Rapid calibration method and system for visual positioning camera and related equipment

Abstract

The invention relates to the technical field of computer vision, and discloses a rapid calibration method and system for a visual positioning camera and related equipment, and the method comprises the steps: obtaining an image of a target region; acquiring a pixel coordinate value corresponding to each calibration point position in the image; acquiring the latitude and longitude and the elevation value corresponding to each calibration point in the image; wherein the calibration point position is a vertex of a marker in a target area; controlling the camera to perform rotary shooting in the target area according to a preset attitude, and recording an attitude value of the camera during shooting; and determining external parameters of the camera based on the pixel coordinate value, the longitude and latitude, the elevation value and the attitude value so as to realize rapid calibration of the external parameters of the camera. The external parameter calibration of the camera is quickly realized through the pixel coordinate value, the latitude and longitude and the elevation value of the calibration point position in the image and the attitude value of the camera during shooting, the efficiency is high, and the method is suitable for cameras of any model and high in applicability.

Description

Technical Field

[0001] This disclosure relates to the field of computer vision technology, and in particular to a rapid calibration method, system and related equipment for a visual positioning camera. Background Technology

[0002] In many key application areas such as intelligent security monitoring, industrial automation inspection, intelligent traffic management, and unmanned system navigation, PTZ (Pan-Tilt-Zoom) cameras have become an indispensable core visual perception infrastructure due to their flexible, wide-range field-of-view coverage and high-resolution capture of local details. The core value of these cameras lies in their ability to dynamically adjust the viewing angle and focal length, enabling continuous tracking of moving targets or detailed observation of specific areas or targets.

[0003] To achieve advanced functions such as precise target localization, 3D measurement, or multi-camera collaboration, obtaining accurate extrinsic parameters of the PTZ camera is crucial. Extrinsic parameters, which determine the camera's position (X, Y, Z) and attitude angles in 3D space, are fundamental to mapping the pixel coordinates of the 2D images captured by the camera to coordinates in the real 3D world.

[0004] Currently, the industry's commonly used methods for calibrating the external parameters of PTZ cameras mainly rely on manually set calibration control points, such as easily identifiable special markers like calibration boards with specific geometric patterns. These calibration methods suffer from problems such as high deployment costs, poor adaptability, and limited flexibility. Summary of the Invention

[0005] To overcome the problems of high deployment cost, poor adaptability and limited flexibility of manual calibration methods, this disclosure provides a rapid calibration method, system and related equipment for visual positioning cameras.

[0006] Firstly, in order to solve the aforementioned technical problems, this disclosure provides a rapid calibration method for a visual positioning camera, comprising: Acquire images of the target area; wherein, the images are taken by the drone in the target area according to preset aerial photography parameters; Obtain the pixel coordinates of each calibration point in the image; the pixel coordinates are determined by constructing a coordinate system with the top left corner of the image as the origin; Obtain the latitude, longitude, and elevation values ​​corresponding to each calibration point in the image; where the calibration point is the vertex of the landmark in the target area; Control the camera to rotate and shoot in the target area according to a preset posture, and record the posture value of the camera when shooting; Based on pixel coordinates, latitude and longitude, elevation and attitude values, the camera's external parameters are determined to enable rapid calibration of the camera's external parameters.

[0007] Furthermore, the latitude, longitude, and elevation values ​​corresponding to each calibration point in the image are obtained, including: Based on the image, an orthophoto is generated using Pix4D software; Obtain the latitude and longitude corresponding to each calibration point from the orthophoto image; Digital elevation models are generated based on images using Pix4D software. Obtain the elevation values ​​corresponding to each calibration point from the digital elevation model.

[0008] Furthermore, the preset aerial photography parameters include: The drone was set to a flight altitude of 80m, a heading overlap rate of 85%, and a directional overlap rate of 80%.

[0009] Furthermore, based on pixel coordinates, latitude and longitude, elevation, and attitude values, the camera's external parameters are determined, including: Based on the transformation relationship between the camera coordinate system and the geodetic coordinate system, the transformed pixel coordinates of each calibration point in the image are obtained from the camera coordinate system to the geodetic coordinate system; Calculate the Euclidean distance between the pixel coordinates and the transformed pixel coordinates for each calibration point; Minimize the Euclidean distance to determine the target Euclidean distance; The camera's external parameters are determined based on the target's Euclidean distance, latitude and longitude, elevation, and attitude.

