Binocular camera parameter adjustment method, device, system and storage medium

Abstract

The present application provides a method for adjusting binocular camera parameters, including: loading fixed marker point parameters, fixed marker points include plane marker points and stereo marker points; collecting plane marker point images and stereo marker point images; performing grayscale value detection on the plane marker point images, and coarsely adjusting the fixed marker point parameters according to the grayscale value detection results; performing feature extraction on the stereo marker point images to obtain stitching accuracy, and fine-tuning the fixed marker point parameters according to the stitching accuracy. The present application can adjust the camera exposure and gain parameters in real time according to the real-time situation, can take into account the brightness of different positions in space to ensure that it is in the optimal state, can effectively improve the efficiency of the system, has very low experience requirements for personnel using the equipment, and improves the system tracking smoothness and accuracy. The present invention can improve the accuracy of scanner shooting marker points, further increase the scanning accuracy of the scanner, and can also improve tracking accuracy, and has great practical value.

Description

Technical Field

[0001] The present invention relates to the technical field of camera parameter adjustment, and in particular to a binocular camera parameter adjustment method, device, system and storage medium. Background Art

[0002] The current camera adjustment mechanism is to pre-set camera parameters or manually adjust camera parameters according to the real-time scene. This manual adjustment requires rich operating experience.

[0003] In related technologies, handheld binocular measurement systems require manual adjustments to camera exposure and gain parameters by pressing buttons on the system. Tracking binocular measurement systems also require pre-adjustment of camera exposure and gain parameters by pressing buttons on the system. Existing technologies are unable to adjust these parameters in real time based on real-time conditions. The tracker shutter can only be manually determined by image acquisition, and it is impossible to determine and set it individually for different distances and positions. Typically, a single tracker shutter is used for the entire tracking area, failing to ensure optimal brightness at different locations in the space. Manual parameter adjustment significantly impacts system efficiency and requires highly experienced personnel, impacting the smoothness and accuracy of system tracking. Summary of the Invention

[0004] The purpose of the present invention is to overcome the above-mentioned technical deficiencies and provide a method, device, system and storage medium for adjusting binocular camera parameters to solve the technical problem that the manual adjustment of parameters in the prior art seriously affects the efficiency of the system.

[0005] To achieve the above technical objectives, in a first aspect, the technical solution of the present invention provides a method for adjusting binocular camera parameters, comprising the following steps:

[0006] Loading fixed marker point parameters, wherein the fixed marker points include plane marker points and three-dimensional marker points;

[0007] Collecting planar marker point images and three-dimensional marker point images;

[0008] Performing grayscale value detection on the plane marker point image, and roughly adjusting the fixed marker point parameters according to the grayscale value detection result;

[0009] Feature extraction is performed on the three-dimensional marker point image to obtain a splicing accuracy, and the fixed marker point parameters are fine-tuned according to the splicing accuracy.

[0010] Compared with the prior art, the present invention has the following beneficial effects:

[0011] The present invention provides a binocular camera parameter adjustment method that can adjust camera exposure and gain parameters in real time based on real-time conditions. This method can ensure optimal brightness at different locations in space, effectively improving system efficiency while minimizing user experience. It also enhances system tracking fluency and accuracy. This method can improve the accuracy of scanners capturing landmarks, further increasing scanning accuracy and tracking accuracy, thus possessing excellent practical value.

[0012] According to some embodiments of the present invention, performing grayscale value detection on the planar marker point image includes the steps of:

[0013] Performing thresholding processing on the plane marker point image to obtain a binary image as a mask;

[0014] Connected domain analysis is performed on pixels in the binary image that exceed a preset threshold, and the average grayscale value of a single connected domain is counted.

[0015] According to some embodiments of the present invention, the fixed marker point parameters are roughly adjusted according to the gray value detection result, including the steps of:

[0016] The camera parameters and LED duration parameters are roughly adjusted so that the average grayscale value of the connected domain in the planar marker point image is within a preset range.

