Camera calibration method, camera calibration device and computer storage medium

Abstract

The invention provides a camera calibration method, a camera calibration device and a computer storage medium. The camera calibration method comprises the following steps: extracting image points of a plurality of images; acquiring a calibration point group consisting of image points of each image and corresponding world points; based on a target calibration point group, calibrating a first transformation matrix from a target image point to a target world point in the target calibration point group; obtaining calibration world points of other calibration point groups by using the first transformation matrix; and calibrating a second transformation matrix of the camera by using the target image point and the target world point of the target calibration point group, and the image points and the calibration world points of the other calibration point groups. Through the camera calibration method, the calibration process is simple and rapid, specific internal and external parameters of the camera do not need to be required, the transformation matrix is solved through iterative optimization of multiple images, the transformation matrix has high precision for the whole image, and large-view-field two-dimensional size measurement calibration is facilitated.

Description

Technical Field

[0001] The present application relates to the technical field of camera calibration, and in particular to a camera calibration method, a camera calibration device and a computer storage medium. Background Art

[0002] Linear array cameras have higher imaging resolution than area array cameras and are very suitable for high-precision two-dimensional dimension measurement. Before realizing two-dimensional dimension measurement through images, it is necessary to establish the correspondence between image points and world points on the plane to be measured, which is called camera calibration.

[0003] However, the current camera calibration scheme for two-dimensional dimension measurement is mainly based on one picture for calibration. In order to ensure the overall accuracy, the calibration plate needs to cover the entire plane to be measured. When the field of view is relatively large and the accuracy requirements are relatively high, this method will significantly increase the calibration cost and operation difficulty. In addition, there is also a method of completing the intrinsic parameter calibration of the camera through multiple pictures, and then using the calibration plate located at the center of the plane to be measured to complete the external parameter calibration, so as to obtain the correspondence between the image points and the points on the plane to be measured. This method does not constrain all the calibration plates on the plane to be measured to one plane, which may cause the measurement error at the edge of the field of view to be larger, and the internal and external parameters need to be solved, and the calibration process is more complicated. Summary of the invention

[0004] In order to solve the above technical problems, the present application proposes a camera calibration method, a camera calibration device and a computer storage medium.

[0005] In order to solve the above technical problems, the present application proposes a camera calibration method, which includes:

[0006] Extracting image points of several images;

[0007] Obtain a calibration point group consisting of image points and corresponding world points of each image;

[0008] Based on the target calibration point group, calibrate a first transformation matrix from a target image point in the target calibration point group to a target world point;

[0009] Using the first transformation matrix, obtaining calibration world points of other calibration point groups;

[0010] The second transformation matrix of the camera is calibrated using the target image points and target world points of the target calibration point group and the image points and calibration world points of the other calibration point groups.

[0011] The step of using the first transformation matrix to obtain calibration world points of other calibration point groups includes:

[0012] Using the first transformation matrix, transform the image points of the other calibration point groups to obtain intermediate world points;

[0013] Acquire a transformation relationship based on the world points of the other calibration point groups and the intermediate world points;

[0014] The intermediate world point is transformed into the world coordinate system where the target world point is located by using the transformation relationship to obtain the calibration world point.

[0015] The second transformation matrix of the camera is calibrated using the target image points and target world points of the target calibration point group and the image points and calibration world points of the other calibration point groups, including:

[0016] Merging the target image points of the target calibration point group and the image points of the other calibration point groups into an image point array;

[0017] Merging the target world points of the target calibration point group and the calibration world points into a world point array;

[0018] The image point array and the world point array are input into a linear calibration equation to obtain a second transformation matrix of the camera by solving the equation.

[0019] After calibrating the second transformation matrix of the camera using the target image points and target world points of the target calibration point group, and the image points and calibration world points of the other calibration point groups, the camera calibration method further includes:

[0020] Taking the world points corresponding to the image points of the plurality of images as real points;

[0021] Using the second transformation matrix, obtaining observation points of image points of the plurality of images;

[0022] Based on the observed point and the real point, obtaining a calibration error;

[0023] In response to the calibration error satisfying a preset condition, a second transformation matrix of the camera is output.