[0010] Furthermore, based on the target Euclidean distance, latitude and longitude, elevation value, and attitude value, the camera's external parameters are determined, including: Based on the target Euclidean distance, the latitude, longitude and elevation values ​​are transformed into three-dimensional space to determine the translation vector; whereby the translation vector is used to characterize the amount of camera translation when tracking the target; Based on the target Euclidean distance, the attitude values ​​are transformed into three-dimensional space to determine the rotation matrix; whereby the rotation matrix is ​​used to characterize the lens orientation when tracking the target.

[0011] Furthermore, the number of each calibration point in the image is greater than the preset number.

[0012] Secondly, this disclosure provides a rapid calibration system for a visual positioning camera, comprising: The image acquisition module is used to acquire images of the target area; wherein, the images are taken in the target area according to preset aerial photography parameters; The first data acquisition module is used to acquire the pixel coordinate values ​​corresponding to each calibration point in the image; wherein, the pixel coordinate values ​​are determined by constructing a coordinate system with the top left corner of the image as the origin; The second data acquisition module is used to acquire the latitude, longitude, and elevation values ​​corresponding to each calibration point in the image; wherein, the calibration point is the vertex of the landmark in the target area; The third data acquisition module is used to control the camera to rotate and shoot in the target area according to a preset posture, and to record the posture value of the camera when shooting. The calibration module is used to determine the camera's external parameters based on pixel coordinates, latitude and longitude, elevation and attitude values, so as to achieve rapid calibration of the camera's external parameters.

[0013] Thirdly, this disclosure provides a computing device, including a memory, a processor, and a program stored in the memory and running on the processor, wherein the processor executes the program to implement a rapid calibration method for a visual positioning camera as described above.

[0014] Fourthly, this disclosure provides a computer-readable storage medium storing instructions that, when executed on a terminal device, cause the terminal device to perform a rapid calibration method for a visual positioning camera as described above.

[0015] The beneficial effects of this disclosure are: by using a drone to capture images of a target area according to preset aerial photography parameters, and obtaining the latitude, longitude, and elevation values ​​corresponding to each calibration point from the images, the camera is controlled to rotate and capture images in the target area according to a preset attitude, and the attitude values ​​are recorded. Finally, the external parameters of the camera are quickly calibrated using the latitude, longitude, elevation values, and attitude values. This disclosure achieves rapid calibration of the camera's external parameters by using the pixel coordinates, latitude, longitude, and elevation values ​​of the calibration points in the image, as well as the attitude values ​​during shooting. It is highly efficient, applicable to any type of camera, and has strong applicability. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the present disclosure will be further described below in conjunction with the accompanying drawings and embodiments.

[0017] Figure 1 This is a flowchart illustrating a rapid calibration method for a visual positioning camera according to an embodiment of the present disclosure. Figure 2 A schematic diagram showing the association between the calibration points in the surveillance footage and the drone footage; Figure 3 Schematic diagram of UAV flight control point planning; Figure 4 This is a schematic diagram of the structure of a rapid calibration system for a visual positioning camera according to an embodiment of the present disclosure; Figure 5 This is a schematic diagram of the structure of a computing device according to an embodiment of the present disclosure. Detailed Implementation

[0018] The following embodiments are further explanations and supplements to this disclosure and do not constitute any limitation on this disclosure.

[0019] The following describes a rapid calibration method, system, and related equipment for a visual positioning camera according to embodiments of the present disclosure, in conjunction with the accompanying drawings.

[0020] like Figure 1 As shown, this disclosure provides a rapid calibration method for a visual positioning camera, including: S1. Acquire images of the target area; wherein, the images are images taken by the UAV in the target area according to preset aerial photography parameters.