[0017] According to some embodiments of the present invention, the calculation process of the average gray value is:

[0018] The number of pixels P(x,y) in the connected domain {U|(x,y)} is N, and the number of pixels of the original image corresponding to the connected domain U is {S U |(x,y)}, the grayscale average is

[0019] According to some embodiments of the present invention, performing feature extraction on the stereoscopic marker point image to obtain a stitching accuracy includes the steps of:

[0020] Performing ellipse feature extraction on the three-dimensional marker point image to obtain an ellipse feature;

[0021] The ellipse features are randomly spliced ​​to obtain a splicing evaluation index, and the splicing accuracy is calculated based on the splicing evaluation index.

[0022] According to some embodiments of the present invention, fine-tuning the fixed marker point parameters according to the stitching accuracy includes the steps of:

[0023] The camera parameters and LED duration parameters are fine-tuned according to the stitching accuracy.

[0024] According to some embodiments of the present invention, the stitching evaluation index includes: stitching tracker accuracy and stitching valid points.

[0025] In a second aspect, the present invention provides a binocular camera parameter adjustment device, comprising:

[0026] A parameter loading unit, used to load parameters of fixed marker points, wherein the fixed marker points include planar marker points and three-dimensional marker points;

[0027] An image acquisition unit, used for acquiring planar marker point images and three-dimensional marker point images;

[0028] a coarse adjustment unit, configured to perform grayscale value detection on the planar marker point image and coarsely adjust the fixed marker point parameters according to the grayscale value detection result;

[0029] A fine-tuning unit is used to extract features from the three-dimensional marker point image to obtain a stitching accuracy, and to fine-tune the fixed marker point parameters according to the stitching accuracy.

[0030] In a third aspect, the present invention provides a binocular camera parameter adjustment system, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the binocular camera parameter adjustment method according to any one of the first aspects is implemented.

[0031] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are used to enable a computer to execute the binocular camera parameter adjustment method as described in any one of the first aspects.

[0032] Additional aspects and advantages of the present invention will be set forth in part in the description which follows and, in part, will be obvious from the description which follows, or may be learned by practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, wherein the abstract drawing is identical to one of the drawings in the specification:

[0034] Figure 1 A flowchart of a binocular camera parameter adjustment method provided by one embodiment of the present invention;

[0035] Figure 2 A flowchart of a binocular camera parameter adjustment method provided by another embodiment of the present invention;

[0036] Figure 3 A planar marker point image of a binocular camera parameter adjustment method provided by another embodiment of the present invention;

[0037] Figure 4 A binary image of a binocular camera parameter adjustment method provided by another embodiment of the present invention;

[0038] Figure 5 A single original image of a marker point in a binocular camera parameter adjustment method provided by another embodiment of the present invention;

[0039] Figure 6 A single marker point binary image of a binocular camera parameter adjustment method provided by another embodiment of the present invention;

[0040] Figure 7 An original image after threshold processing of a single marker point in a binocular camera parameter adjustment method provided by another embodiment of the present invention;

[0041] Figure 8 A stereoscopic marker point image of a binocular camera parameter adjustment method provided by another embodiment of the present invention;

[0042] Figure 9 A diagram illustrating feature extraction of stereo marker images in a binocular camera parameter adjustment method according to another embodiment of the present invention;

[0043] Figure 10 A point set correspondence diagram of a binocular camera parameter adjustment method provided by another embodiment of the present invention;

[0044] Figure 11 A point set conversion diagram of a binocular camera parameter adjustment method provided by another embodiment of the present invention;

[0045] Figure 12 A distance error diagram of a binocular camera parameter adjustment method provided by another embodiment of the present invention. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0047] It should be noted that although the system diagrams illustrate functional module divisions and the flowcharts illustrate logical sequences, in certain circumstances, the steps shown or described may be performed in a sequence that differs from the module divisions in the system or the sequence in the flowcharts. The terms "first," "second," and so on, in the specification, claims, and drawings, are used to distinguish similar items and are not necessarily used to describe a specific sequence or precedence.

[0048] The present invention provides a binocular camera parameter adjustment method, which can improve the accuracy of scanner shooting mark points, further improve the scanner scanning accuracy, and also improve tracking accuracy, and has great practical value.