[0024] Wherein, in response to the calibration error satisfying a preset condition, outputting a second transformation matrix of the camera comprises:

[0025] Get the calibration error of multiple consecutive camera calibration processes;

[0026] In response to the error difference of calibration errors of adjacent camera calibration processes being less than a preset threshold, a second transformation matrix obtained by a subsequent camera calibration process in the adjacent camera calibration processes is output.

[0027] Wherein, the camera is a linear array camera;

[0028] The step of calibrating a first transformation matrix from a target image point in the target calibration point group to a target world point based on the target calibration point group includes:

[0029] A plurality of target image points and a plurality of target world points of the target calibration point group are input into the linear calibration equation of the line array camera, and a first transformation matrix from the target image points to the target world points is obtained by solving the equation.

[0030] Wherein, the camera calibration method further includes:

[0031] Based on the motion speed of the motion platform, the first calibration relationship between the world coordinate system and the camera coordinate system is established;

[0032] Establishing a second calibration relationship between the image coordinate system and the world coordinate system according to the perspective projection transformation and the first calibration relationship;

[0033] The second calibration relationship is transformed and resolved to obtain a linear calibration equation between the image point and the world point.

[0034] In order to solve the above technical problems, the present application also proposes a camera calibration device, which includes: an extraction module, a calibration module, and a transformation module; wherein:

[0035] The extraction module is used to extract image points of a plurality of images;

[0036] The calibration module is used to obtain a calibration point group consisting of image points and corresponding world points of each image;

[0037] The calibration module is used to calibrate a first transformation matrix from a target image point to a target world point in the target calibration point group based on the target calibration point group;

[0038] The transformation module is used to obtain calibration world points of other calibration point groups using the first transformation matrix;

[0039] The calibration module is used to calibrate the second transformation matrix of the camera using the target image points and target world points of the target calibration point group and the image points and calibration world points of the other calibration point groups.

[0040] In order to solve the above technical problems, the present application also proposes a camera 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 camera calibration method as described above.

[0041] In order to solve the above technical problems, the present application also proposes a computer storage medium, which is used to store program data. When the program data is executed by a computer, it is used to implement the above camera calibration method.

[0042] Compared with the prior art, the beneficial effects of the present application are: the camera calibration device extracts the image points of several images; obtains the calibration point group consisting of the image points of each image and the corresponding world points; based on the target calibration point group, calibrates the first transformation matrix from the target image points to the target world points in the target calibration point group; uses the first transformation matrix to obtain the calibration world points of other calibration point groups; uses the target image points and target world points of the target calibration point group, and the image points and calibration world points of the other calibration point groups to calibrate the second transformation matrix of the camera. Through the above-mentioned camera calibration method, the calibration process is simple and fast, and there is no need to find the specific internal and external parameters of the camera. The transformation matrix is ​​solved by iterative optimization of multiple images, so that the transformation matrix has high accuracy for the entire image, which is conducive to large field of view two-dimensional size measurement calibration. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0044] in:

[0045] Figure 1 is a flowchart of the first embodiment of the camera calibration method provided by the present application;

[0046] Figure 2 It is a schematic diagram of the overall process of the camera calibration method provided by this application;

[0047] Figure 3 is a flowchart of a second embodiment of a camera calibration method provided by the present application;

[0048] Figure 4 is a flowchart of a third embodiment of a camera calibration method provided by the present application;

[0049] Figure 5 is a structural schematic diagram of an embodiment of a camera calibration device provided by the present application;

[0050] Figure 6 is a structural schematic diagram of an embodiment of a camera calibration device provided by the present application;

[0051] Figure 7 It is a structural diagram of an embodiment of a computer storage medium provided by the present application. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0053] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can, for example, be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0054] The problem to be solved by this application is to perform large-field-of-view two-dimensional size measurement calibration using a general 2D plane target (such as a chessboard, a circular array, etc.). This application can collect multiple images containing 2D plane targets, where the targets are located in different areas of the image, thereby ensuring the calibration accuracy of each area on the large-field-of-view image, and the calibration process is also simpler and faster.

