Method and device for automatically calibrating camera

Abstract

The invention discloses a method and a device for automatically calibrating a camera. The camera automatic calibration method comprises the following steps: acquiring calibration images of at least three stagnation points in a preset calibration environment when a conveyor belt moves through image acquisition equipment mounted on the conveyor belt; under the condition that polling of the stagnation points in the preset calibration environment is finished, feature extraction is carried out according to the calibration images of the at least three stagnation points, and feature data are obtained; and performing internal reference calculation through the image acquisition equipment according to the feature data to obtain a calculation result, and ending the automatic calibration. The technical effect of improving the calibration efficiency and accuracy can be achieved.

Description

Technical Field

[0001] The present invention relates to the field of computer technology applications, and in particular to a method and device for automatic calibration of a camera. Background Art

[0002] Traditional camera calibration requires manual placement of calibration plates multiple times to ensure that the characteristic information of the calibration plate can be observed at every position of the image. The camera internal parameters are solved according to the camera model, including focal length, center offset, and distortion coefficient. During the solution process, the internal parameters need to be solved by optimization method based on the coordinates of the QR code corner points in the calibration plate coordinate system on the screen and the coordinates of the QR code in the image coordinate system.

[0003] The disadvantage of the existing technology is that it is time-consuming and labor-intensive, and requires manual placement of calibration plates multiple times. In addition, the positions of the calibration plates are different for different calibrations, and the obtained calibration plates cannot evenly cover all areas of the image, resulting in large repetition errors and poor consistency.

[0004] Currently, no effective solution has been proposed to address the problems of time-consuming, labor-intensive, inefficient and poor consistency of calibration results in traditional camera calibration methods. Summary of the invention

[0005] In order to solve the above technical problems, the embodiments of the present invention hope to provide a method and device for automatic camera calibration, so as to at least solve the problems of time-consuming, labor-intensive, low efficiency and poor consistency of calibration results existing in traditional camera calibration methods.

[0006] The technical solution of the present invention is achieved in this way:

[0007] An embodiment of the present invention provides a method for automatic calibration of a camera, comprising: using an image acquisition device installed on a conveyor belt, acquiring calibration images of at least three stationary points in a preset calibration environment when the conveyor belt passes through the conveyor belt in motion; when polling of the stationary points in the preset calibration environment is completed, performing feature extraction based on the calibration images of the at least three stationary points to obtain feature data; performing internal parameter calculation based on the feature data through the image acquisition device to obtain a calculation result, and the automatic calibration is completed.

[0008] Optionally, the preset calibration environment includes: at least three stationary points, wherein each stationary point is provided with a display, the display being used to display the identification code array; the distance between the display and the conveyor belt is determined according to the depth of field of the image acquisition device; wherein the size of the identification code in the identification code array is adjusted according to the distance, and the image size of the identification code remains unchanged during the calibration process; the conveyor belt is provided with a structure for fixing the image acquisition device, the structure being used to fix the image acquisition device, and when the conveyor belt moves to each stationary point, the image acquisition device is rotated according to a preset angle.

[0009] Optionally, capturing calibration images of the conveyor belt passing through at least three stationary points in a preset calibration environment during its movement through an image acquisition device installed on the conveyor belt includes: controlling the conveyor belt to move at a preset speed, moving the image acquisition device installed on the conveyor belt to the position of each stationary point, capturing the identification code array displayed on the display at each stationary point, and obtaining a calibration image.

[0010] Further, optionally, the method further includes: controlling the image acquisition device to rotate sequentially at preset angles according to a preset rotation speed at each stationary point position.

[0011] Optionally, after obtaining the calculation result, the method further includes: storing the calculation result in an image acquisition device.

[0012] An embodiment of the present invention provides a device for automatic calibration of a camera, comprising: an acquisition module, which is used to acquire calibration images of at least three stationary points in a preset calibration environment when a conveyor belt passes through the conveyor belt during movement through an image acquisition device installed on the conveyor belt; an extraction module, which is used to extract features according to the calibration images of at least three stationary points in the preset calibration environment when polling of the stationary points in the preset calibration environment is completed, so as to obtain feature data; and a calculation module, which is used to perform internal parameter calculation through the image acquisition device according to the feature data, so as to obtain a calculation result, and the automatic calibration is completed.