[0049] The embodiments of the present invention are further described below with reference to the accompanying drawings.

[0050] Reference Figure 1 , Figure 1 A flowchart of a binocular camera parameter adjustment method provided by one embodiment of the present invention; the binocular camera parameter adjustment method includes but is not limited to the following steps:

[0051] Step S110, loading fixed marker point parameters, where fixed marker points include planar marker points and three-dimensional marker points;

[0052] Step S120, collecting a planar marker point image and a three-dimensional marker point image;

[0053] Step S130, performing grayscale value detection on the plane marker point image, and roughly adjusting the fixed marker point parameters according to the grayscale value detection result;

[0054] Step S140 , extracting features from the three-dimensional marker point image to obtain stitching accuracy, and fine-tuning the fixed marker point parameters according to the stitching accuracy.

[0055] In one embodiment, a binocular camera parameter adjustment method includes: loading fixed marker point parameters, where the fixed marker points include planar marker points and stereo marker points; collecting planar marker point images and stereo marker point images; performing grayscale value detection on the planar marker point images, and coarsely adjusting the fixed marker point parameters based on the grayscale value detection results; performing feature extraction on the stereo marker point images to obtain stitching accuracy, and fine-tuning the fixed marker point parameters based on the stitching accuracy.

[0056] The binocular camera parameter adjustment method provided in this embodiment can adjust camera exposure and gain parameters in real time based on real-time conditions, ensuring optimal brightness at different locations in space. This method effectively improves system efficiency, requires minimal user experience, and enhances system tracking fluency and accuracy. This method can improve the accuracy of scanners capturing landmarks, further increasing scanning accuracy and tracking accuracy, thus possessing excellent practical value.

[0057] Reference Figure 2 , Figure 2 A flowchart of a binocular camera parameter adjustment method provided in another embodiment of the present invention; the binocular camera parameter adjustment method includes but is not limited to the following steps:

[0058] Step S210, performing thresholding processing on the plane marker point image to obtain a binary image as a mask;

[0059] Step S220 , performing connected domain analysis on pixels exceeding a preset threshold in the binary image, and calculating the average grayscale value of a single connected domain.

[0060] In one embodiment, a binocular camera parameter adjustment method includes: loading fixed marker point parameters, where fixed marker points include planar marker points and stereo marker points; acquiring planar marker point images and stereo marker point images; performing grayscale value detection on the planar marker point images and coarsely adjusting the fixed marker point parameters based on the grayscale value detection results; performing feature extraction on the stereo marker point images to obtain stitching accuracy, and fine-tuning the fixed marker point parameters based on the stitching accuracy. Grayscale value detection on the planar marker point images includes the steps of: thresholding the planar marker point images to obtain a binary image as a mask; performing connected domain analysis on pixels in the binary image that exceed a preset threshold, and calculating the average grayscale value of each connected domain.

[0061] Reference Figures 3 to 7 , Figure 3 A planar marker point image of a binocular camera parameter adjustment method provided by another embodiment of the present invention; Figure 4 A binary image of a binocular camera parameter adjustment method provided by another embodiment of the present invention; Figure 5 A single original image of a marker point in a binocular camera parameter adjustment method provided by another embodiment of the present invention; Figure 6 A single marker point binary image of a binocular camera parameter adjustment method provided by another embodiment of the present invention; Figure 7 This is an original image after threshold processing of a single marker point in the binocular camera parameter adjustment method provided by another embodiment of the present invention.

[0062] In one embodiment, a binocular camera parameter adjustment method includes: loading fixed marker point parameters, where fixed marker points include planar marker points and stereo marker points; acquiring planar marker point images and stereo marker point images; performing grayscale value detection on the planar marker point images and coarsely adjusting the fixed marker point parameters based on the grayscale value detection results; performing feature extraction on the stereo marker point images to obtain stitching accuracy, and fine-tuning the fixed marker point parameters based on the stitching accuracy. Grayscale value detection on the planar marker point images includes the steps of: thresholding the planar marker point images to obtain a binary image as a mask; performing connected domain analysis on pixels in the binary image that exceed a preset threshold, and calculating the average grayscale value of each connected domain.

