Binocular vision early warning ranging system parameter acquisition method and equipment, computer equipment and medium

Abstract

The embodiment of the invention provides a binocular vision early warning distance measurement system parameter acquisition method and device, computer equipment and a medium, and relates to the technical field of binocular computer vision distance measurement systems, and the acquisition method comprises the steps: carrying out the camera baseline selection; carrying out camera image sensor pixel size selection; obtaining the constraint of the focal length of a camera lens according to the obtained camera baseline and the image element size of the camera image sensor; determining an image resolution constraint; if the design requirements are not met, the above steps are repeated for iteration until the design requirements of the binocular vision early warning ranging system are met; and comprehensively weighing all the parameter groups meeting the design requirements to obtain an optimal parameter group. According to the invention, design steps and calculation formulas of the parameters and a basic type selection principle are given, a priority order for determining the parameters and an evaluation method for the distance measurement distance and the distance measurement precision are provided, and the parameters required by a whole set of binocular vision distance measurement system are obtained.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of binocular computer vision ranging system, and particularly relates to a binocular vision early warning ranging system parameter acquisition method, equipment, computer device and medium. BACKGROUND

[0002] The binocular vision ranging system is a system that simulates human binocular stereo vision. By acquiring left and right images of the same scene, the parallax of corresponding points in the images is calculated to calculate the distance of the object to the camera. This technology has a wide range of applications in robot navigation, unmanned aerial vehicles, augmented reality and other fields.

[0003] In the low-altitude economy field, the flight speed of low-altitude aircraft is generally much higher than that of cars. The current vehicle-mounted laser radar early warning ranging distance of 300m cannot meet the needs of low-altitude collision avoidance warning. Kilometer-level ranging laser radars generally have the disadvantages of high cost and low frame rate. The flight platform generally provides a larger camera baseline than the car platform, which makes it possible to achieve kilometer-level ranging of binocular vision.

[0004] The basic principle of binocular vision ranging is triangulation. By knowing the baseline length (the distance between the optical centers of the left and right cameras) and the parallax, the distance of the object to the camera can be calculated.

[0005] The composition of the binocular vision ranging system generally includes: (1) camera body: two cameras with the same parameters, used to acquire left and right images of the same scene at the same time. (2) lens: used to combine with the camera body to form a complete camera system, providing an optical path. (3) baseline: the horizontal distance between the two parallel cameras, analogous to the interpupillary distance of the human eye.

[0006] The working process of the binocular vision ranging system includes camera calibration: determining the intrinsic parameters (focal length, principal point, etc.) and extrinsic parameters (rotation matrix, translation vector) of the camera. Image correction: correcting the collected images to eliminate lens distortion and geometric differences between images. Feature extraction and matching: extracting feature points in left and right images and matching them to find corresponding points. Parallax calculation: calculating the parallax according to the corresponding points obtained by matching. Depth map generation: calculating the depth map according to the parallax and camera parameters, i.e. the depth information corresponding to each pixel.

[0007] The binocular vision ranging system has important research value and application prospect in the field of computer vision. The main application fields of the binocular vision ranging system are: (1) robot navigation: realizing autonomous navigation, obstacle avoidance and other functions. (2) unmanned aerial vehicles: performing three-dimensional reconstruction, target tracking and other tasks. (3) augmented reality: superimposing virtual objects onto real scenes. (4) industrial measurement: three-dimensional measurement, defect detection, etc.

