value and the camera PT calibration value of each corresponding point is calculated; in response to the error being less than a threshold, the corresponding point is regarded as a valid corresponding point; in response to the error being greater than or equal to the threshold, horizontal angle compensation is performed on the corresponding point to convert the corresponding point into a valid corresponding point; based on the valid corresponding points, the parameters of the Bursa seven-parameter conversion model are solved to obtain the Bursa seven-parameter conversion model.

[0009] In one embodiment, the model ratio parameter is calculated as follows: using an automatic image space sampling method, all integer positions of vertical angle and magnification in the image space of the camera are sampled to establish an image space sample library of the camera, wherein the sampling includes obtaining the screen coordinates and PTZ values ​​of the sampling points; based on the image space sample library, the theoretical imaging plane coordinates of each sampling point in the theoretical imaging plane coordinate system are calculated using the sphere-centered oblique axis projection azimuth calculation model; based on the PTZ value and the theoretical imaging plane coordinates of each sampling point, an initial model ratio parameter is calculated; based on the original model ratio parameter and the PTZ value of the center point of the camera in the current pose, the model ratio parameter in the current pose is obtained by interpolation.

[0010] According to a second aspect of this application, a coordinate transformation method for video GIS is provided, comprising: obtaining screen imaging plane coordinates of a target point; and converting the screen imaging plane coordinates of the target point into theoretical imaging plane coordinates according to a model ratio parameter, wherein the model ratio parameter is an imaging scaling factor between the theoretical imaging plane and the screen imaging plane at different magnifications of the camera. , Here are the model ratio parameters for the camera at magnification n. R is the imaging distance at magnification n, and R is the theoretical imaging distance. The theoretical imaging plane coordinates are converted into camera spatial coordinates using the sphere-centered oblique axis projection azimuth calculation model. The camera spatial coordinates are converted into geographic spatial coordinates using the Bursa seven-parameter transformation model.

[0011] In one embodiment, converting the theoretical imaging plane coordinates into camera spatial coordinates using a sphere-centered oblique axis projection azimuth calculation model includes: using the sphere-centered oblique axis projection azimuth calculation model to convert the theoretical imaging plane coordinates into PT values ​​in the camera image space, wherein the PT values ​​include horizontal angles and vertical angles; correcting the horizontal angles and converting the vertical angles and the corrected horizontal angles into spatial vectors; and calculating the camera spatial coordinates based on the spatial vectors.

[0012] In one embodiment, converting the camera spatial coordinates into geospatial coordinates using the Bursa-Bursa seven-parameter transformation model includes: calculating initial geospatial coordinates using the Bursa-Bursa seven-parameter transformation model based on the camera spatial coordinates, and decomposing the initial geospatial coordinates into direction vectors and translation vectors; calculating the collision between the geospatial coordinates of each point on the direction vector after compensation by the translation vector and the DEM data to obtain the geospatial coordinates, wherein the DEM data is digital elevation model data.

[0013] According to a third aspect of this application, a coordinate transformation apparatus for video GIS is provided, comprising a memory and a processor, wherein the memory stores computer-executable instructions, which, when executed by the processor, implement the coordinate transformation method for video GIS according to the first and / or second aspects of this application.

[0014] The technical solution of this application has the following beneficial technical effects:

[0015] In the technical solution of this application, a mutual conversion relationship between the screen plane coordinate system and the spatial geographic coordinate system of a surveillance camera with known spatial three-dimensional coordinates is established, realizing the mutual mapping between the screen plane coordinates and the spatial geographic coordinates, thereby achieving efficient two-way fusion of video data and geographic information. Attached Figure Description

[0016] The above and other objects, features, and advantages of exemplary embodiments of this application will become readily understood by reading the following detailed description with reference to the accompanying drawings. In the drawings, several embodiments of this application are illustrated by way of example and not limitation, and the same or corresponding reference numerals denote the same or corresponding parts, wherein:

[0017] Figure 1 This is a flowchart of a coordinate transformation method for video GIS according to an embodiment of this application;