[0063] 1. Collect images of tablet marker points at different distances and angles;

[0064] 2. Perform thresholding on the image to obtain a binary image as a mask;

[0065] Thresholding formula:

[0066] X=0,X<T,X=255,X> =T

[0067] 3. Perform connected domain analysis on pixels exceeding the threshold and perform average grayscale statistics on a single connected domain;

[0068] 4. Adjust the camera parameters and LED duration parameters for rough adjustment so that the average grayscale value of the connected domain within the camera shooting area is in the range [T1, T2] (generally 200-220);

[0069] The process of calculating the average value is as follows:

[0070] Assuming that the number of pixels P(x,y) in the connected domain {U|(x,y)} is N, then the number of pixels of the original image corresponding to the connected domain U is {S U |(x,y)}

[0071] Grayscale average

[0072] In one embodiment, a binocular camera parameter adjustment method includes: loading fixed marker point parameters, where fixed marker points include planar marker points and stereo marker points; acquiring planar marker point images and stereo marker point images; performing grayscale value detection on the planar marker point images and roughly adjusting the fixed marker point parameters based on the grayscale value detection results; performing feature extraction on the stereo marker point images to obtain stitching accuracy, and fine-tuning the fixed marker point parameters based on the stitching accuracy. Grayscale value detection on the planar marker point images includes the steps of: thresholding the planar marker point images to obtain a binary image as a mask; performing connected domain analysis on pixels in the binary image that exceed a preset threshold, and calculating the average grayscale value of each connected domain. Based on the grayscale value detection results, the fixed marker point parameters are roughly adjusted, including the steps of: roughly adjusting the camera parameters and LED duration parameters so that the average grayscale value of the connected domain within the planar marker point images is within a preset range.

[0073] In one embodiment, a method for adjusting binocular camera parameters includes: loading fixed marker point parameters, where fixed marker points include planar marker points and stereo marker points; collecting planar marker point images and stereo marker point images; performing grayscale value detection on the planar marker point images, and coarsely adjusting the fixed marker point parameters based on the grayscale value detection results; performing feature extraction on the stereo marker point images to obtain stitching accuracy, and fine-tuning the fixed marker point parameters based on the stitching accuracy. Grayscale value detection on the planar marker point images includes the steps of: thresholding the planar marker point images to obtain a binary image as a mask; performing connected domain analysis on pixels in the binary image that exceed a preset threshold, and calculating the average grayscale value of a single connected domain. The average grayscale value calculation process is as follows:

[0074] The number of pixels P(x,y) in the connected domain {U|(x,y)} is N, and the number of pixels of the original image corresponding to the connected domain U is {S U |(x,y)}, the grayscale average is

[0075] Reference Figures 8 to 12 , Figure 8 A stereoscopic marker point image of a binocular camera parameter adjustment method provided by another embodiment of the present invention; Figure 9 A diagram illustrating feature extraction of stereo marker images in a binocular camera parameter adjustment method according to another embodiment of the present invention; Figure 10 A point set correspondence diagram of a binocular camera parameter adjustment method provided by another embodiment of the present invention; Figure 11 A point set conversion diagram of a binocular camera parameter adjustment method provided by another embodiment of the present invention; Figure 12 A distance error diagram of a binocular camera parameter adjustment method provided by another embodiment of the present invention.

[0076] In one embodiment, a binocular camera parameter adjustment method includes: loading fixed marker point parameters, where the fixed marker points include planar marker points and stereo marker points; acquiring planar marker point images and stereo marker point images; performing grayscale value detection on the planar marker point images and coarsely adjusting the fixed marker point parameters based on the grayscale value detection results; performing feature extraction on the stereo marker point images to obtain stitching accuracy, and fine-tuning the fixed marker point parameters based on the stitching accuracy. Feature extraction on the stereo marker point images to obtain stitching accuracy includes the steps of: performing ellipse feature extraction on the stereo marker point images to obtain ellipse features; performing random stitching on the ellipse features to obtain a stitching evaluation index, and calculating the stitching accuracy based on the stitching evaluation index.