[0055] Please refer to Figure 1 and Figure 2 , Figure 1 is a flowchart of the first embodiment of the camera calibration method provided by this application, Figure 2 It is a schematic diagram of the overall process of the camera calibration method provided in this application.

[0056] The camera calibration method of the present application is applied to a camera calibration device, wherein the camera calibration device of the present application can be a server, a terminal device, or a system in which a server and a terminal device cooperate with each other. Accordingly, the various parts included in the camera calibration device, such as various units, sub-units, modules, and sub-modules, can all be set in the server, can all be set in the terminal device, or can be set in the server and the terminal device respectively.

[0057] Furthermore, the above-mentioned server can be hardware or software. When the server is hardware, it can be implemented as a distributed server cluster consisting of multiple servers, or it can be implemented as a single server. When the server is software, it can be implemented as multiple software or software modules, such as software or software modules used to provide distributed servers, or it can be implemented as a single software or software module, which is not specifically limited here.

[0058] like Figure 1 As shown, the specific steps are as follows:

[0059] Step S11: extracting image points of a number of images.

[0060] In an embodiment of the present application, when the plane to be measured is relatively large, the commonly used targets often cannot cover the entire plane, resulting in poor accuracy of points farther away from the targets. Therefore, the present application chooses to place the targets in various areas of the plane to be measured, and collects a calibration image for each area, thereby obtaining n images.

[0061] Furthermore, the camera calibration device extracts the feature points on each image and uses (P i , Q i ) represents the image point on the i-th image and the world point corresponding to the image point, P i and Q i Each point in has a one-to-one correspondence.

[0062] It should be noted that the camera calibration device extracts multiple feature points from each image, which should be understood as satisfying the quantity requirement for camera calibration of a single image.

[0063] Step S12: Obtain a calibration point group consisting of image points and corresponding world points of each image.

[0064] In the embodiment of the present application, the camera calibration device obtains a calibration point group (P i , Q i ).

[0065] Step S13: based on the target calibration point group, calibrate a first transformation matrix from the target image point to the target world point in the target calibration point group.

[0066] In the embodiment of the present application, the camera calibration device selects the first calibration point group (P1, Q1) as the target calibration point group, and calculates the transformation matrix H from the image point to the world point. The camera calibration device can use a commonly used camera calibration algorithm to obtain the above-mentioned first transformation matrix according to a single image calibration calculation.

[0067] It should be noted that, in other embodiments, the camera calibration device may also select other groups of calibration point groups as the target calibration point groups in step S13, which is not specifically limited here.

[0068] Step S14: using the first transformation matrix, obtaining calibration world points of other calibration point groups.

[0069] In the embodiment of the present application, the image points (P2, P3, P4, P5, P6, P7, P8, P9, P10, P11, P12, P13, P14, P15, P16, P17, P18, P19, P20, P21, P22, P23, P24, P25, P26, P27, P28, P29, P30, P31, P32 n ), and use the transformation matrix H to transform the corresponding world points (Q′2, Q′3…, Q′ n ).

[0070] Then, the camera calibration device calculates (Q2, Q3…, Q n ) to (Q′2, Q′3…, Q′ n ) of the optimal transformation relation RT, and obtain the corresponding transformation relation (RT2, RT3…, RT n ).

[0071] Finally, the camera calibration device is used (RT2, RT3…, RT n ) points (Q′2, Q′3…, Q′ n ) is transformed to the world coordinate system (Q″2, Q″3…, W″ n ).

[0072] Step S15: calibrate the second transformation matrix of the camera using the target image points and target world points of the target calibration point group, and the image points and calibration world points of other calibration point groups.

[0073] In the embodiment of the present application, the camera calibration device converts the image points (P1, P2, P3..., P n ) are merged into P, and the world points (Q1, Q″2, Q″3…, Q″ n ) is merged into Q. Among them, P is the image point array; Q is the world point array.

[0074] Finally, the camera calibration device calculates the transformation matrix H between the merged image point and the world point (P, Q) as the camera transformation matrix. The linear equation used in the calibration process of step S15 is the same as the linear equation used in the calibration process of step S13. The principle is equivalent to treating the image points in multiple images as being on the same image, thereby achieving single image calibration.