[0008] However, research on binocular vision systems mainly focuses on areas such as stereo matching, disparity calculation, and image processing. For the overall design of the binocular vision system itself, there is currently a lack of a parametric design method. Setting parameters based solely on experience is not accurate. Summary of the Invention

[0009] In view of this, embodiments of the present invention provide a method for acquiring parameters of a binocular vision early warning ranging system, outlining design steps and calculation formulas, basic selection principles, prioritizing parameter determination, and methods for evaluating ranging distance and accuracy. This includes: The camera baseline is selected based on the size of the transport platform, the limitations of the reserved installation space, and the intended ranging distance. The camera image sensor pixel size is selected based on the ranging distance, lighting conditions, and the platform's image processing capabilities. The camera lens focal length constraint is obtained based on the aforementioned camera baseline and camera image sensor pixel size; The image resolution constraint is determined based on the focal length constraint, ranging distance, required field of view, and given field of view requirements. The constraints of the camera baseline, camera image sensor pixel size, camera lens focal length, and image resolution obtained above are verified. If the design requirements are not met, the above steps are repeated for iteration until the design requirements of the binocular vision early warning ranging system are met. By comprehensively weighing all the parameter sets that meet the design requirements, the optimal parameter set is obtained.

[0010] The binocular vision early warning ranging system parameter acquisition method proposed in this invention also has the following technical features: the camera baseline selection based on the size of the carrier platform, the reserved installation space limit, and the intended ranging distance includes: the camera baseline is less than 1 / 3 of the intended ranging distance.

[0011] The parameter acquisition method for the binocular vision early warning ranging system proposed in this invention also has the following technical feature: the constraint of obtaining the camera lens focal length based on the aforementioned acquired camera baseline and camera image sensor pixel size includes: The camera lens focal length is constrained based on the camera baseline and the camera image sensor pixel size, combined with the ranging distance, parallax error, and error rate index.

[0012] The parameter acquisition method for the binocular vision early warning ranging system proposed in this invention also has the following technical features: the step of obtaining the constraint on the camera lens focal length based on the camera baseline and the pixel size of the camera image sensor, combined with the ranging distance, parallax error, and error rate index value, includes: The constraint on the camera lens focal length f is:

[0013] in, D For measuring distance, For parallax error, b is the pixel size of the image sensor, and b is the baseline distance of the stereo camera. Given the error rate.

[0014] The parameter acquisition method for the binocular vision early warning ranging system proposed in this invention also has the following technical features: determining the image resolution constraint based on focal length constraints, ranging distance, required field of view, and given field of view requirements includes: horizontal resolution of the image M for:

[0015] Image vertical resolution N for:

[0016] in, f For camera lens focal length, For image sensor pixel size, For the horizontal field of view required by the mission, The horizontal field of view is the required parameter for the mission.

[0017] The parameter acquisition method for the binocular vision early warning ranging system proposed in this invention also has the following technical features: f To select the minimum focal length that satisfies the constraints based on the camera lens focal length constraints and the actual specifications of the selected lens focal length.

[0018] The parameter acquisition method for the binocular vision early warning ranging system proposed in this invention also has the following technical feature: the step of comprehensively weighing all the parameter sets that meet the design requirements to obtain the optimal parameter set includes: Using a weighted scoring method, the score of the i-th qualified solution is:

[0019] in, For weighting coefficients, , The score is based on the baseline distance; the smaller the required baseline distance, the higher the score. The score is based on pixel size; the smaller the pixel size, the higher the score. For focal length, the smaller the focal length, the higher the score. The score is for camera resolution; the higher the score, the better. The required parallax error is scored individually; the larger the score, the higher the score. The design error rate is scored individually; the smaller the score, the higher the score. The score is for the period cost item; the lower the score, the higher the score. Ultimately, the group with the highest score is the optimal parameter group.

[0020] Another object of the present invention is to provide a parameter acquisition device for a binocular vision early warning ranging system, comprising: The camera baseline acquisition module is used to select the camera baseline based on the size of the carrier platform, the reserved installation space limit, and the intended ranging distance; The camera image sensor pixel size acquisition module is used to select the camera image sensor pixel size based on the ranging distance, lighting conditions, and the platform's image computing and processing capabilities. The camera lens focal length constraint acquisition module is used to obtain the camera lens focal length constraint based on the aforementioned acquired camera baseline and camera image sensor pixel size. The image resolution constraint acquisition module is used to determine the image resolution constraint based on the focal length constraint, ranging distance, required field of view, and given field of view requirements. The verification module is used to verify the constraints of the camera baseline, camera image sensor pixel size, camera lens focal length and image resolution obtained above. If the design requirements are not met, the above steps are repeated for iteration until the design requirements of the binocular vision early warning ranging system are met. The comprehensive weighing module is used to comprehensively weigh all the parameter sets that meet the design requirements to obtain the optimal parameter set.

