A calibration method and device applied to a camera coordinate system and a world coordinate system

Abstract

The application provides a calibration method applied to a camera coordinate system and a world coordinate system, a calibration device and a computer storage medium. The calibration method comprises the following steps: collecting a two-dimensional image and a depth image of an area where a three-dimensional camera acquisition device is located; determining a device area and a world coordinate system direction line segment of the device in the two-dimensional image; generating a device plane according to depth information of the device area in the depth image; obtaining an end point of the world coordinate system direction line segment converted to a normalized camera plane of the camera, and obtaining an intermediate end point; determining a first coordinate axis direction vector of the world coordinate system in the camera coordinate system according to the intermediate end point, an origin of the camera coordinate system and the device plane; and determining a calibration matrix between the camera coordinate system and the world coordinate system according to the first coordinate axis direction vector. Through the calibration method, the 3D camera and the device world coordinate system are quickly calibrated, the calibration process is simplified, and the calibration cost is reduced.

Description

Technical Field

[0001] This application relates to the field of 3D calibration technology, and in particular to a calibration method, calibration device, and computer storage medium for camera coordinate system and world coordinate system. Background Technology

[0002] With the development of 3D vision technology, it has been applied to various aspects of the industrial field. Compared to 2D vision, 3D vision can acquire accurate spatial position information of objects, giving it a significant advantage in industrial applications.

[0003] In the industrial field, achieving 3D vision requires prior calibration of the camera coordinate system and the world coordinate system of the industrial equipment to ensure precise control based on 3D vision. However, current calibration methods still rely on calibration boards or markers for positioning, using a camera to photograph the calibration board or markers to calculate the extrinsic parameters between the camera coordinate system and the calibration board coordinate system, thereby obtaining the extrinsic parameters between the camera and the equipment's world coordinate system.

[0004] The above calibration process involves numerous steps and requires hardware costs such as calibration boards or calibration markers, resulting in high calibration costs and low efficiency for the current calibration scheme. Summary of the Invention

[0005] To address the aforementioned technical problems, this application proposes a calibration method, calibration device, and computer storage medium applicable to camera coordinate systems and world coordinate systems.

[0006] To address the aforementioned technical problems, this application proposes a calibration method for camera coordinate systems and world coordinate systems, the calibration method comprising:

[0007] Use a 3D camera to acquire 2D and depth images of the area where the equipment is located;

[0008] The device region and the world coordinate system direction line segment of the device are determined in the two-dimensional image;

[0009] Based on the depth information of the device region in the depth image, a device plane is generated;

[0010] The endpoints of the direction line segments in the world coordinate system are transformed to the normalized phase plane of the camera, and the intermediate endpoints are obtained.

[0011] Based on the intermediate endpoint, the origin of the camera coordinate system, and the device plane, determine the direction vector of the first coordinate axis of the world coordinate system in the camera coordinate system;

[0012] Based on the first coordinate axis direction vector, determine the calibration matrix between the camera coordinate system and the world coordinate system.

[0013] The step of generating a device plane based on the depth information of the device region in the depth image includes:

[0014] The point cloud information of the device region is determined based on the depth information of the device region in the depth image and the two-dimensional information of the device region in the two-dimensional image;

[0015] The least squares method is used to perform plane fitting on the point cloud information of the device area to generate the device plane.

[0016] Wherein, the area of ​​the two-dimensional image determination device includes:

[0017] Based on the user's selection instructions, the device area is determined in the two-dimensional image;

[0018] Alternatively, device detection can be performed in the two-dimensional image, and the device region can be determined in the two-dimensional image based on the device detection results.

[0019] The device region refers to the image location where at least a portion of the device is located.

[0020] Wherein, the area of ​​the two-dimensional image determination device includes:

[0021] Based on the user's selection instructions, candidate device regions are determined in the two-dimensional image;

[0022] Device detection is performed in the two-dimensional image, and the complete device region is determined in the two-dimensional image based on the device detection results.

[0023] The device region is determined based on the intersection of the candidate device region and the complete device region.

[0024] The step of determining the world coordinate system direction line segment of the device includes:

[0025] Based on the user's drawing instructions, the world coordinate system direction line segments are determined in the two-dimensional image;

[0026] Alternatively, device edge detection can be performed in the two-dimensional image, and the world coordinate system direction line segment can be determined in the two-dimensional image based on the device edge detection results.