[0018] Figure 2 This is a flowchart illustrating the mapping from a spatial geographic coordinate system to a screen planar coordinate system according to an embodiment of this application;

[0019] Figure 3 This is a schematic diagram illustrating the principle of the sphere center oblique axis projection orientation calculation model according to an embodiment of this application;

[0020] Figure 4 This is a schematic diagram illustrating the calculation of the model ratio parameters according to an embodiment of this application;

[0021] Figure 5 This is a flowchart of a coordinate transformation method for video GIS according to an embodiment of this application;

[0022] Figure 6 This is a flowchart illustrating the mapping from a screen planar coordinate system to a spatial geographic coordinate system according to an embodiment of this application.

[0023] Figure 7 This is a schematic diagram of the structure of a coordinate transformation device for video GIS according to an embodiment of this application. Detailed Implementation

[0024] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0025] It should be understood that when the terms "first," "second," etc., are used in the claims, description, and drawings of this application, they are only used to distinguish different objects and not to describe a specific order. The terms "comprising" and "including" used in the description and claims of this application indicate the presence of the described features, integrals, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or collections thereof.

[0026] According to a first aspect of this application, this application provides a coordinate transformation method for video GIS, used for mapping from a spatial geographic coordinate system to a screen planar coordinate system.

[0027] Figure 1 This is a flowchart of a coordinate transformation method for video GIS according to an embodiment of this application. Figure 2 This is a flowchart illustrating the mapping process from a spatial geographic coordinate system to a screen planar coordinate system according to an embodiment of this application. For example... Figure 1 As shown, the coordinate transformation method includes steps S101 to S104, which are explained in detail below.

[0028] S101, obtain the geospatial coordinates of the target point and the three-dimensional spatial coordinates of the camera.

[0029] Specifically, the geospatial coordinates include latitude, longitude, and elevation, and these geospatial and three-dimensional spatial coordinates can be obtained from a GIS database. Specifically, the geospatial coordinates of the target point can be represented by latitude, longitude, and elevation, while the camera's three-dimensional spatial coordinates include the camera's position and orientation in space.

[0030] S102, based on the geographic spatial coordinates of the target point and the three-dimensional spatial coordinates of the camera, the geographic spatial coordinates are converted into image spatial coordinates using the Bursa seven-parameter transformation model.

[0031] Specifically, the Bursa seven-parameter transformation model is used for coordinate transformation between two spatial three-dimensional coordinate systems. In this patent, it is used to transform an object from geographic spatial coordinates (i.e., the object's actual location) to image spatial coordinates (i.e., a coordinate system with the camera as the origin). By acquiring three or more corresponding points through the camera, the seven parameters in the spatial coordinate transformation model are obtained using the indirect adjustment method; this is the seven-parameter transformation model. The Bursa model for transformation between two coordinate systems is as follows:

[0032]

[0033] In the formula, TX, TY, and TZ are the translation parameters from coordinate system B to coordinate system A, and w x w y w z Let be the rotation parameter from coordinate system B to coordinate system A, and m be the scale parameter from coordinate system B to coordinate system A.

[0034] Typically, the Euler angle of rotation between two different coordinate systems is very small, therefore R3(w z ), R2(w y ), R1(w x All of these are approximated as identity matrices. The Bursa model can ultimately be simplified to...

[0035] .

[0036] The Bursa seven-parameter transformation model can be calculated as follows: Map point calibration and camera PT value calibration are performed separately to obtain map point calibration values ​​and camera PT calibration values ​​for multiple corresponding points; the error between the map point calibration value and the camera PT calibration value for each corresponding point is calculated; in response to the error being less than a threshold, the corresponding point is considered a valid corresponding point; in response to the error being greater than or equal to the threshold, horizontal angle compensation is performed on the corresponding point to convert it into a valid corresponding point; based on the valid corresponding points, the parameters of the Bursa seven-parameter transformation model are solved to obtain the Bursa seven-parameter transformation model.