[0021] S2. Obtain the pixel coordinate values ​​corresponding to each calibration point in the image; wherein, the pixel coordinate values ​​are determined by constructing a coordinate system with the top left corner of the image as the origin; S2. Obtain the latitude, longitude, and elevation values ​​corresponding to each calibration point in the image; where the calibration point is the vertex of the landmark in the target area.

[0022] S3. Control the camera to rotate and shoot in the target area according to the preset posture, and record the posture value of the camera when shooting.

[0023] S4. Based on pixel coordinates, latitude and longitude, elevation and attitude values, determine the camera's external parameters to achieve rapid calibration of the camera's external parameters.

[0024] In this embodiment, an unmanned aerial vehicle (UAV) captures images of the target area according to preset aerial photography parameters. The latitude, longitude, and elevation values ​​corresponding to each calibration point are obtained from the images. The camera is then controlled to rotate and capture images within the target area according to a preset attitude, and the attitude values ​​are recorded. Finally, the camera's external parameters are quickly calibrated using the latitude, longitude, elevation, and attitude values. This disclosure achieves rapid calibration of the camera's external parameters by using the pixel coordinates, latitude, longitude, and elevation values ​​of the calibration points in the image, as well as the attitude values ​​during shooting. It is highly efficient, applicable to any type of camera, and has strong applicability.

[0025] In this embodiment, the target area covers key areas in the monitoring scene, such as roads and building entrances. The calibration points are the vertices of prominent landmarks in the key areas, such as zebra crossing vertices, guardrail vertices, and ground landmark vertices. For example, Figure 2 The attached image on the left shows the entrance to the residential area as captured by surveillance cameras. The points that can be used as markers are the vertex 1 of the no-parking line, the vertex 2 of the turning arrow, and the two vertices 3 and 4 of the straight arrow. When captured by a drone, the orthographic view is as follows. Figure 2As shown in the attached diagram on the right.

[0026] In this embodiment, the attitude value refers to PTZ information, specifically including: Pan (Horizontal Rotation): The gimbal drives the camera to rotate horizontally (left and right), covering 360° (some models support continuous rotation) or a specific angle range, expanding the horizontal field of view.

[0027] Tilt (vertical tilt): The gimbal drives the camera to move vertically (up and down), adjusting the tilt angle (e.g., -90° to +90°) to cover the vertical space (e.g., from the ground to the sky).

[0028] Zoom: Adjusting the lens focal length optically or digitally to "zoom in" or "zoom out" the image.

[0029] For example, as shown in Table 1 below, these are five images captured by the camera when it rotates and shoots in a preset posture in the target area. The PTZ information for each image is as follows: Table 1 Optionally, the latitude, longitude, and elevation values ​​corresponding to each calibration point in the image are obtained, including: Based on the image, an orthophoto is generated using Pix4D software; Obtain the latitude and longitude corresponding to each calibration point from the orthophoto image; Digital elevation models are generated based on images using Pix4D software. Obtain the elevation values ​​corresponding to each calibration point from the digital elevation model.

[0030] In this embodiment, the Pix4D software integrates photogrammetry and computer vision algorithms to transform two-dimensional image / point cloud data collected by UAVs, SLR cameras, or LiDAR into geospatial data such as digital orthophoto maps (DOM) and digital elevation models (DEM), which are widely used in surveying, agriculture, construction, disaster monitoring and other fields.

[0031] In this embodiment, the orthophoto map and digital elevation model are imported into the GIS map software, and the latitude, longitude and elevation values ​​of the corresponding calibration points can be directly exported.

[0032] Optionally, preset aerial photography parameters include: The drone was set to a flight altitude of 80m, a heading overlap rate of 85%, and a directional overlap rate of 80%.

[0033] In this embodiment, during aerial photography, the drone equipped with a camera needs to fly along a preset path within the target area and collect images, such as... Figure 3 As shown, the lines and arrows indicate the flight path of the drone, and each dot represents one shot. To ensure the integrity and continuity of the images, the drone collects a sequence of images with an overlap rate of ≥80% during shooting, and then analyzes them to obtain the images.