[0027] The step of determining the direction vector of the first coordinate axis of the world coordinate system in the camera coordinate system based on the intermediate endpoint, the origin of the camera coordinate system, and the device plane includes:

[0028] Determine the first straight line based on the origin and the initial midpoint of the camera coordinate system;

[0029] Determine the second straight line based on the origin and the intermediate endpoint of the camera coordinate system;

[0030] Obtain the first intersection point between the first straight line and the device plane;

[0031] Obtain the second intersection point between the second straight line and the device plane;

[0032] The direction vector of the first coordinate axis is determined based on the first intersection point and the second intersection point.

[0033] The calibration method further includes:

[0034] Based on the device plane, determine the direction vector of the second coordinate axis of the world coordinate system in the camera coordinate system;

[0035] Based on the first coordinate axis direction vector and the second coordinate axis direction vector, determine the third coordinate axis direction vector of the world coordinate system in the camera coordinate system;

[0036] The step of determining the calibration matrix between the camera coordinate system and the world coordinate system based on the first coordinate axis direction vector includes:

[0037] The calibration matrix between the camera coordinate system and the world coordinate system is determined based on the first coordinate axis direction vector, the second coordinate axis direction vector, and the third coordinate axis direction vector.

[0038] The calibration matrix includes a rotation matrix and a translation vector.

[0039] The step of determining the calibration matrix between the camera coordinate system and the world coordinate system based on the first coordinate axis direction vector, the second coordinate axis direction vector, and the third coordinate axis direction vector includes:

[0040] Based on the first coordinate axis direction vector, the second coordinate axis direction vector, and the third coordinate axis direction vector, determine the rotation matrix between the camera coordinate system and the world coordinate system;

[0041] Based on the rotation matrix and the first intersection point, determine the translation vector between the camera coordinate system and the world coordinate system.

[0042] To address the aforementioned technical problems, this application also proposes a calibration device, which includes a memory and a processor coupled to the memory; wherein the memory is used to store program data, and the processor is used to execute the program data to implement the calibration method as described above.

[0043] To address the aforementioned technical problems, this application also proposes a computer storage medium for storing program data, which, when executed by a computer, is used to implement the aforementioned calibration method.

[0044] Compared with the prior art, the beneficial effects of this application are: the calibration device does not need to introduce calibration plates or calibration markers during the entire calibration process; the calibration device can complete the calibration of the world coordinate system of the 3D camera and the device by locating the relevant area and reference line segment in the two-dimensional image and transforming the relationship, without relying on cumbersome measurements, simplifying the calibration process and realizing the rapid calibration of the extrinsic parameters of the coordinate system of the 3D camera and the device. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0046] Figure 1 This is a schematic diagram of a scenario of an embodiment of the single-piece separator provided in this application;

[0047] Figure 2 This is a schematic diagram of a scenario of an embodiment of the cross-belt vehicle provided in this application;

[0048] Figure 3 This is a flowchart illustrating an embodiment of the calibration method for camera coordinate system and world coordinate system provided in this application;

[0049] Figure 4 This is a schematic diagram of a scenario of an embodiment of the device area of ​​the single-piece separator provided in this application;

[0050] Figure 5 This is a schematic diagram of a scenario of an embodiment of the equipment area of ​​the cross-belt trolley provided in this application;

[0051] Figure 6 This is a flowchart illustrating another embodiment of the calibration method for camera coordinate system and world coordinate system provided in this application;

[0052] Figure 7 This is a schematic diagram of a scenario of an embodiment of the world coordinate system direction line segment of the single-piece separator provided in this application;

[0053] Figure 8 This is a schematic diagram of a scenario of an embodiment of the world coordinate system direction line segment of the cross-belt vehicle provided in this application;

[0054] Figure 9This is a schematic diagram of an embodiment of the calibration device provided in this application;

[0055] Figure 10 This is a schematic diagram of the structure of an embodiment of the computer storage medium provided in this application. Detailed Implementation

[0056] 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 a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0057] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a particular order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the application described herein can be implemented, for example, in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0058] This application provides a low-cost and high-efficiency calibration method that can be applied to the extrinsic parameter calibration between the world coordinate system of a 3D camera and all types of equipment in the industrial field, thereby enabling automated control of industrial equipment based on 3D vision. The following description uses the logistics field as an example:

[0059] In the parcel sorting process, two widely used pieces of equipment are: single-item separators (see [link to product description]). Figure 1 The single-piece separator is used to separate a large number of packages into orderly packages with consistent front-to-back spacing, and the cross-belt grayscale meter is used to implement the cross-belt cart (see [link]). Figure 2 Both devices require a 3D camera to detect the package's position in order to perform subsequent package separation and position correction.