[0037] This model uses seven parameters to describe the transformation relationship between different coordinate systems, including three translation parameters, three rotation parameters, and one scale factor parameter. These parameters can be used to transform coordinates from one coordinate system to another. These parameters can be calculated by collecting corresponding points, and a Bursa seven-parameter transformation model can be established based on these parameters. The Bursa seven-parameter transformation model is derived from Bursa's rule and the seven-parameter model. Bursa's rule states that in the same coordinate system, the difference between the coordinates of two points is equal to the algebraic sum of the differences between their coordinates in different coordinate systems.

[0038] Therefore, the Bursa seven-parameter transformation model combines Bursa's rule with the seven-parameter model, transforming coordinates in one coordinate system to another by solving for the seven parameters.

[0039] The seven parameters in the Bursa seven-parameter transformation model can be solved using the least squares method. The least squares method is a mathematical optimization technique that determines the parameters of the model by minimizing the sum of squared errors. In the Bursa seven-parameter transformation model, the error can be defined as the difference in coordinates of the same point in two coordinate systems.

[0040] The specific solution process can be divided into the following steps: Select a set of known control points, which have known coordinates in both coordinate systems; establish the transformation equation between the coordinate systems based on the seven-parameter model; substitute the coordinates of the known control points into the transformation equation to obtain the transformation relationship between the two coordinate systems; calculate the coordinate difference of each control point in the two coordinate systems and use it as the error; use the least squares method to determine the values ​​of the seven parameters by minimizing the sum of squares of the errors; apply the obtained seven parameters to other points to achieve the transformation between the coordinate systems.

[0041] Solving the Bursa seven-parameter transformation model requires the use of corresponding points. Corresponding points are points that have the same geographical location in both coordinate systems. The coordinates of these points are known in both coordinate systems and can be used as control points to solve the seven-parameter transformation model.

[0042] It is important to note that the selected corresponding points should be distributed throughout the entire area, and the more the better, in order to improve the conversion accuracy. The following factors need to be considered when selecting corresponding points: Quantity: The more corresponding points, the higher the conversion accuracy; Distribution: Corresponding points should be evenly distributed throughout the entire area to ensure global conversion accuracy; Stability: Corresponding points should be stable ground features, unaffected by changes, such as mountain peaks, buildings, etc.

[0043] In practical applications, the selection of corresponding points needs to be based on specific circumstances. The coordinates of corresponding points can be obtained through GPS measurements, topographic maps, and other methods.

[0044] In this application, to improve the accuracy of corresponding point acquisition and thus the precision of the conversion model, corresponding points are screened and horizontal angle compensation is performed on them. Horizontal angle compensation can be performed using the horizontal angle correction method described below, or using a known horizontal angle compensation method in the prior art; this application does not impose any particular limitation on this method.

[0045] S103, the image space coordinates are converted into theoretical imaging plane coordinates using the sphere-centered oblique axis projection orientation calculation model.

[0046] Specifically, the sphere-centered oblique axis azimuth projection calculation model is a calculation model used to calculate the plane coordinates of a point (spherical coordinates) on the sphere in the spherical spatial relationship, projected onto a plane tangent to the sphere by the center projection. Figure 3 This is a schematic diagram illustrating the principle of the sphere-centered oblique axis projection azimuth calculation model according to an embodiment of this application. In this application, the sphere-centered oblique axis projection calculation model is used to convert the camera's pt values ​​(horizontal and vertical azimuth angles) into planar coordinates in the theoretical imaging plane, specifically including the following steps:

[0047] 1) Convert the oblique axis azimuth projection of the sphere center to the normal axis azimuth projection of the sphere center; transform the pole P of the sphere to the new pole Q through geometric transformation, thereby establishing a new spherical coordinate system based on the new pole.

[0048]

[0049]

[0050] After transformation, the polar coordinates of A in the new polar coordinate system are (Z, Thus, the oblique azimuth projection in the original polar coordinate system can be transformed into the normal azimuth projection in the new polar coordinate system.