[0075] In the present application, a camera calibration device extracts image points of several images; obtains a calibration point group consisting of image points and corresponding world points of each image; based on the target calibration point group, calibrates the first transformation matrix from the target image point to the target world point in the target calibration point group; uses the first transformation matrix to obtain the calibration world points of other calibration point groups; uses the target image points and target world points of the target calibration point group, as well as the image points and calibration world points of the other calibration point groups to calibrate the second transformation matrix of the camera. Through the above-mentioned camera calibration method, the calibration process is simple and fast, and there is no need to find out the specific internal and external parameters of the camera. The transformation matrix is ​​solved by iterative optimization of multiple images, so that the transformation matrix has high accuracy for the entire image, which is conducive to large field of view two-dimensional size measurement calibration.

[0076] Furthermore, if Figure 2 As shown, in Figure 1 In the camera calibration method shown, a single calibration may not produce a good effect. Therefore, the present application also provides a calibration evaluation system for camera calibration and a corresponding iterative optimization solution.

[0077] Please continue to read Figure 3 , Figure 3 It is a flowchart of the second embodiment of the camera calibration method provided in this application.

[0078] like Figure 3 As shown, the specific steps are as follows:

[0079] Step S21: taking the world points corresponding to the image points of several images as real points.

[0080] In the embodiment of the present application, the camera calibration device converts the world points (Q1, Q2, Q3..., Q n ) as a point of truth.

[0081] Step S22: using the second transformation matrix, obtaining observation points of image points of a plurality of images.

[0082] In the embodiment of the present application, the camera calibration device uses the transformation matrix H obtained by the calibration in step S15 to obtain the image points (P1, P2, P3..., P n ) of the observation points (Q″′1, Q″′2, Q″′3…, Q″′ n ).

[0083] Step S23: Obtain calibration errors based on the observed points and the real points.

[0084] In the embodiment of the present application, the camera calibration device calculates the observation points (Q″′1, Q″′2, Q″′3…, Q″′ n ) and the real points (Q1, Q2, Q3…, Q n). The calibration error of the present application can be evaluated by RMS error (Root Mean Squared Error), also known as root mean square error or standard error.

[0085] Step S24: In response to the calibration error satisfying a preset condition, outputting a second transformation matrix of the camera.

[0086] In the embodiment of the present application, the camera calibration device repeats Figure 1 The camera calibration method shown, as well as steps S21 to S23, ends outputting the transformation matrix H until the difference between the two RMS errors is less than a certain threshold or the number of iterations is greater than a certain threshold.

[0087] Therefore, the transformation matrix H output by the camera calibration device can be used for large-field-of-view two-dimensional size measurement and can ensure the accuracy of each area in the entire image.

[0088] Furthermore, the above Figure 1 and Figure 3 The camera calibration methods shown above can all be used to calibrate line scan cameras. The following will introduce the calibration scheme for line scan cameras, that is, the derivation process of the above linear equations. Figure 4 , Figure 4 It is a flowchart of the third embodiment of the camera calibration method provided in this application.

[0089] like Figure 4 As shown, the specific steps are as follows:

[0090] Step S31: Based on the motion speed of the motion platform, a first calibration relationship between the world coordinate system and the camera coordinate system is established.

[0091] In the embodiment of the present application, since the line array camera can only image one or several rows of pixels at a time, an additional motion platform is required to assist in imaging. Assume that the motion speed of the platform is (v x , v y , v z ), which means the amount of movement of the platform in the camera coordinate system when the camera captures a line of pixels.

[0092] Based on the above assumptions, the camera calibration device fixes the world coordinate system on the motion platform, and the relationship between the coordinates in the world coordinate system and the coordinates in the camera system is as follows:

[0093]

[0094] Among them, (x c ,y c , z c ) and (x w ,y w , z w) represent the coordinates in the camera coordinate system and the coordinates in the world coordinate system respectively; r ij and (t x , t y , t z ) represents the external parameters of the camera in the world coordinate system when collecting the 0th row of pixels; (w, h) represents the pixel coordinates of the point on the image.