[0060] The package position obtained by the 3D camera is relative to the camera coordinate system. Before actual use, it is necessary to calibrate the external parameters between the 3D camera coordinate system and the world coordinate system defined by the device (such as the single-piece separator coordinate system or the cross-belt trolley coordinate system). The package position can be transformed to the device coordinate system through the calibrated external parameters in order to realize the single-piece separator's separation control of the package and the cross-belt package position correction function.

[0061] Therefore, the calibration method provided in this application can complete the external parameter calibration of the world coordinate system of the 3D camera and the device without the need for external calibration objects, simplify the calibration process, achieve rapid calibration, and avoid operational errors.

[0062] Please refer to the details. Figure 3 , Figure 3 This is a schematic flowchart of an embodiment of the calibration method for camera coordinate system and world coordinate system provided in this application. Figure 3 As shown, the calibration method for the 3D camera and device world coordinate system proposed in this application can be applied to application scenarios that require calibration of the extrinsic parameters of the 3D camera coordinate system and device world coordinate system, such as single-piece separators and cross-band grayscale meters.

[0063] The calibration method of this application is applied to a calibration device, which can be a server, a terminal device, or a system in which the server and the terminal device cooperate with each other. Accordingly, the various parts of the calibration device, such as each unit, subunit, module, and submodule, can all be set in the server, all in the terminal device, or separately in the server and the terminal device.

[0064] Furthermore, the aforementioned server can be either hardware or software. When the server is hardware, it can be implemented as a distributed server cluster consisting of multiple servers, or as a single server. When the server is software, it can be implemented as multiple software programs or software modules, such as software or software modules used to provide distributed server functionality, or as a single software program or software module; no specific limitations are made here.

[0065] like Figure 3 As shown, the specific steps are as follows:

[0066] Step S11: Use a 3D camera to acquire 2D and depth images of the area where the device is located.

[0067] In this embodiment, the staff sets up the 3D camera above the device in advance to ensure that the acquisition range of the 3D camera can cover the entire area or core area of ​​the device.

[0068] The calibration device controls the 3D camera to acquire 2D (color) images and depth images of the area where the device is located. The 2D images provide planar information of the device in the camera coordinate system, and the depth images provide depth information of the device.

[0069] The calibration device of this application obtains raw data containing planar geometric information of the device. The depth image provides the depth distance of each pixel, while the two-dimensional image is used for visual assistance and interaction.

[0070] Step S12: Determine the device region and the world coordinate system direction line segment of the device in the two-dimensional image.

[0071] In this embodiment of the application, the calibration device determines the device area and the world coordinate system direction line segment of the device on the two-dimensional image. The device area is used to fit the device plane, and the world coordinate system direction line segment of the device is used to reflect the origin of the world coordinate system and the coordinate axis direction in the camera coordinate system.

[0072] Specifically, such as Figure 4 and Figure 5 As shown, the calibration device can determine the equipment area in a two-dimensional image based on the user's selection instructions. The area shape includes, but is not limited to, rectangles, circles, triangles, or other custom shapes. The user's selection instructions can be implemented in the following scenarios: the user manually selects a planar area of ​​a single-piece separation system or a cross-belt trolley on a two-dimensional image.

[0073] In other embodiments, the calibration device can also automatically determine the device area, that is, detect the area where the device is located in the two-dimensional image by using a target detection algorithm or a target segmentation algorithm on the two-dimensional image.

[0074] The device region determined by the above method is the image location where at least part of the device is located. Preferably, the device region is the complete area of ​​the device in the image.

[0075] It should be noted that the calibration device can also integrate the two technical solutions mentioned above for determining the equipment area to improve the accuracy of the equipment area.