[0013] Optionally, the preset calibration environment includes: at least three stationary points, wherein each stationary point is provided with a display, the display being used to display the identification code array; the distance between the display and the conveyor belt is determined according to the depth of field of the image acquisition device; wherein the size of the identification code in the identification code array is adjusted according to the distance, and the image size of the identification code remains unchanged during the calibration process; the conveyor belt is provided with a structure for fixing the image acquisition device, the structure being used to fix the image acquisition device, and when the conveyor belt moves to each stationary point, the image acquisition device is rotated according to a preset angle.

[0014] Optionally, the acquisition module includes: an acquisition unit, used to control the conveyor belt to move at a preset speed, and when the image acquisition device installed on the conveyor belt moves to the position of each stationary point, the identification code array displayed on the display at each stationary point is acquired to obtain a calibration image.

[0015] Further, optionally, the apparatus further comprises: a rotation module, configured to control the image acquisition device to rotate sequentially at preset angles at each stationary point according to a preset rotation speed.

[0016] Optionally, the apparatus further includes: a storage module, configured to store the calculation result in the image acquisition device after the calculation result is obtained.

[0017] The embodiment of the present invention provides a method and device for automatic calibration of a camera. The method and device collect calibration images of at least three stationary points in a preset calibration environment when the conveyor belt passes through the conveyor belt in motion through an image acquisition device. When the polling of the stationary points in the preset calibration environment is completed, feature extraction is performed based on the calibration images of the at least three stationary points to obtain feature data. Internal parameter calculation is performed through the image acquisition device based on the feature data to obtain a calculation result, and the automatic calibration is completed, thereby achieving a technical effect of improving the efficiency and accuracy of calibration. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0019] Figure 1 A schematic diagram of a flow chart of a method for automatic camera calibration provided by an embodiment of the present invention;

[0020] Figure 2 A schematic diagram of a method for automatic camera calibration provided by an embodiment of the present invention;

[0021] Figure 3 A schematic diagram of a camera automatic calibration device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0023] It should be noted that the terms "first", "second" and the like in the specification, claims and drawings of the present invention are used to distinguish different objects rather than to limit a specific order.

[0024] It should also be noted that the following embodiments of the present invention may be executed separately, or in combination with each other, and the embodiments of the present invention do not impose any specific limitations on this.

[0025] The embodiment of the present invention provides a method for automatic calibration of a camera. Figure 1 A schematic diagram of a flow chart of a method for automatic camera calibration provided by an embodiment of the present invention; Figure 1 As shown, the method for automatic camera calibration provided in the embodiment of the present application includes:

[0026] Step S102, using an image acquisition device installed on the conveyor belt, to acquire calibration images of at least three stationary points in a preset calibration environment when the conveyor belt is moving;

[0027] Optionally, the preset calibration environment includes: at least three stationary points, wherein each stationary point is provided with a display, the display being used to display the identification code array; the distance between the display and the conveyor belt is determined according to the depth of field of the image acquisition device; wherein the size of the identification code in the identification code array is adjusted according to the distance, and the image size of the identification code remains unchanged during the calibration process; the conveyor belt is provided with a structure for fixing the image acquisition device, the structure being used to fix the image acquisition device, and when the conveyor belt moves to each stationary point, the image acquisition device is rotated according to a preset angle.

[0028] Specifically, in the preset calibration environment in the embodiment of the present application, the identification code array can be a two-dimensional code array, wherein the two-dimensional code array is displayed through a display; in the method for automatic camera calibration provided in the embodiment of the present application, the actual size of the displayed two-dimensional code can be obtained by the resolution of the display and the pixel size of the displayed two-dimensional code.

[0029] The image acquisition device in the embodiment of the present application can be a camera, wherein the distance between the conveyor belt and the screen (i.e., the screen of the display in the embodiment of the present application) is adjusted according to the depth of field of the camera, and the size of the QR code (i.e., the size of the identification code in the embodiment of the present application) can be adjusted according to the distance. The QR code image remains unchanged during the calibration process, and it is stipulated that the camera captures the QR code on the screen, and the QR code in the captured image covers all positions in the image.