[0051] 2) Calculation of the orthogonal azimuth projection; (Z, ) is the polar coordinate of A obtained in (1) in the new polar coordinate system, R is the distance between the theoretical imaging surface and the camera, and (x,y) is the coordinate of the theoretical imaging surface.

[0052]

[0053]

[0054] In some embodiments, converting the image space coordinates into theoretical imaging plane coordinates using a sphere-centered oblique projection azimuth calculation model includes: converting the image space coordinates into PT values, wherein the PT values ​​include a horizontal angle and a vertical angle; correcting the horizontal angle to obtain a corrected horizontal angle; obtaining the PTZ value of the center point of the camera in its current pose; and calculating the theoretical imaging plane coordinates using the sphere-centered oblique projection azimuth calculation model based on the PTZ value, the corrected horizontal angle, and the vertical angle.

[0055] Specifically, the Bursa seven-parameter transformation model is suitable for cases where the rotation Euler angle is very small. However, due to installation reasons, the camera's initial north direction often deviates significantly from its true north direction. To ensure that the calculation conforms to the calculation conditions of the Bursa seven-parameter transformation model, the average calibration value of the horizontal angle obtained from the collected corresponding points is used to correct the horizontal angle of the camera.

[0056] ,in n This indicates the number of points with the same name as the target point that have been collected. i Indicates the first i A point with the same name, express n The average calibration value of the horizontal angle at corresponding points is used as the corrected horizontal angle. Indicates the first i The angle between the line connecting the corresponding point to the camera coordinates and the north direction in the geospatial coordinate system. Indicates the first i The angle between the line connecting the corresponding point to the camera coordinates and the north direction in the image space coordinate system.

[0057] S104, based on the model ratio parameters, convert the theoretical imaging plane coordinates into screen imaging plane coordinates.

[0058] Figure 4 This is a schematic diagram illustrating the calculation of the model ratio parameter according to an embodiment of this application. The model ratio parameter is the imaging scaling factor between the theoretical imaging plane and the screen imaging plane at different magnifications of the camera, wherein... , Here are the model ratio parameters for the camera at magnification n. R is the imaging distance at magnification n, and R is the theoretical imaging distance.

[0059] The model ratio parameter is used to convert between the theoretical imaging plane and the real imaging plane. After obtaining the coordinates (x, y) of the theoretical imaging plane using the above method, the coordinates of the real imaging plane are calculated using the model ratio parameter. ), ,in The model ratio parameter when the ratio is n.

[0060] The model ratio parameter can be calculated as follows: using an automatic sampling method of the camera image space, all integer positions of the vertical angle and magnification in the image space of the camera are sampled to establish an image space sample library of the camera, wherein the sampling includes obtaining the screen coordinates and PTZ values ​​of the sampling points; based on the image space sample library, the theoretical imaging plane coordinates of each sampling point in the theoretical imaging plane coordinate system are calculated using the sphere-centered oblique axis projection azimuth calculation model; based on the PTZ value and the theoretical imaging plane coordinates of each sampling point, the initial model ratio parameter is calculated; based on the original model ratio parameter and the PTZ value of the center point of the camera in the current posture, the model ratio parameter in the current posture is obtained by interpolation.

[0061] Specifically, firstly, the camera needs to sample all integer positions of vertical angle and magnification in its image space, and then build an image space sample library for the camera. This process includes obtaining the screen coordinates and PTZ values ​​(i.e., the camera's horizontal angle, pitch angle, and focal length) of the sampling points for subsequent calculations.

[0062] Next, based on the image space sample library, the sphere-centered oblique projection azimuth calculation model is used to calculate the theoretical imaging plane coordinates of each sampling point in the theoretical imaging plane coordinate system. This process can be achieved by calculating the three-dimensional coordinates of the sampling point in the sphere-centered oblique projection azimuth and then projecting them onto the theoretical imaging plane.