[0077] 1. Collect 3D landmark images at different distances and angles;

[0078] 2. Extract ellipse features from landmark images;

[0079] 3. Perform random splicing of ellipse features to obtain splicing evaluation. Generally, the splicing index is the tracker accuracy and the number of valid points. Specifically, there are two point sets V1 and V2. Assuming that they are one-to-one corresponding, after a rotation and translation transformation, they can obtain almost the same configuration; assuming that the point set V1 after the coordinate system transformation is recorded as V3, then the error between V3 and V2 is, and the distance error between the nearest neighbor points of V3 and V2 is t1~t6; then, the average splicing error is Adjust the camera parameters and LED duration parameters based on the stitching error RMS;

[0080] 4. Fine-tune the camera parameters and LED duration parameters according to the stitching accuracy.

[0081] In one embodiment, a binocular camera parameter adjustment method includes: loading fixed marker point parameters, where the fixed marker points include planar marker points and stereo marker points; acquiring planar marker point images and stereo marker point images; performing grayscale value detection on the planar marker point images and coarsely adjusting the fixed marker point parameters based on the grayscale value detection results; performing feature extraction on the stereo marker point images to obtain stitching accuracy, and fine-tuning the fixed marker point parameters based on the stitching accuracy. Feature extraction on the stereo marker point images to obtain stitching accuracy includes the steps of: performing elliptical feature extraction on the stereo marker point images to obtain elliptical features; performing random stitching on the elliptical features to obtain a stitching evaluation index, and calculating the stitching accuracy based on the stitching evaluation index. Fine-tuning the fixed marker point parameters based on the stitching accuracy includes the steps of: fine-tuning the camera parameters and LED duration parameters based on the stitching accuracy.

[0082] In one embodiment, a binocular camera parameter adjustment method includes: loading fixed marker point parameters, where the fixed marker points include planar marker points and stereo marker points; collecting planar marker point images and stereo marker point images; performing grayscale value detection on the planar marker point images, and coarsely adjusting the fixed marker point parameters based on the grayscale value detection results; performing feature extraction on the stereo marker point images to obtain stitching accuracy, and fine-tuning the fixed marker point parameters based on the stitching accuracy. Feature extraction on the stereo marker point images to obtain stitching accuracy includes the steps of: performing ellipse feature extraction on the stereo marker point images to obtain ellipse features; performing random stitching on the ellipse features to obtain a stitching evaluation index, and calculating the stitching accuracy based on the stitching evaluation index. The stitching evaluation index includes: stitching tracker accuracy and the number of effective stitching points.

[0083] The present invention also provides a binocular camera parameter adjustment device, including: a parameter loading unit, used to load fixed marker point parameters, the fixed marker points include plane marker points and stereo marker points; an image acquisition unit, used to acquire plane marker point images and stereo marker point images; a coarse adjustment unit, used to perform grayscale value detection on the plane marker point image, and coarsely adjust the fixed marker point parameters according to the grayscale value detection result; a fine adjustment unit, used to perform feature extraction on the stereo marker point image to obtain splicing accuracy, and fine-tune the fixed marker point parameters according to the splicing accuracy.

[0084] The present invention also provides a binocular camera parameter adjustment system, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the binocular camera parameter adjustment method described above is implemented.

[0085] The processor and the memory may be connected via a bus or other means.

[0086] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0087] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, i.e., they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.

[0088] In addition, an embodiment of the present invention further provides a computer-readable storage medium, which stores computer-executable instructions. The computer-executable instructions are executed by a processor or controller, for example, by a processor in the above-mentioned terminal embodiment, so that the above-mentioned processor can execute the binocular camera parameter adjustment method in the above-mentioned embodiment.