[0030] Among them, the entire imaging area is covered to accurately estimate the distortion coefficient. Specifically, the lens distortion of the camera is usually most obvious in the edge area of ​​the image, especially the radial distortion. Therefore, by collecting images from different angles, the feature points will be distributed on the entire image plane, especially covering the edge area of ​​the image, which helps to accurately estimate the distortion coefficient.

[0031] The structure of the conveyor belt fixed with the image acquisition device in the embodiment of the present application may be a device for fixing the camera on the conveyor belt, which can control the camera to rotate to a fixed angle after the conveyor belt runs to each stationary point.

[0032] In the embodiment of the present application, at least three stationary points are set, that is, the number of the stationary points is greater than or equal to three, and each time the conveyor belt reaches a stationary point, the camera is rotated according to a preset angle.

[0033] Optionally, in step S102, the image acquisition device installed on the conveyor belt is used to capture calibration images of the conveyor belt passing through at least three stationary points in a preset calibration environment during its movement, including: controlling the conveyor belt to move at a preset speed, moving the image acquisition device installed on the conveyor belt to the position of each stationary point, capturing the identification code array displayed on the display at each stationary point, and obtaining a calibration image.

[0034] Among them, the preset speed can be: 1m / s;

[0035] Further, optionally, the method for automatic camera calibration provided in the embodiment of the present application also includes: controlling the image acquisition device to rotate sequentially at preset angles according to a preset rotation speed at each stationary point.

[0036] Among them, the preset rotation speed in the embodiment of the present application can be: 1rad / s;

[0037] The preset angles may include: 0°, -5°, 5°, -10°, 10°…, and it is not recommended to exceed 30°.

[0038] In the embodiment of the present application, multi-perspective improves the stability of parameters, wherein the stability of parameter estimation is related to the condition number of the matrix. In camera calibration, the parameters to be estimated include focal length, optical center, distortion coefficient, rotation matrix, and translation vector, etc. The calibration process is essentially a least squares problem, the goal of which is to minimize the projection error of feature points. By shooting from multiple angles, the position and posture of the calibration plate in the camera coordinate system are constantly changing, which is equivalent to increasing the independence of the conditional equations, thereby improving the condition number of the system of equations. A better condition number means that when solving these equations, the solution is more stable and accurate, avoiding numerical instability caused by uneven distribution of input data.

[0039] During the camera calibration process, images taken at different angles are collected to accurately estimate the camera's intrinsic parameters (such as focal length, optical center, distortion coefficient) and extrinsic parameters (for example, the camera's posture). Images taken at different angles help ensure the accuracy and robustness of the calibration results.

[0040] Step S104, when polling of stationary points in the preset calibration environment is completed, feature extraction is performed based on calibration images of at least three stationary points to obtain feature data;

[0041] Specifically, in the embodiment of the present application, feature extraction based on the calibration images of at least three stationary points includes:

[0042] 1. Image preprocessing:

[0043] 1.1 Grayscale conversion: converting the input color image (i.e., the calibration image in the embodiment of the present application) into a grayscale image;

[0044] 1.2 Thresholding and edge detection: The grayscale image is binarized using an adaptive thresholding method to highlight the edges of the checkerboard (i.e., the image content captured in the calibration image in the embodiment of the present application, such as QR codes, checkerboards, etc. used for calibration).

[0045] 2. Pattern Detection

[0046] 2.1 Shape detection: In the binary image, find the contour with checkerboard features, usually a rectangular contour with four corners, which is recognized as a checkerboard square;

[0047] 2.2 Corner point extraction: By analyzing the rectangular outline, find the intersection point of each square, where the intersection point is the inner corner point of the chessboard. The inner corner point is the intersection point of four adjacent squares inside the chessboard, not the corner point outside the chessboard.

[0048] 3. Verification and optimization

[0049] 3.1 Pattern matching: The extracted corner points are matched according to the preset number of checkerboard corner points (patternSize) to verify whether they conform to the expected checkerboard pattern. If the number and position of the corner points found match the expected pattern, the detection is considered successful.

[0050] 3.2 Sub-pixel accuracy: In order to improve the detection accuracy, pixel interpolation methods (such as cornerSubPix) are usually used to further optimize the position of corner points. This step can make the detection accuracy of corner points reach the sub-pixel level.