[0063] Then, based on the PTZ value of each sampling point and the coordinates of the theoretical imaging plane, the initial model ratio parameter is calculated. This ratio parameter can be used to convert the coordinates in image space to the coordinates in the theoretical imaging plane.

[0064] Finally, based on the original model ratio parameters and the PTZ value of the camera's center point in the current pose, the model ratio parameters in the current pose are obtained through interpolation. This process can be achieved by interpolating the data at sampling points around the original model ratio parameters.

[0065] This completes the conversion from the spatial geographic coordinate system to the planar screen coordinate system.

[0066] According to a second aspect of this application, this application provides a coordinate transformation method for video GIS, used for mapping from a screen planar coordinate system to a spatial geographic coordinate system. The mapping process in this method is the reverse of the mapping process in the first aspect of this application; the same technical details will not be repeated here, but refer to the above-described forward mapping process.

[0067] Figure 5 This is a flowchart of a coordinate transformation method for video GIS according to an embodiment of this application. Figure 6 This is a flowchart illustrating the mapping process from a screen planar coordinate system to a spatial geographic coordinate system according to an embodiment of this application. For example... Figure 5 As shown, the coordinate transformation method includes steps S501 to S504, which are described in detail below.

[0068] S501, obtain the screen imaging plane coordinates of the target point.

[0069] Specifically, the target point is, for example, a point on a monitoring screen.

[0070] S502, based on the model ratio parameters, convert the screen imaging plane coordinates of the target point into theoretical imaging plane coordinates.

[0071] The model ratio parameter is defined the same as above, and is the imaging ratio factor between the theoretical imaging plane and the screen imaging plane at different magnifications of the camera. , Here are the model ratio parameters for the camera at magnification n. R is the imaging distance at magnification n, and R is the theoretical imaging distance.

[0072] S503 uses the sphere-centered oblique axis projection orientation calculation model to convert the theoretical imaging plane coordinates into camera spatial coordinates.

[0073] Specifically, using the sphere-centered oblique axis projection azimuth calculation model, the theoretical imaging plane coordinates are converted into PT values ​​in the camera image space, wherein the PT values ​​include horizontal and vertical angles; the horizontal angle is corrected, and the vertical angle and the corrected horizontal angle are converted into spatial vectors; the camera spatial coordinates are calculated based on the spatial vectors.

[0074] First, using a sphere-centered oblique projection azimuth calculation model, the theoretical imaging plane coordinates are converted into PT values ​​in the camera's image space. Here, PT values ​​refer to the horizontal and vertical angles, which describe the camera's orientation in space.

[0075] Next, the horizontal angle needs to be corrected because, in reality, the camera may have some deviations and requires calibration. Then, the corrected horizontal and vertical angles are converted into spatial vectors, which can describe the camera's position and orientation in space.

[0076] Finally, based on the spatial vectors, the camera's coordinates in space can be calculated. This process can be performed using methods such as triangulation.

[0077] S504 uses the Bursa seven-parameter transformation model to convert the camera spatial coordinates into geospatial coordinates.

[0078] Specifically, based on the spatial coordinates of the camera, the initial geospatial coordinates are calculated using the Bursa seven-parameter transformation model, and the initial geospatial coordinates are decomposed into direction vectors and translation vectors; the collision between the geospatial coordinates of each point on the direction vector after compensation by the translation vector and the DEM data is calculated to obtain the geospatial coordinates, wherein the DEM data is digital elevation model data.

[0079] The direction vector v(x) in the geospatial coordinate system is obtained using a seven-parameter transformation model. v ,y v ,z v ), and translation vector h(x) h ,y h ,z hAfter that, the camera captures the coordinates of any point on the light path as (x...). L ,y L ,z L )=(x v ,y v ,z v )*L+(x h ,y h ,z h ), where L is the distance between any point on the ray and the camera; dem is the digital elevation model data, representing the horizontal coordinate x of any point on the ray. L ,y L Substituting the values ​​into the dem parameter yields the ground elevation value z at that horizontal position. d When z d <z L The time ray is located above dem, when z d >z L The time indicates that the light has passed through the DEM, that is, it has collided with the DEM.