[0076] Please refer to the details. Figure 6 , Figure 6 This is a flowchart illustrating another embodiment of the calibration method for camera coordinate system and world coordinate system provided in this application.

[0077] like Figure 6 As shown, the specific steps are as follows:

[0078] Step S21: Based on the user's selection instructions, determine the candidate device region in the two-dimensional image.

[0079] Step S22: Perform device detection in the two-dimensional image, and determine the complete device area in the two-dimensional image based on the device detection results.

[0080] In this embodiment, the calibration device determines candidate device regions through user interaction commands and automatically determines the complete device region through a detection algorithm. These two device regions are used to evaluate the accurate location of the device region from both the user's and the machine's perspectives.

[0081] Step S23: Determine the device region based on the intersection of the candidate device region and the complete device region.

[0082] In this embodiment, the calibration device calculates the intersection area between the candidate device area and the complete device area, thereby determining the overlapping area of ​​the candidate device area and the complete device area as the device area. This device area is at least a part of both the candidate device area and the complete device area, reflecting the comprehensiveness of the calibration scheme. By introducing evaluation results from different angles, it reduces the error between the user angle and the machine angle, achieving accurate positioning of the device area.

[0083] Similarly, as Figure 7 and Figure 8 As shown, the calibration device can determine the world coordinate system direction line segment in the two-dimensional image according to the user's drawing instructions. The implementation scenario of the user's drawing instructions is as follows: The user manually draws a line segment on the color image. The starting point of the line segment is at the origin of the device's world coordinate system, and the direction of the line segment is parallel to the x-axis of the device's world coordinate system.

[0084] In other embodiments, the calibration device can also automatically determine the world coordinate system direction line segments, that is, by using an edge detection algorithm on the two-dimensional image to detect the edge line segments of the device in the two-dimensional image.

[0085] It should be noted that the calibration device can also integrate the two aforementioned technical solutions for determining world coordinate system direction segments to improve the accuracy of these segments. Specifically, this can be achieved by: using machine-generated world coordinate system direction segments to correct user-drawn world coordinate system direction segments; or, using user-drawn world coordinate system direction segments to correct machine-generated world coordinate system direction segments.

[0086] After the calibration device determines the direction line segment in the world coordinate system, it records the starting point of the direction line segment in the world coordinate system on the two-dimensional image. and the end point .

[0087] Step S13: Generate a device plane based on the depth information of the device region in the depth image.

[0088] In this embodiment of the application, the calibration device combines the two-dimensional planar information on the two-dimensional image and the depth information of the depth image to determine the point cloud information within the device area.

[0089] Since both the 2D and depth images are captured simultaneously by the 3D camera, there is no misalignment issue. Therefore, the calibration device can add the depth coordinates provided by the depth image to the pixel coordinates of the 2D image to generate a point cloud in 3D space. Specifically, the calibration device can use the 2D coordinates and depth values ​​of these pixels, combined with camera intrinsic parameters, to calculate their 3D coordinate point cloud in the 3D camera coordinate system.

[0090] Then, the calibration device uses the least squares method to perform plane fitting on the point cloud of the equipment area to generate the equipment plane. The general form of the equipment plane equation is:

[0091]

[0092] It should be noted that before plane fitting, the calibration device can also perform data preprocessing on the point cloud of the equipment area, including but not limited to: noise reduction processing, linear interpolation, etc., to improve the accuracy of the point cloud.

[0093] This application ensures that all point clouds used for plane fitting are point clouds of the device by pre-determining the device area, thus preventing the influence of areas outside the device on the device's plane generation.

[0094] Step S14: Transform the endpoints of the direction line segments in the world coordinate system to the normalized phase plane of the camera, and obtain the intermediate endpoints.

[0095] In this embodiment of the application, the starting point among the endpoints of the world coordinate system direction line segment determined in step S12 is... , is defined as the starting point of the device world coordinate system; the direction of the line segment is defined as the positive direction of the X-axis of the device world coordinate system.

[0096] Step S15: Determine the direction vector of the first coordinate axis of the world coordinate system in the camera coordinate system based on the intermediate endpoint, the origin of the camera coordinate system, and the device plane.