[0051] 4. Output: If the detection is successful, the function returns the two-dimensional coordinates of these corner points, and these corner points are arranged from left to right and from top to bottom.

[0052] Step S106, performing internal parameter calculation through the image acquisition device according to the feature data to obtain the calculation result, and the automatic calibration is completed.

[0053] Specifically, in the embodiment of the present application, the internal parameter calculation is performed by the image acquisition device based on the feature data, including:

[0054] 1. Initial estimation: After obtaining enough calibration images, the direct linear transformation (DLT) method is used for initial estimation. The goal of this stage is to make a preliminary estimate of the camera's intrinsic and extrinsic parameters (the rotation and translation of the camera relative to the world coordinate system). Among them, the extrinsic parameters include: rotation matrix and translation vector.

[0055] 2. Optimization process: Based on the initial estimation, iterative optimization is performed. The goal of the optimization process is to further accurately estimate the camera's intrinsic parameters, distortion coefficients, and extrinsic parameters by minimizing the image projection error.

[0056] Projection error: refers to the difference between the actual image position of the feature point and the image position calculated by the calibration model.

[0057] Least squares method: Minimize the sum of squares of errors in all images. Through iteration, the algorithm continuously adjusts the camera parameters so that the projection error gradually decreases and eventually reaches a stable minimum.

[0058] 3. Output results: After the optimization is completed, the camera's intrinsic parameter matrix, distortion coefficient, rotation and translation matrices corresponding to each image, and the final projection error are output.

[0059] Optionally, after obtaining the calculation results, the method for automatic camera calibration provided in the embodiment of the present application further includes: storing the calculation results in an image acquisition device.

[0060] Specifically, after the stationary polling is completed, the camera obtains N images, extracts features from the images, and calculates internal parameters through the camera model to obtain the internal parameters and write them into the camera's internal storage (i.e., the calculation results are stored in the image acquisition device in the embodiment of the present application).

[0061] In summary, in combination with step S102 to step S106, Figure 2 A schematic diagram of a camera automatic calibration method provided by an embodiment of the present invention is shown as follows: Figure 2 As shown, the method for automatic camera calibration provided in the embodiment of the present application may specifically be:

[0062] In the present application, the calibration content is: internal reference (f x , f y , c x , c y , k1, k2), where f x , f y is the focal length of the camera; c x , c y is the offset of the optical center of the camera relative to the origin of the image coordinate system; k1 and k2 are distortion coefficients, where the calibration distortion coefficients can correct abnormal distortion of the image.

[0063] In the embodiment of the present application, the calibrated camera model can be: Jiazhi camera, and the depth of field of the camera is about 10cm.

[0064] During the calibration environment layout:

[0065] According to the depth of field of the camera, the distance between the conveyor belt and the screen is adjusted to 0.1m. The QR code image remains unchanged during the calibration process.

[0066] The QR code array is displayed on the monitor. The real size of the QR code after display can be obtained through the resolution of the monitor and the pixel size of the displayed QR code. Currently, a 2560*1440 resolution monitor is used, and the screen size is 27 inches.

[0067] Therefore, the actual size of a single pixel = 0.0254 / (std::sqrt(2560*2560+1440*1440) / 27) = 0.0002334m,

[0068] The QR code uses Apriltag QR code, the pixel size of the QR code is 70*70, the actual size after display is 0.01634m*0.01634m, and the interval between QR codes is 20 pixels, that is, the actual interval size between QR codes is 0.004668m.

[0069] Three stationary points are set on the conveyor belt with a spacing of 0.1m;

[0070] Calibration process:

[0071] Place the camera on the device. The conveyor moves at a speed of 1m / s. After moving to the next stationary point, a new camera can be placed at the first stationary point. The dwell time is 5s.

[0072] Each time a stationary point is reached, the camera captures a frame of image;

[0073] The camera device rotates at each stationary point at angles (rotation speed 1 rad / s) of 0°, -5°, and 5°;

[0074] After the stationary polling is completed, the camera obtains 3 images, extracts features from the images, and calculates internal parameters through the camera model to obtain the internal parameters (f x , f y , c x , c y , k1, k2) and write them into the camera's internal storage.