[0021] A third objective of this invention is to provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the parameter acquisition method for the binocular vision early warning ranging system described in any of the preceding claims.

[0022] A fourth objective of the present invention is to provide a computer-readable storage medium storing a method for acquiring parameters of a binocular vision early warning ranging system as described in any of the preceding claims.

[0023] Compared with the prior art, the beneficial effects that can be achieved by the above-mentioned at least one technical solution adopted in the embodiments of this specification include: providing the design steps and calculation formulas for these parameters as well as the basic selection principles, proposing the priority order for parameter determination and the evaluation methods for ranging distance and ranging accuracy, and obtaining a complete set of parameters required for a binocular vision ranging system. Attached Figure Description

[0024] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a flowchart of the method provided in the embodiments of the present invention; Figure 2 This is a structural block diagram of a computer device provided in an embodiment of the present invention; Figure 3 This is a structural block diagram of an acquisition device provided in an embodiment of the present invention. Detailed Implementation

[0026] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0027] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. This application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0028] In embodiments of the present invention, such as Figure 1 As shown, a method for acquiring parameters of a binocular vision early warning ranging system is provided, including: The camera baseline is selected based on the size of the transport platform, the limitations of the reserved installation space, and the intended ranging distance. The camera image sensor pixel size is selected based on the ranging distance, lighting conditions, and the platform's image processing capabilities. The camera lens focal length constraint is obtained based on the aforementioned camera baseline and camera image sensor pixel size; The image resolution constraint is determined based on the focal length constraint, ranging distance, required field of view, and given field of view requirements. The constraints of the camera baseline, camera image sensor pixel size, camera lens focal length, and image resolution obtained above are verified. If the design requirements are not met, the above steps are repeated for iteration until the design requirements of the binocular vision early warning ranging system are met. By comprehensively weighing all the parameter sets that meet the design requirements, the optimal parameter set is obtained.

[0029] In some embodiments, the step of selecting the camera baseline based on the size of the carrier platform, the reserved installation space limit, and the intended ranging distance includes: the camera baseline is less than 1 / 3 of the intended ranging distance.

[0030] In the above embodiments, the longer the camera baseline, the better. For kilometer-level ranging systems, the maximum size of the installation space that the carrier equipment can provide is generally taken.

[0031] In some embodiments, the selection of camera image sensor pixel size based on ranging distance, lighting conditions, and platform image computing and processing capabilities includes: the farther the ranging distance, the higher the required image resolution, and the smaller the image sensor pixel size, which can reduce dependence on the baseline and improve ranging accuracy. However, the smaller the image sensor size, the higher the requirements for lighting conditions. Under the condition of meeting the ranging requirements, a smaller pixel size is generally selected.

[0032] In some embodiments, the constraint of obtaining the camera lens focal length based on the aforementioned obtained camera baseline and camera image sensor pixel size includes: The camera lens focal length is constrained based on the camera baseline and the camera image sensor pixel size, combined with the ranging distance, parallax error, and error rate index.

[0033] In some embodiments, the step of obtaining the constraint on the camera lens focal length based on the camera baseline and the camera image sensor pixel size, combined with the ranging distance, parallax error, and error rate index, includes: Camera lens focal length f The constraints are:

[0034] in, D For measuring distance, For parallax error, For image sensor pixel size, b Baseline distance of binocular cameras, Given the error rate.