[0080] This completes the conversion from a planar screen coordinate system to a spatial geographic coordinate system.

[0081] The technical principles and implementation details of the coordinate transformation method for video GIS of this application have been described above through specific embodiments. It should be noted that the two methods described in the first and second aspects of this application are mappings in opposite directions, and can be implemented individually or in combination; this application does not limit this. Through the technical solution of this application, a mutual transformation relationship is established between the screen plane coordinate system and the spatial geographic coordinate system of a surveillance camera with known spatial three-dimensional coordinates, realizing the mutual mapping between screen plane coordinates and spatial geographic coordinates, thereby achieving efficient bidirectional fusion of video data and geographic information.

[0082] According to a third aspect of this application, this application also provides a coordinate transformation device for video GIS.

[0083] Figure 7 This is a schematic diagram of the structure of a coordinate transformation device 70 for video GIS according to an embodiment of this application. The device includes a processor and a memory. The memory stores computer program instructions, which, when executed by the processor, implement the coordinate transformation method for video GIS according to the first and / or second aspects of this application. The device also includes other components well known to those skilled in the art, such as a communication bus and a communication interface. The settings and functions of these components are known in the art and will not be described further here.

[0084] In this application, the aforementioned memory can be any tangible medium containing or storing a program that can be used or combined with an instruction execution system, apparatus, or device. For example, a computer-readable storage medium can be any suitable magnetic or magneto-optical storage medium, such as Resistive Random Access Memory (RRAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), Enhanced Dynamic Random Access Memory (EDRAM), High-Bandwidth Memory (HBM), Hybrid Memory Cube (HMC), etc., or any other medium that can be used to store desired information and can be accessed by an application, module, or both. Any such computer storage medium can be part of a device or accessible to or connected to a device. Any application or module described in this application can be implemented using computer-readable / executable instructions that can be stored or otherwise retained by such a computer-readable medium.

[0085] Based on the above description in this specification, those skilled in the art will also understand that the terms used, such as "upper" and "lower," which indicate orientation or positional relationship, are based on the orientation or positional relationship shown in the accompanying drawings of this specification. They are only for the purpose of facilitating the explanation of the present application and simplifying the description, and do not imply that the device or element involved must have the specific orientation, or be constructed and operated in a specific orientation. Therefore, the above-mentioned orientation or positional relationship terms should not be understood or interpreted as a limitation on the present application.

[0086] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0087] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A coordinate transformation method for video GIS, characterized in that, include: Obtain the geospatial coordinates of the target point and the three-dimensional spatial coordinates of the camera, wherein the geospatial coordinates include latitude, longitude and elevation; Based on the geospatial coordinates of the target point and the three-dimensional spatial coordinates of the camera, the geospatial coordinates are converted into image spatial coordinates using the Bursa seven-parameter transformation model; Using the sphere-centered oblique axis projection azimuth calculation model, the image space coordinates are converted into theoretical imaging plane coordinates; the image space coordinates are converted into PT values, the PT values ​​including horizontal and vertical angles; the horizontal angle is corrected to obtain a corrected horizontal angle; the PTZ value of the center point of the camera in the current pose is obtained; based on the PTZ value, the corrected horizontal angle, and the vertical angle, the theoretical imaging plane coordinates are calculated using the sphere-centered oblique axis projection azimuth calculation model. Based on the model ratio parameter, the theoretical imaging plane coordinates are converted into screen imaging plane coordinates, wherein the model ratio parameter is an imaging scaling factor between the theoretical imaging plane and the screen imaging plane at different magnifications of the camera. , Here are the model ratio parameters for the camera at magnification n. R is the imaging distance at magnification n, and R is the theoretical imaging distance.