[0089] Those skilled in the art will appreciate that all or some of the steps and systems in the method disclosed above can be implemented as software, firmware, hardware, and appropriate combinations thereof. Some physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, and the computer-readable medium can include computer storage media (or non-transitory media) and communication media (or temporary media). As known to those skilled in the art, the term computer storage media is included in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data) and is volatile and non-volatile, removable, and non-removable. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory, or other memory technology, CD-ROM, digital versatile disks (DVD), or other optical disk storage, magnetic cassettes, magnetic tapes, disk storage, or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, as is well known to those skilled in the art, communication media typically embodies computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0090] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the above implementation. Those skilled in the art can make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present invention.

[0091] The specific embodiments of the present invention described above do not limit the scope of protection of the present invention. Any other corresponding changes and modifications made based on the technical concept of the present invention should be included in the scope of protection of the claims of the present invention.

Claims

1. A binocular camera parameter adjustment method, characterized in that: The following steps are involved: Loading fixed marker point parameters, wherein the fixed marker points include plane marker points and three-dimensional marker points; Collecting planar marker point images and three-dimensional marker point images; Performing grayscale value detection on the plane marker point image, and roughly adjusting the fixed marker point parameters according to the grayscale value detection result; Extracting features from the three-dimensional marker point image to obtain a stitching accuracy, and fine-tuning the fixed marker point parameters according to the stitching accuracy; The fixed marker point parameters are roughly adjusted according to the grayscale value detection result, including the steps of: Coarsely adjusting the camera parameters and LED duration parameters so that the average grayscale value of the connected domain in the planar marker point image is within a preset range; Extracting features from the three-dimensional marker point image to obtain stitching accuracy includes the following steps: Performing ellipse feature extraction on the three-dimensional marker point image to obtain an ellipse feature; Performing disordered splicing on the ellipse features to obtain a splicing evaluation index, and calculating the splicing accuracy according to the splicing evaluation index; Fine-tuning the fixed marker point parameters according to the stitching accuracy includes the following steps: The camera parameters and LED duration parameters are fine-tuned according to the stitching accuracy.

2. The binocular camera parameter adjustment method according to claim 1, wherein: Grayscale value detection is performed on the plane marker point image, comprising the steps of: Performing thresholding processing on the plane marker point image to obtain a binary image as a mask; Connected domain analysis is performed on pixels in the binary image that exceed a preset threshold, and the average grayscale value of a single connected domain is counted.

3. The binocular camera parameter adjustment method according to claim 2, characterized in that: The calculation process of the average gray value is: The number of pixels P(x,y) in the connected domain {U|(x,y)} is N, and the number of pixels of the original image corresponding to the connected domain U is {S U |(x,y)}, the grayscale average is .

4. The binocular camera parameter adjustment method according to claim 1, wherein: The stitching evaluation index includes: stitching tracker accuracy and stitching effective points.

5. A binocular camera parameter adjustment device, characterized in that: include: A parameter loading unit, used to load parameters of fixed marker points, wherein the fixed marker points include planar marker points and three-dimensional marker points; An image acquisition unit, used for acquiring planar marker point images and three-dimensional marker point images; a coarse adjustment unit, configured to perform grayscale value detection on the planar marker point image and coarsely adjust the fixed marker point parameters according to the grayscale value detection result; a fine-tuning unit, configured to extract features from the stereoscopic marker point image to obtain a stitching accuracy, and fine-tune the fixed marker point parameters according to the stitching accuracy; The fixed marker point parameters are roughly adjusted according to the grayscale value detection result, including: Coarsely adjusting the camera parameters and LED duration parameters so that the average grayscale value of the connected domain in the planar marker point image is within a preset range; Extracting features from the three-dimensional marker point image to obtain stitching accuracy includes: Performing ellipse feature extraction on the three-dimensional marker point image to obtain an ellipse feature; Performing disordered splicing on the ellipse features to obtain a splicing evaluation index, and calculating the splicing accuracy according to the splicing evaluation index; Fine-tuning the fixed marker point parameters according to the stitching accuracy includes: The camera parameters and LED duration parameters are fine-tuned according to the stitching accuracy.

6. A binocular camera parameter adjustment system, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the binocular camera parameter adjustment method according to any one of claims 1 to 4 when executing the computer program.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the binocular camera parameter adjustment method according to any one of claims 1 to 4.

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