[0035] In the above embodiments, by given the ranging distance and error rate requirements, and combining the parallax error performance of the proposed parallax calculation algorithm, constraints on the lens focal length can be derived. Specifically: Firstly, based on the principle of binocular visual parallax ranging:

[0036] According to the error propagation theory, the following calculations are performed:

[0037] Further obtain the error rate :

[0038] For SGM and deep learning-based methods, disparity error is generally a concern. No larger than 0.5 pixels; generally, this value is taken based on algorithm performance. Pixels. Based on the error rate requirement, this is transferred to the camera focal length requirement to obtain... Constraints: , in, For measuring distance, For parallax, For parallax, For image sensor pixel size, Baseline distance of binocular cameras, For a given error rate, For error rate, ≤ For low-altitude ranging and collision avoidance missions, kilometer-level ranging is generally... .

[0039] In some embodiments, determining the image resolution constraint based on the focal length constraint, ranging distance, required field of view, and given field of view requirements includes: The horizontal resolution M of the image is:

[0040] The vertical resolution N of the image is:

[0041] in, f For camera lens focal length, For image sensor pixel size, For the horizontal field of view required by the mission, The horizontal field of view is the required parameter for the mission.

[0042] In the above embodiments, based on the focal length constraint and the actual focal length specifications of the lens for industrial products, the minimum focal length that satisfies the constraint is generally chosen. This is determined based on the ranging distance and the required field of view. The greater the ranging distance, the longer the required lens focal length. The wider the ranging angle range, the smaller the required lens focal length. Then, combined with the given field of view requirement, the image resolution constraint is derived. Specifically, as follows: The horizontal field of view of the image is:

[0043] If required ,in Given the horizontal field of view required by the task, the horizontal resolution of the image... have

[0044] Similarly, the vertical field of view of the image is:

[0045] If required ,in Given the horizontal field of view required by the task, the vertical resolution of the image is... have , in, For the horizontal resolution of the image sensor, f is the height resolution of the image sensor, and f is the focal length of the camera lens. For image sensor pixel size, The horizontal field of view of the camera. This is the camera's vertical field of view.

[0046] In some embodiments, f To select the minimum focal length that satisfies the constraints based on the camera lens focal length constraints and the actual specifications of the selected lens focal length.

[0047] In some embodiments, the step of comprehensively weighing all the parameter sets that meet the design requirements to obtain the optimal parameter set includes: Using a weighted scoring method, the score of the i-th qualified solution is:

[0048] in, For weighting coefficients, , The score is based on the baseline distance; the smaller the required baseline distance, the higher the score. The score is based on pixel size; the smaller the pixel size, the higher the score. For focal length, the smaller the focal length, the higher the score. The score is for camera resolution; the higher the score, the better. The required parallax error is scored individually; the larger the score, the higher the score. The design error rate is scored individually; the smaller the score, the higher the score. The score is for the period cost item; the lower the score, the higher the score. Ultimately, the group with the highest score is the optimal parameter group.

[0049] In some embodiments, for ranging distance baseline The binocular vision collision avoidance system should have a horizontal field of view greater than 25° and a vertical field of view greater than 15°, with a ranging error of less than 10%. The computing platform can only process binocular vision images with a resolution of 1920*1080 or less, achieving 20 frames per second.

[0050] Candidate solutions: Option 1, The first step is to obtain the baseline distance. ; The second step is to preset the pixel size. ; The third step is to preset the error rate according to the vision system requirements. Derive camera focal length constraints ; The fourth step is to select the appropriate lens based on the lens choice and image resolution estimation. ,but Pixels ; Step 5, Determination We can proceed to the sixth step of weighing the pros and cons.

[0051] Option 2, The first step is to obtain the baseline distance. ; The second step is to preset the pixel size. ; The third step is to preset the error rate according to the vision system requirements. Derive camera focal length constraints ; The fourth step is to select the appropriate lens based on the lens choice and image resolution estimation. ,but Pixels ; Step 5, Determination We can proceed to the sixth step of weighing the pros and cons.