[0034] Optionally, based on pixel coordinates, latitude and longitude, elevation, and attitude values, the camera's external parameters are determined, including: Based on the transformation relationship between the camera coordinate system and the geodetic coordinate system, the transformed pixel coordinates of each calibration point in the image are obtained from the camera coordinate system to the geodetic coordinate system; Calculate the Euclidean distance between the pixel coordinates and the transformed pixel coordinates for each calibration point; Minimize the Euclidean distance to determine the target Euclidean distance; The camera's external parameters are determined based on the target's Euclidean distance, latitude and longitude, elevation, and attitude.

[0035] In this embodiment, by transforming the camera coordinates and the geodetic coordinate system, the latitude, longitude, elevation, and attitude values ​​in two-dimensional space can be converted into three-dimensional space, thereby quickly calibrating the external parameters of the camera. Evaluation shows that the positioning accuracy is significantly improved, and the accuracy of the camera in tracking targets is significantly enhanced.

[0036] This embodiment provides examples of the latitude, longitude, elevation, and original pixel coordinates in the camera coordinate system corresponding to each calibration point, as shown in Table 2: Table 2 Optionally, based on the calibration point pixel coordinates, latitude and longitude, elevation values, and attitude values, the camera's external parameters are determined, including: Based on the target Euclidean distance, the latitude, longitude and elevation values ​​are transformed into three-dimensional space to determine the translation vector; whereby the translation vector is used to characterize the amount of camera translation when tracking the target; Based on the target Euclidean distance, the attitude values ​​are transformed into three-dimensional space to determine the rotation matrix; whereby the rotation matrix is ​​used to characterize the lens orientation when tracking the target.

[0037] For example: The latitude, longitude, and elevation values ​​of the calibration points are transformed to obtain the translation vector; where the translation vector represents the coordinate value of the target point in the camera coordinate system; based on the attitude value of the camera when shooting the target, it is transformed into three-dimensional space to determine the rotation matrix; where the rotation matrix is ​​used to characterize the lens orientation when tracking the target.

[0038] Based on translation vectors and rotation matrices, the latitude, longitude, and elevation coordinates of the target point are converted into pixel coordinates, and the Euclidean distance between these values ​​and the actual pixel values ​​of the target point in the image is calculated. This process is repeated for multiple selected target points, iteratively fitting the minimum Euclidean distance.

[0039] In this embodiment, the attitude value reflects the orientation of the camera when tracking the target in two-dimensional space. By using the camera's initial attitude and converting it to three-dimensional space, we can obtain the camera's orientation when tracking the target in the real world (three-dimensional space).

[0040] In this embodiment, the latitude, longitude, and elevation values ​​reflect the positions of the calibration points captured by the camera in the two-dimensional space of the image. By using coordinate transformation relationships to convert the latitude, longitude, and elevation values ​​into three-dimensional space, the position information of each calibration point in the camera coordinate system can be obtained, thereby determining the translation amount of the target position when tracking the target.

[0041] Optionally, the number of each calibration point in the image is greater than a preset number.

[0042] In this embodiment, the preset quantity is set according to the actual situation. Preferably, the preset quantity in this embodiment is 20.

[0043] like Figure 4 As shown, this disclosure provides a rapid calibration system for a visual positioning camera, including: The image acquisition module is used to acquire images of the target area; wherein, the images are taken in the target area according to preset aerial photography parameters; The first data acquisition module is used to acquire the pixel coordinate values ​​corresponding to each calibration point in the image; wherein, the pixel coordinate values ​​are determined by constructing a coordinate system with the top left corner of the image as the origin; The second data acquisition module is used to acquire the latitude, longitude, and elevation values ​​corresponding to each calibration point in the image; wherein, the calibration point is the vertex of the landmark in the target area; The third data acquisition module is used to control the camera to rotate and shoot in the target area according to a preset posture, and to record the posture value of the camera when shooting. The calibration module is used to determine the camera's external parameters based on pixel coordinates, latitude and longitude, elevation and attitude values, so as to achieve rapid calibration of the camera's external parameters.

[0044] Optionally, the second data acquisition module is specifically used for: Based on the image, an orthophoto is generated using Pix4D software; Obtain the latitude and longitude corresponding to each calibration point from the orthophoto image; Digital elevation models are generated based on images using Pix4D software. Obtain the elevation values ​​corresponding to each calibration point from the digital elevation model.