[0075] The method for automatic camera calibration provided in the embodiment of the present application solves the problems of time-consuming, labor-intensive, inefficient and poor consistency of calibration results in the traditional camera calibration method by arranging the calibration environment automatically: using the QR code array displayed on the display, combined with the display resolution and the QR code pixel size, the real size of the QR code is automatically calculated to ensure that the QR code image covers all positions of the camera image during the calibration process. By adjusting the distance between the conveyor belt and the screen: according to the depth of field of the camera, the distance between the conveyor belt and the screen is adjusted so that the size of the QR code adapts to the distance, ensuring that the camera can clearly capture the QR code image. By setting multiple stationary points and rotation angles: multiple stationary points are set on the conveyor belt, and each stationary point camera device rotates a fixed angle after arriving to ensure that image data is obtained from different directions, thereby increasing the comprehensiveness and accuracy of the calibration. By automated acquisition and processing: the conveyor belt moves at a fixed speed, and the camera acquires images after arriving at each stationary point. The automated process reduces manual intervention and improves the efficiency and consistency of the calibration. Finally, feature extraction and internal parameter calculation are performed: feature extraction is performed on the collected image, and then the internal parameters, including focal length, center offset and distortion coefficient, are calculated using the camera model, and the calculation results are written into the camera's internal storage. Among them, the pipeline calibration method is adopted: the entire calibration process adopts pipeline operation, and the standardization and automation of the calibration process are ensured through a systematic method, thus solving the efficiency and consistency problems in traditional calibration methods.

[0076] Based on the above, the method for automatic camera calibration provided in the embodiment of the present application realizes the automation and standardization of the camera calibration process, improves the efficiency and accuracy of the calibration, and reduces the errors caused by human factors.

[0077] An embodiment of the present invention provides a method for automatic calibration of a camera, wherein an image acquisition device installed on a conveyor belt is used to acquire calibration images of at least three stationary points in a preset calibration environment when the conveyor belt is in motion; when polling of the stationary points in the preset calibration environment is completed, feature extraction is performed based on the calibration images of the at least three stationary points to obtain feature data; internal parameter calculation is performed based on the feature data through the image acquisition device to obtain a calculation result, and the automatic calibration is completed, thereby achieving a technical effect of improving the efficiency and accuracy of calibration.

[0078] The embodiment of the present invention provides a device for automatic calibration of a camera. Figure 3 A schematic diagram of a camera automatic calibration device provided by an embodiment of the present invention; Figure 3 As shown, the camera automatic calibration device provided in the embodiment of the present application includes:

[0079] The acquisition module 32 is used to acquire calibration images of at least three stationary points in a preset calibration environment when the conveyor belt is in motion through an image acquisition device installed on the conveyor belt; the extraction module 34 is used to extract features based on the calibration images of at least three stationary points to obtain feature data when the polling of the stationary points in the preset calibration environment is completed; the calculation module 36 is used to perform internal parameter calculation based on the feature data through the image acquisition device to obtain the calculation result, and the automatic calibration is completed.

[0080] Optionally, the preset calibration environment includes: at least three stationary points, wherein each stationary point is provided with a display, the display being used to display the identification code array; the distance between the display and the conveyor belt is determined according to the depth of field of the image acquisition device; wherein the size of the identification code in the identification code array is adjusted according to the distance, and the image size of the identification code remains unchanged during the calibration process; the conveyor belt is provided with a structure for fixing the image acquisition device, the structure being used to fix the image acquisition device, and when the conveyor belt moves to each stationary point, the image acquisition device is rotated according to a preset angle.

[0081] Optionally, the acquisition module 32 includes: an acquisition unit, which is used to control the conveyor belt to move at a preset speed, and when the image acquisition device installed on the conveyor belt moves to the position of each stationary point, the identification code array displayed on the display at each stationary point is acquired to obtain a calibration image.

[0082] Further, optionally, the apparatus for automatic camera calibration provided in the embodiment of the present application further includes: a rotation module, used to control the image acquisition device to rotate sequentially at preset angles according to a preset rotation speed at each stationary position.

[0083] Optionally, the apparatus for automatic camera calibration provided in the embodiment of the present application further includes: a storage module, for storing the calculation results in the image acquisition device after the calculation results are obtained.