[0052] Option 3 The first step is to obtain the baseline distance. ; The second step is to preset the pixel size. ; The third step is to preset the error rate according to the vision system requirements. Derive camera focal length constraints ; The fourth step is to select the appropriate lens based on the lens choice and image resolution estimation. ,but Pixels ; Step 5, Determination It needs to be redesigned.

[0053] Option 4 The first step is to obtain the baseline distance. ; The second step is to preset the pixel size. ; The third step is to preset the error rate according to the vision system requirements. Derive camera focal length constraints ; The fourth step is to select the appropriate lens based on the lens choice and image resolution estimation. ,but Pixels ; Step 5, Determination It needs to be redesigned.

[0054] After generating several mature solutions, proceed to step six.

[0055] Step 6: Balancing the design, Scheme 1 and Scheme 2 can meet the performance of the hardware platform. Scheme 2 uses an image sensor with smaller pixel size and lower cost, and a shorter lens focal length, which can obtain a larger field of view, making it the optimal solution.

[0056] In some embodiments, a computer device is provided, such as... Figure 2 As shown, it includes a memory 201, a processor 202, and a computer program stored in the memory 201 and executable on the processor 202. When the processor 202 executes the computer program, it implements the parameter acquisition method of the binocular vision early warning ranging system of any of the above embodiments.

[0057] Specifically, the computer device can be a computer terminal, a server, or a similar computing device.

[0058] In some embodiments, a computer-readable storage medium is provided, which stores a method for acquiring parameters of a binocular vision early warning ranging system as described in any of the above embodiments.

[0059] Specifically, computer-readable storage media, including both permanent and non-permanent, removable and non-removable media, can store information using any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer-readable storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable storage media does not include transient media, such as modulated data signals and carrier waves.

[0060] Based on the same inventive concept, this invention also provides a device for acquiring parameters of a binocular vision early warning ranging system, as described in the following embodiments. Since the principle of a device for acquiring parameters of a binocular vision early warning ranging system is similar to that of a method for acquiring parameters of a binocular vision early warning ranging system, the implementation of such a device can refer to the implementation of the method for acquiring and detecting parameters of a binocular vision early warning ranging system; repeated details will not be elaborated further. As used below, the terms "unit" or "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0061] A parameter acquisition device for a binocular vision early warning ranging system, the structural block diagram of which is shown below. Figure 3 As shown, it includes: The camera baseline acquisition module is used to select the camera baseline based on the size of the carrier platform, the reserved installation space limit, and the intended ranging distance; The camera image sensor pixel size acquisition module is used to select the camera image sensor pixel size based on the ranging distance, lighting conditions, and the platform's image computing and processing capabilities. The camera lens focal length constraint acquisition module is used to obtain the camera lens focal length constraint based on the aforementioned acquired camera baseline and camera image sensor pixel size. The image resolution constraint acquisition module is used to determine the image resolution constraint based on the focal length constraint, ranging distance, required field of view, and given field of view requirements. The verification module is used to verify the constraints of the camera baseline, camera image sensor pixel size, camera lens focal length and image resolution obtained above. If the design requirements are not met, the above steps are repeated for iteration until the design requirements of the binocular vision early warning ranging system are met. The comprehensive weighing module is used to comprehensively weigh all the parameter sets that meet the design requirements to obtain the optimal parameter set.

[0062] Obviously, those skilled in the art should understand that the modules or steps of the above-described embodiments of the present invention can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the embodiments of the present invention are not limited to any particular hardware and software combination.

[0063] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, various modifications and variations can be made to the embodiments of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for acquiring parameters of a binocular vision early warning ranging system, characterized in that, include: The camera baseline is selected based on the size of the transport platform, the limitations of the reserved installation space, and the intended ranging distance. The camera image sensor pixel size is selected based on the ranging distance, lighting conditions, and the platform's image processing capabilities. The camera lens focal length constraint is obtained based on the aforementioned camera baseline and camera image sensor pixel size; The image resolution constraint is determined based on the focal length constraint, ranging distance, required field of view, and given field of view requirements. The constraints of the camera baseline, camera image sensor pixel size, camera lens focal length, and image resolution obtained above are verified. If the design requirements are not met, the above steps are repeated for iteration until the design requirements of the binocular vision early warning ranging system are met. By comprehensively weighing all the parameter sets that meet the design requirements, the optimal parameter set is obtained.