[0045] Optionally, the calibration module is specifically used for: Based on the transformation relationship between the camera coordinate system and the geodetic coordinate system, the transformed pixel coordinates of each calibration point in the image are obtained from the camera coordinate system to the geodetic coordinate system; Calculate the Euclidean distance between the pixel coordinates and the transformed pixel coordinates for each calibration point; Minimize the Euclidean distance to determine the target Euclidean distance; The camera's external parameters are determined based on the target's Euclidean distance, latitude and longitude, elevation, and attitude.

[0046] Optionally, the calibration module is specifically used for: Based on the target Euclidean distance, the latitude, longitude and elevation values ​​are transformed into three-dimensional space to determine the translation vector; whereby the translation vector is used to characterize the amount of camera translation when tracking the target; Based on the target Euclidean distance, the attitude values ​​are transformed into three-dimensional space to determine the rotation matrix; whereby the rotation matrix is ​​used to characterize the lens orientation when tracking the target.

[0047] A computing device according to an embodiment of this disclosure includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the aforementioned fast calibration method for a visual positioning camera. That is, a computing device according to an embodiment of this disclosure may include, but is not limited to: a processor and a memory; the memory is used to store the computer program; the processor is used to execute the fast calibration method for a visual positioning camera shown in any embodiment of this disclosure by calling the computer program.

[0048] In one alternative embodiment, a computing device is provided, such as Figure 5 As shown, Figure 5 The computing device 4000 shown includes a processor 4001 and a memory 4003. The processor 4001 and the memory 4003 are connected, for example, via a bus 4002. Optionally, the computing device 4000 may further include a transceiver 4004, which can be used for data interaction between the computing device and other computing devices, such as sending and / or receiving data. It should be noted that in practical applications, the transceiver 4004 is not limited to one type, and the structure of this computing device 4000 does not constitute a limitation on the embodiments of this disclosure.

[0049] Processor 4001 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with this disclosure. Processor 4001 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0050] Bus 4002 may include a path for transmitting information between the aforementioned components. Bus 4002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 4002 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 5 The bus 4002 is represented by only one thick line, but this does not mean that there is only one bus or one type of bus.

[0051] The memory 4003 may be ROM (Read Only Memory) or other types of static storage devices capable of storing static information and instructions, RAM (Random Access Memory) or other types of dynamic storage devices capable of storing information and instructions, or EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0052] The memory 4003 stores application code (computer program) that executes the present invention, and its execution is controlled by the processor 4001. The processor 4001 executes the application code stored in the memory 4003 to implement the content shown in the foregoing method embodiments.

[0053] The computing device can also be a terminal device, which can be any device that can install applications, including at least one of smartphones, tablets, laptops, desktop computers, smart speakers, smartwatches, smart TVs, and smart in-vehicle devices.

[0054] It should be noted that, Figure 5 The computing device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0055] This disclosure provides an embodiment of a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the aforementioned rapid calibration method for a visual positioning camera.

[0056] Alternatively, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), magnetic tape, a floppy disk, and an optical data storage device, etc.

[0057] In an exemplary embodiment, a computer program product or computer program is also provided, which includes computer instructions stored in a computer-readable storage medium. A processor of a computing device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computing device to perform the aforementioned rapid calibration method for a visual positioning camera.

[0058] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0059] It should be understood that the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of methods and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0060] The computer-readable storage medium provided in this disclosure can be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EEPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0061] The computer-readable storage medium described above carries one or more programs, which, when executed by the computing device, cause the computing device to perform the method shown in the above embodiments.

[0062] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

[0063] It should be noted that the terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and represent a limitation on a specific order or sequence. Where appropriate, the order of use for similar objects can be interchanged so that the embodiments of this application described herein can be implemented in an order other than that shown or described.

[0064] Those skilled in the art will recognize that this disclosure can be implemented as a system, method, or computer program product. Therefore, this disclosure can be implemented in the following forms: it can be entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, generally referred to herein as a "circuit," "module," or "system." Furthermore, in some embodiments, this disclosure can also be implemented as a computer program product contained in one or more computer-readable media, which includes computer-readable program code.