2. The coordinate transformation method for video GIS according to claim 1, characterized in that, The correction of the horizontal angle includes: Collect multiple points with the same name as the target point; The horizontal angle is corrected according to the following formula. ,in N This indicates the number of points with the same name as the target point that have been collected. i Indicates the first i A point with the same name, express N The average calibration value of the horizontal angle at corresponding points is used as the corrected horizontal angle. Indicates the first i The angle between the line connecting the corresponding point to the camera coordinates and the north direction in the geospatial coordinate system. Indicates the first i The angle between the line connecting the corresponding point to the camera coordinates and the north direction in the image space coordinate system.

3. The coordinate transformation method for video GIS according to claim 2, characterized in that, The Bursa seven-parameter transformation model is calculated in the following way: Map point calibration and camera PT value calibration are performed separately to obtain map point calibration values ​​and camera PT calibration values ​​for multiple points with the same name; Calculate the error between the map location calibration value and the camera PT calibration value for each point with the same name; In response to the error being less than a threshold, the corresponding point is considered a valid corresponding point; In response to the error being greater than or equal to the threshold, horizontal angle compensation is performed on the corresponding points to convert the corresponding points into valid corresponding points; Based on the effective corresponding points, the parameters of the Bursa seven-parameter transformation model are solved to obtain the Bursa seven-parameter transformation model.

4. The coordinate transformation method for video GIS according to claim 3, characterized in that, The model ratio parameters are calculated in the following way: Using an automatic sampling method for camera image space, all integer positions of vertical angle and magnification in the image space of the camera are sampled to establish an image space sample library of the camera, wherein the sampling includes obtaining the screen coordinates and PTZ value of the sampling points; Based on the image space sample library, the theoretical imaging plane coordinates of each sampling point in the theoretical imaging plane coordinate system are calculated using the sphere-centered oblique axis projection orientation calculation model. The original model ratio parameter is calculated based on the PTZ value and the theoretical imaging plane coordinates of each sampling point; Based on the original model ratio parameters and the PTZ value of the center point of the camera in the current pose, the model ratio parameters in the current pose are obtained by interpolation.

5. A coordinate transformation method for video GIS, characterized in that, include: Obtain the screen imaging plane coordinates of the target point; Based on the model ratio parameter, the screen imaging plane coordinates of the target point are converted into theoretical imaging plane coordinates, wherein the model ratio parameter is the imaging scaling factor between the theoretical imaging plane and the screen imaging plane at different magnifications of the camera. , Here are the model ratio parameters for the camera at magnification n. Let R be the imaging distance at magnification n, and R be the theoretical imaging distance. The theoretical imaging plane coordinates are converted into image space coordinates using the sphere-centered oblique axis projection azimuth calculation model. The image spatial coordinates are converted into geospatial coordinates using the Bursa seven-parameter transformation model. The method of using the sphere-centered oblique axis projection azimuth calculation model to convert the theoretical imaging plane coordinates into image space coordinates includes: Using the sphere-centered oblique axis projection azimuth calculation model, the theoretical imaging plane coordinates are converted into PT values ​​in the camera image space, wherein the PT values ​​include horizontal and vertical angles; The horizontal angle is corrected, and the vertical angle and the corrected horizontal angle are converted into spatial vectors; Calculate the image space coordinates based on the spatial vector.

6. The coordinate transformation method for video GIS according to claim 5, characterized in that, The process of converting the image space coordinates to geospatial coordinates using the Bursa seven-parameter transformation model includes: Based on the image space coordinates, the initial geospatial coordinates are calculated using the Bursa seven-parameter transformation model, and the initial geospatial coordinates are decomposed into direction vectors and translation vectors; The collision between the geospatial coordinates of each point on the direction vector after compensation by the translation vector and the DEM data is calculated to obtain the geospatial coordinates, wherein the DEM data is digital elevation model data.

7. A coordinate transformation device for video GIS, comprising a memory and a processor, wherein the memory stores computer-executable instructions, characterized in that, When executed by the processor, the computer-executable instructions implement the coordinate transformation method for video GIS according to any one of claims 1 to 4, and the coordinate transformation method for video GIS according to claim 5 or 6.

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