[0097] In this embodiment, the calibration device utilizes camera intrinsic parameters, such as focal length. He Guangxin The starting point of the direction line segment in the world coordinate system and the end point Transform to the normalized phase plane.

[0098] The normalized phase plane is an imaginary plane located at Z=1 directly in front of the camera. It is a normalized two-dimensional coordinate system onto which points in three-dimensional space are projected, ignoring their Z-axis coordinates (depth). The origin of this coordinate system is at the optical center, and the X and Y axes are parallel to the U and V axes of the image coordinate system.

[0099] Starting point of direction line segment in world coordinate system The initial intermediate endpoints obtained by transforming to the normalized phase plane for:

[0100]

[0101] End point of direction line segment in world coordinate system Termination intermediate endpoints obtained by transformation to the normalized phase plane for:

[0102]

[0103] Then, based on the principle that two points determine a straight line, the calibration device can obtain the points passing through the origin O of the camera coordinate system and... straight line and passing through the origin O of the camera coordinate system and straight line .

[0104] Finally, the calibration device calculates the straight line. Intersection with the equipment plane calibrated in step S13 The intersection point represents the coordinates of the origin of the device's world coordinate system in the 3D camera coordinate system.

[0105] Calibration device calculates straight line Intersection with the equipment plane calibrated in step S13 As can be seen from the previous calibration steps, this point is located on the x-axis of the device's world coordinate system.

[0106] Based on this, the calibration device can be based on the intersection point. and intersection Determine the direction vector of the device's world coordinate system x-axis in the 3D camera coordinate system. , that is, the direction vector of the first coordinate axis.

[0107] Step S16: Determine the calibration matrix between the camera coordinate system and the world coordinate system based on the direction vector of the first coordinate axis.

[0108] In this embodiment, the calibration device determines the z-axis direction vector of the device's world coordinate system based on the device plane normal vector. That is, the direction vector of the second coordinate axis. The calibration device is based on... Cross product The direction vector of the y-axis in the device's world coordinate system can then be calculated. That is, the direction vector of the third coordinate axis.

[0109] After the preceding steps, the calibration device calculates the direction vectors of the x, y, and z axes of the device world coordinate system in the 3D camera coordinate system, as well as the coordinates of the origin of the device world coordinate system in the 3D camera coordinate system. This allows us to obtain the extrinsic parameters from the 3D camera coordinate system to the device world coordinate system, namely the rotation matrix R and the translation vector T.

[0110]

[0111]

[0112] The calibration method of this application can complete the calibration of the world coordinate system of the 3D camera and the device through interactive operation on the color image of the 3D camera, without the need for external calibration tools and cumbersome measurements, thus simplifying the calibration process and realizing the rapid calibration of the external parameters of the coordinate system of the 3D camera, single-piece separator and cross-band grayscale meter and other application scenarios.

[0113] Those skilled in the art will understand that, in the above-described method of the specific implementation, the order in which each step is written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of each step should be determined by its function and possible internal logic.

[0114] To implement the above calibration method, this application also proposes a calibration device, for details please refer to [link / reference needed]. Figure 9 , Figure 9 This is a schematic diagram of an embodiment of the calibration device provided in this application.

[0115] The calibration device 400 in this embodiment includes a processor 41, a memory 42, an input / output device 43, and a bus 44.

[0116] The processor 41, memory 42, and input / output device 43 are respectively connected to the bus 44. The memory 42 stores program data, and the processor 41 is used to execute the program data to implement the calibration method described in the above embodiments.

[0117] In this embodiment, processor 41 can also be referred to as CPU (Central Processing Unit). Processor 41 may be an integrated circuit chip with signal processing capabilities. Processor 41 can also be a general-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component. The general-purpose processor can be a microprocessor, or processor 41 can be any conventional processor.

[0118] This application also provides a computer storage medium; please refer to the following: Figure 10 , Figure 10 This is a schematic diagram of a computer storage medium according to an embodiment of the present application. The computer storage medium 600 stores a computer program 61, which, when executed by a processor, is used to implement the calibration method of the above embodiment.