[0065] Although embodiments of the present disclosure have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present disclosure. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present disclosure.

Claims

1. A rapid calibration method for a visual positioning camera, characterized in that, include: Acquire an image of the target area; wherein the image is an image taken by a drone in the target area according to preset aerial photography parameters; Obtain the pixel coordinate values ​​corresponding to each calibration point in the image; wherein the pixel coordinate values ​​are determined by constructing a coordinate system with the top left corner of the image as the origin; Obtain the latitude, longitude, and elevation values ​​corresponding to each calibration point in the image; wherein, the calibration point is the vertex of a landmark in the target area; Control the camera to rotate and shoot in the target area according to a preset posture, and record the posture value of the camera when shooting; Based on the pixel coordinates, latitude and longitude, elevation and attitude values, the camera's external parameters are determined to achieve rapid calibration of the camera's external parameters.

2. The method according to claim 1, characterized in that, The step of obtaining the latitude, longitude, and elevation values ​​corresponding to each calibration point in the image includes: Based on the image, an orthophoto is generated using Pix4D software; Obtain the latitude and longitude corresponding to each calibration point from the orthophoto image; Based on the image, a digital elevation model is generated using Pix4D software; The elevation values ​​corresponding to each calibration point are obtained from the digital elevation model.

3. The method according to claim 1, characterized in that, Preset aerial photography parameters include: The drone was set to a flight altitude of 80m, a heading overlap rate of 85%, and a directional overlap rate of 80%.

4. The method according to claim 1, characterized in that, The determination of the camera's external parameters based on the pixel coordinates, latitude and longitude, elevation, and attitude values ​​includes: Based on the transformation relationship between the camera coordinate system and the geodetic coordinate system, the transformed pixel coordinates of each calibration point in the image are obtained from the camera coordinate system to the geodetic coordinate system; Calculate the Euclidean distance between the pixel coordinates and the transformed pixel coordinates for each calibration point; Minimize the Euclidean distance to determine the target Euclidean distance; The camera's external parameters are determined based on the target Euclidean distance, latitude and longitude, elevation value, and attitude value.

5. The method according to claim 4, characterized in that, The determination of the camera's external parameters based on the target Euclidean distance, latitude and longitude, elevation value, and attitude value includes: Based on the target Euclidean distance, the latitude, longitude, and elevation values ​​are converted into three-dimensional space to determine the translation vector; wherein, the translation vector is used to characterize the amount of camera translation when tracking the target; Based on the target Euclidean distance, the attitude value is transformed into three-dimensional space to determine the rotation matrix; wherein, the rotation matrix is ​​used to characterize the lens orientation when tracking the target.

6. The method according to claim 1, characterized in that, The number of each calibration point in the image is greater than the preset number.

7. The method according to claim 1, characterized in that, The number of each calibration point in the image is greater than the preset number.

8. A rapid calibration system for a visual positioning camera, characterized in that, include: An image acquisition module is used to acquire an image of a target area; wherein the image is an image taken in the target area according to preset aerial photography parameters; The first data acquisition module is used to acquire the pixel coordinate values ​​corresponding to each calibration point in the image; wherein the pixel coordinate values ​​are determined by constructing a coordinate system with the upper left corner of the image as the origin; The second data acquisition module is used to acquire the latitude, longitude, and elevation values ​​corresponding to each calibration point in the image; wherein, the calibration point is the vertex of a landmark in the target area; The third data acquisition module is used to control the camera to rotate and shoot in the target area according to a preset posture, and to record the posture value of the camera when shooting. The calibration module is used to determine the camera's external parameters based on the pixel coordinates, latitude and longitude, elevation, and attitude values, so as to achieve rapid calibration of the camera's external parameters.

9. A computing device, comprising a memory, a processor, and a program stored in the memory and running on the processor, characterized in that, When the processor executes the program, it implements a rapid calibration method for a visual positioning camera as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed on a terminal device, cause the terminal device to perform a rapid calibration method for a visual positioning camera as described in any one of claims 1-7.

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