[0095] Step S32: establishing a second calibration relationship between the image coordinate system and the world coordinate system according to the perspective projection transformation and the first calibration relationship.

[0096] In the embodiment of the present application, according to the perspective projection transformation, the point z on the target w = 0, then there is a second calibration relationship between the image coordinate system and the world coordinate system:

[0097]

[0098] Step S33: transform and solve the second calibration relationship to obtain a linear calibration equation between the image point and the world point.

[0099] In the embodiment of the present application, the second calibration relationship between the image coordinate system and the world coordinate system is further resolved to obtain:

[0100]

[0101] make,

[0102]

[0103] Among them, each image point (w, h) is related to its corresponding world point (x w ,y w , 0) can be a linear equation:

[0104]

[0105] Therefore, the camera calibration device can solve the transformation matrix H through direct linear transformation of multiple groups of points. The matrix H realizes the mutual conversion between image points and world points, that is, completes the two-dimensional size measurement calibration based on a single image.

[0106] The camera calibration method of the present application has a simple and fast calibration process. It does not need to find out the specific internal and external parameters of the camera. The transformation matrix H is solved by iterative optimization of multiple images, so that the transformation matrix has high accuracy for the entire image, and large field of view two-dimensional size measurement calibration can be performed.

[0107] When the camera calibration method of the present application establishes a camera model, no strict requirements are imposed on the platform movement direction, and the derived transformation matrix is ​​simpler and more general.

[0108] Those skilled in the art will appreciate that, in the above method of specific implementation, the order in which the steps are written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of the steps should be determined by their functions and possible internal logic.

[0109] In order to implement the above-mentioned camera calibration method, this application also proposes a camera calibration device, for details, please refer to Figure 5 , Figure 5 It is a structural schematic diagram of an embodiment of a camera calibration device provided in this application.

[0110] The camera calibration device 500 of this embodiment includes: an extraction module 51 , a calibration module 52 , and a transformation module 53 .

[0111] The extraction module 51 is used to extract image points of a plurality of images.

[0112] The calibration module 52 is used to obtain a calibration point group consisting of image points and corresponding world points of each image.

[0113] The calibration module 52 is used to calibrate a first transformation matrix from a target image point in the target calibration point group to a target world point based on the target calibration point group.

[0114] The transformation module 53 is used to obtain the calibration world points of other calibration point groups by using the first transformation matrix.

[0115] The calibration module 52 is used to calibrate the second transformation matrix of the camera using the target image points and target world points of the target calibration point group and the image points and calibration world points of the other calibration point groups.

[0116] To implement the above camera calibration method, this application also proposes a camera calibration device, please refer to Figure 6 , Figure 6 It is a structural schematic diagram of an embodiment of a camera calibration device provided in this application.

[0117] The camera calibration device 400 of this embodiment includes a processor 41 , a memory 42 , an input / output device 43 , and a bus 44 .

[0118] The processor 41 , the memory 42 , and the input / output device 43 are respectively connected to the bus 44 . The memory 42 stores program data. The processor 41 is used to execute the program data to implement the camera calibration method described in the above embodiment.

[0119] In the embodiment of the present application, the processor 41 may also be referred to as a CPU (Central Processing Unit). The processor 41 may be an integrated circuit chip having the ability to process signals. The processor 41 may also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gates or transistor logic devices, or discrete hardware components. A general-purpose processor may be a microprocessor or the processor 41 may also be any conventional processor, etc.

[0120] This application also provides a computer storage medium, please continue to refer to Figure 7 , Figure 7 6 is a schematic diagram of the structure of an embodiment of a computer storage medium provided in the present application. The computer storage medium 600 stores a computer program 61. When the computer program 61 is executed by a processor, it is used to implement the camera calibration method of the above embodiment.

[0121] When the embodiments of the present application are implemented in the form of 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 the present application is essentially 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, and the computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor (processor) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a disk or an optical disk.