[0119] When the embodiments of this application are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, 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. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0120] The above description is merely an embodiment of this application and does not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A method for calibrating a camera coordinate system and a world coordinate system, comprising: The calibration method comprises: acquiring a two-dimensional image and a depth image of an area where the device is located by using a three-dimensional camera acquisition device; determining a device area and a world coordinate system direction line segment of the device in the two-dimensional image; generating a device plane according to depth information of the device area in the depth image; converting a starting point and an ending point of the world coordinate system direction line segment to a normalized phase plane of the camera to obtain an intermediate endpoint; determining a first coordinate axis direction vector of the world coordinate system in the camera coordinate system according to the intermediate endpoint, an origin of the camera coordinate system, and the device plane; determining a second coordinate axis direction vector of the world coordinate system in the camera coordinate system according to the device plane; determining a third coordinate axis direction vector of the world coordinate system in the camera coordinate system according to the first coordinate axis direction vector and the second coordinate axis direction vector; determining a calibration matrix between the camera coordinate system and the world coordinate system according to the first coordinate axis direction vector, the second coordinate axis direction vector, and the third coordinate axis direction vector; the determining of the first coordinate axis direction vector of the world coordinate system in the camera coordinate system according to the intermediate endpoint, the origin of the camera coordinate system, and the device plane comprises: determining a first straight line according to the origin of the camera coordinate system and a starting intermediate endpoint; determining a second straight line according to the origin of the camera coordinate system and a terminal intermediate endpoint; obtaining a first intersection point of the first straight line and the device plane; obtaining a second intersection point of the second straight line and the device plane; determining the first coordinate axis direction vector according to the first intersection point and the second intersection point.

2. The calibration method according to claim 1, wherein the generating of the device plane according to the depth information of the device area in the depth image comprises: determining point cloud information of the device area according to the depth information of the device area in the depth image and two-dimensional information of the device area in the two-dimensional image; performing plane fitting on the point cloud information of the device area by using a least square method to generate the device plane.

3. The calibration method according to claim 1, wherein the determining of the device area in the two-dimensional image comprises: determining the device area in the two-dimensional image based on a frame selection instruction of a user; or, performing device detection in the two-dimensional image, and determining the device area in the two-dimensional image according to a device detection result; wherein the device area is an image position where at least part of the device is located.

4. The calibration method according to claim 1 or 3, wherein the determining of the device area in the two-dimensional image comprises: determining a candidate device area in the two-dimensional image based on a frame selection instruction of a user; performing device detection in the two-dimensional image, and determining a complete device area in the two-dimensional image according to a device detection result; determining the device area according to an intersection area of the candidate device area and the complete device area.

5. The calibration method according to claim 1, wherein the determining of the world coordinate system direction line segment of the device comprises: determining a world coordinate system direction line segment in the two-dimensional image based on user drawing instructions; alternatively, performing device edge detection in the two-dimensional image, and determining a world coordinate system direction line segment in the two-dimensional image based on the device edge detection result.

6. The calibration method of claim 1, wherein the calibration matrix comprises a rotation matrix and a translation vector; and wherein the determining the calibration matrix between the camera coordinate system and the world coordinate system based on the first coordinate axis direction vector, the second coordinate axis direction vector, and the third coordinate axis direction vector comprises: determining a rotation matrix between the camera coordinate system and the world coordinate system based on the first coordinate axis direction vector, the second coordinate axis direction vector, and the third coordinate axis direction vector; and determining a translation vector between the camera coordinate system and the world coordinate system based on the rotation matrix and the first intersection point.

6. The calibration method of claim 1, wherein the calibration matrix comprises a rotation matrix and a translation vector; and wherein the determining the calibration matrix between the camera coordinate system and the world coordinate system based on the first coordinate axis direction vector, the second coordinate axis direction vector, and the third coordinate axis direction vector comprises: determining a rotation matrix between the camera coordinate system and the world coordinate system based on the first coordinate axis direction vector, the second coordinate axis direction vector, and the third coordinate axis direction vector; and determining a translation vector between the camera coordinate system and the world coordinate system based on the rotation matrix and the first intersection point. The calibration device comprises a memory and a processor coupled to the memory; wherein the memory is configured to store program data, and the processor is configured to execute the program data to implement the calibration method of any one of claims 1 to 6. The computer storage medium is configured to store program data, which when executed by a computer, is configured to implement the calibration method of any one of claims 1 to 6.

7. A calibration device, characterized by ​ ​ 8. A computer storage medium, characterized in that, ​

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