[0084] An embodiment of the present invention provides a device for automatic calibration of a camera. The device collects calibration images of at least three stationary points in a preset calibration environment when the conveyor belt is in motion through an image acquisition device installed on the conveyor belt. When the polling of the stationary points in the preset calibration environment is completed, feature extraction is performed based on the calibration images of the at least three stationary points to obtain feature data. Internal parameter calculation is performed through the image acquisition device based on the feature data to obtain a calculation result, and the automatic calibration is completed, thereby achieving a technical effect of improving the efficiency and accuracy of calibration.

[0085] The above are only preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention.

Claims

1. A method for automatic camera calibration, characterized in that: include: By means of an image acquisition device installed on the conveyor belt, calibration images of at least three stationary points in a preset calibration environment are acquired when the conveyor belt is in motion; When polling of the stationary points in the preset calibration environment is completed, feature extraction is performed according to the calibration images of the at least three stationary points to obtain feature data; The image acquisition device is used to perform internal parameter calculation based on the feature data to obtain a calculation result, and the automatic calibration is completed.

2. The method for automatic camera calibration according to claim 1, characterized in that: The preset calibration environment includes: At least three stationary points, wherein each stationary point is provided with a display; The display is used to display the identification code array; The distance between the display and the conveyor belt is determined according to the depth of field of the image acquisition device; wherein the size of the identification code in the identification code array is adjusted according to the distance, and the image size of the identification code remains unchanged during the calibration process; The conveyor belt is provided with a structure for fixing the image acquisition device, and the structure is used to fix the image acquisition device and rotate the image acquisition device according to a preset angle when the conveyor belt moves to each stationary point.

3. The method for automatic camera calibration according to claim 1 or 2, characterized in that: The step of collecting calibration images of at least three stationary points in a preset calibration environment when the conveyor belt is moving by an image acquisition device installed on the conveyor belt comprises: The conveyor belt is controlled to move at a preset speed, and the image acquisition device installed on the conveyor belt moves to the position of each stationary point, and the identification code array displayed on the display at each stationary point is acquired to obtain the calibration image.

4. The method for automatic camera calibration according to claim 3, characterized in that: The method further comprises: The image acquisition device is controlled to rotate in sequence at preset angles at each stationary point according to a preset rotation speed.

5. The method for automatic camera calibration according to claim 1, characterized in that: After obtaining the calculation result, the method further includes: The calculation result is stored in the image acquisition device.

6. A camera automatic calibration device, characterized in that: include: A collection module, used for collecting calibration images of at least three stationary points in a preset calibration environment when the conveyor belt is moving, through an image collection device installed on the conveyor belt; An extraction module, configured to extract features from the calibration images of the at least three stationary points to obtain feature data when polling of the stationary points in the preset calibration environment is completed; The calculation module is used to perform internal parameter calculation through the image acquisition device according to the feature data to obtain the calculation result, and the automatic calibration is completed.

7. The camera automatic calibration device according to claim 6, characterized in that: The preset calibration environment includes: At least three stationary points, each stationary point being provided with a display, The display is used to display the identification code array; The distance between the display and the conveyor belt is determined according to the depth of field of the image acquisition device; wherein the size of the identification code in the identification code array is adjusted according to the distance, and the image size of the identification code remains unchanged during the calibration process; The conveyor belt is provided with a structure for fixing the image acquisition device, and the structure is used to fix the image acquisition device and rotate the image acquisition device according to a preset angle when the conveyor belt moves to each stationary point.

8. The camera automatic calibration device according to claim 6 or 7, characterized in that: The acquisition module comprises: The acquisition unit is used to control the conveyor belt to move at a preset speed, and when the image acquisition device installed on the conveyor belt moves to the position of each stationary point, the identification code array displayed on the display at each stationary point is acquired to obtain the calibration image.

9. The camera automatic calibration device according to claim 8, characterized in that: The device also includes: The rotation module is used to control the image acquisition device to rotate in sequence at the respective stationary positions at preset angles according to a preset rotation speed.

10. The camera automatic calibration device according to claim 6, characterized in that: The device also includes: A storage module is used to store the calculation result in the image acquisition device after the calculation result is obtained.

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