[0122] The above description is only an implementation method of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly used in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A camera calibration method, characterized in that: The camera calibration method comprises: Extracting image points of several images; Obtain a calibration point group consisting of image points and corresponding world points of each image; Based on the target calibration point group, calibrate a first transformation matrix from a target image point in the target calibration point group to a target world point; Using the first transformation matrix, obtaining calibration world points of other calibration point groups; The second transformation matrix of the camera is calibrated using the target image points and target world points of the target calibration point group and the image points and calibration world points of the other calibration point groups.

2. The camera calibration method according to claim 1, characterized in that: The step of using the first transformation matrix to obtain calibration world points of other calibration point groups includes: Using the first transformation matrix, transform the image points of the other calibration point groups to obtain intermediate world points; Acquire a transformation relationship based on the world points of the other calibration point groups and the intermediate world points; The intermediate world point is transformed into the world coordinate system where the target world point is located by using the transformation relationship to obtain the calibration world point.

3. The camera calibration method according to claim 1, characterized in that: Using the target image points and target world points of the target calibration point group, and the image points and calibration world points of the other calibration point groups to calibrate the second transformation matrix of the camera, comprising: Merging the target image points of the target calibration point group and the image points of the other calibration point groups into an image point array; Merging the target world points of the target calibration point group and the calibration world points into a world point array; The image point array and the world point array are input into a linear calibration equation to obtain a second transformation matrix of the camera by solving the equation.

4. The camera calibration method according to claim 1 or 3, characterized in that: After calibrating the second transformation matrix of the camera using the target image points and target world points of the target calibration point group, and the image points and calibration world points of the other calibration point groups, the camera calibration method further includes: Taking the world points corresponding to the image points of the plurality of images as real points; Using the second transformation matrix, obtaining observation points of image points of the plurality of images; Based on the observed point and the real point, obtaining a calibration error; In response to the calibration error satisfying a preset condition, a second transformation matrix of the camera is output.

5. The camera calibration method according to claim 4, characterized in that: In response to the calibration error satisfying a preset condition, outputting a second transformation matrix of the camera comprises: Get the calibration error of multiple consecutive camera calibration processes; In response to the error difference of calibration errors of adjacent camera calibration processes being less than a preset threshold, a second transformation matrix obtained by a subsequent camera calibration process in the adjacent camera calibration processes is output.

6. The camera calibration method according to claim 1, characterized in that: The camera is a linear array camera; The step of calibrating a first transformation matrix from a target image point in the target calibration point group to a target world point based on the target calibration point group includes: A plurality of target image points and a plurality of target world points of the target calibration point group are input into the linear calibration equation of the line array camera, and a first transformation matrix from the target image points to the target world points is obtained by solving the equation.

7. The camera calibration method according to claim 6, characterized in that: The camera calibration method further includes: Based on the motion speed of the motion platform, the first calibration relationship between the world coordinate system and the camera coordinate system is established; Establishing a second calibration relationship between the image coordinate system and the world coordinate system according to the perspective projection transformation and the first calibration relationship; The second calibration relationship is transformed and resolved to obtain a linear calibration equation between the image point and the world point.

8. A camera calibration device, characterized in that: The camera calibration device comprises: an extraction module, a calibration module, and a transformation module; wherein, The extraction module is used to extract image points of a plurality of images; The calibration module is used to obtain a calibration point group consisting of image points and corresponding world points of each image; The calibration module is used to calibrate a first transformation matrix from a target image point to a target world point in the target calibration point group based on the target calibration point group; The transformation module is used to obtain calibration world points of other calibration point groups using the first transformation matrix; The calibration module is used to calibrate the second transformation matrix of the camera using the target image points and target world points of the target calibration point group and the image points and calibration world points of the other calibration point groups.

9. A camera calibration device, characterized in that: The camera calibration device includes a memory and a processor coupled to the memory; The memory is used to store program data, and the processor is used to execute the program data to implement the camera calibration method according to any one of claims 1 to 7.

10. A computer storage medium, characterized in that: The computer storage medium is used to store program data, and when the program data is executed by a computer, it is used to implement the camera calibration method according to any one of claims 1 to 7.

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