2. The parameter acquisition method for the binocular vision early warning ranging system according to claim 1, characterized in that, The selection of camera baseline based on the size of the carrier platform, the reserved installation space limit, and the intended ranging distance includes: the camera baseline is less than 1 / 3 of the intended ranging distance.

3. The method for acquiring parameters of a binocular vision early warning ranging system according to claim 1, characterized in that, The constraint for obtaining the camera lens focal length based on the aforementioned camera baseline and camera image sensor pixel size includes: The camera lens focal length is constrained based on the camera baseline and the camera image sensor pixel size, combined with the ranging distance, parallax, and error rate indicators.

4. The method for acquiring parameters of a binocular vision early warning ranging system according to claim 3, characterized in that, The process of obtaining the constraint on the camera lens focal length based on the camera baseline and the camera image sensor pixel size, combined with the ranging distance, parallax, and error rate indicators, includes: The constraint on the camera lens focal length f is: Where D is the ranging distance, For parallax error, b is the pixel size of the image sensor, and b is the baseline distance of the stereo camera. Given the error rate.

5. The method for acquiring parameters of a binocular vision early warning ranging system according to claim 1, characterized in that, The process of determining image resolution constraints based on focal length constraints, ranging distance, required field of view, and given field of view requirements includes: The horizontal resolution M of the image is: The vertical resolution N of the image is: Where f is the focal length of the camera lens, For image sensor pixel size, For the horizontal field of view required by the mission, The horizontal field of view is the required parameter for the mission.

6. The method for acquiring parameters of a binocular vision early warning ranging system according to claim 5, characterized in that, f represents the minimum focal length that satisfies the constraints based on the camera lens focal length constraints and the actual specifications of the selected lens focal length.

7. The method for acquiring parameters of a binocular vision early warning ranging system according to claim 1, characterized in that, The process of comprehensively weighing all the parameter sets that meet the design requirements to obtain the optimal parameter set includes: Using a weighted scoring method, the score of the i-th qualified solution is: in, For weighting coefficients, , The score is based on the baseline distance; the smaller the required baseline distance, the higher the score. The score is based on pixel size; the smaller the pixel size, the higher the score. For focal length, the smaller the focal length, the higher the score. The score is for camera resolution; the higher the score, the better. The required parallax error is scored individually; the larger the score, the higher the score. The design error rate is scored individually; the smaller the score, the higher the score. The score is for the period cost item; the lower the score, the higher the score. Ultimately, the group with the highest score is the optimal parameter group.

8. A parameter acquisition device for a binocular vision early warning ranging system, characterized in that, include: The camera baseline acquisition module is used to select the camera baseline based on the size of the carrier platform, the reserved installation space limit, and the intended ranging distance; The camera image sensor pixel size acquisition module is used to select the camera image sensor pixel size based on the ranging distance, lighting conditions, and the platform's image computing and processing capabilities. The camera lens focal length constraint acquisition module is used to obtain the camera lens focal length constraint based on the aforementioned acquired camera baseline and camera image sensor pixel size. The image resolution constraint acquisition module is used to determine the image resolution constraint based on the focal length constraint, ranging distance, required field of view, and given field of view requirements. The verification module is used to verify the constraints of the camera baseline, camera image sensor pixel size, camera lens focal length and image resolution obtained above. If the design requirements are not met, the above steps are repeated for iteration until the design requirements of the binocular vision early warning ranging system are met. The comprehensive weighing module is used to comprehensively weigh all the parameter sets that meet the design requirements to obtain the optimal parameter set.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the parameter acquisition method for the binocular vision early warning ranging system as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores the method for acquiring parameters of a binocular vision early warning ranging system according to any one of claims 1 to 7.

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