Camera angle adjustment analysis method and device, equipment and storage medium

Abstract

A method, apparatus, device, and storage medium for camera angle adjustment and analysis are disclosed. The method includes: acquiring detection deviations of the camera at a preset position and at various installation angles for identifying and detecting various different targets; determining the comprehensive deviation of the camera at each installation angle based on the detection deviations of the camera detecting various different targets; and determining the installation angle corresponding to the minimum comprehensive deviation as the optimal installation angle based on the comprehensive deviations of the camera at various installation angles. Through this scheme, the detection results at each installation angle are comprehensively analyzed and verified across multiple scenarios. Then, these detection deviations are combined and analyzed to obtain the comprehensive deviation of the camera at that installation angle, achieving a more accurate verification result for that installation angle that conforms to real-world scenarios. Finally, the optimal installation angle is selected from multiple installation angles, enabling the camera to be more accurate in actual use.

Description

Technical Field

[0001] This application relates to the field of vehicle equipment technology, specifically to a camera angle adjustment and analysis method, device, equipment, and storage medium. Background Technology

[0002] With the development and popularization of intelligent driving assistance systems, intelligent driving assistance cameras have become mainstream. Whether it's a single-camera solution or a millimeter-wave radar + camera solution, they are all present. How to efficiently and quickly verify their current installation status has become a challenge for major OEMs. Camera verification solutions based on dark boxes have become the main verification method. By displaying the scene to be identified on the dark box's screen, the camera is controlled to detect and identify the scene from different positions. The detection and recognition performance of the camera in different positions is then analyzed to verify the camera's detection capabilities and ultimately find the appropriate installation angle.

[0003] However, the current analysis and verification process after capturing and displaying images using cameras is too simple. It often only analyzes the recognition and detection effect of a certain scene in different locations. In actual use, different targets need to be detected, and the recognition effect will also vary when the target is different. Therefore, the current verification process has limitations and needs to be further improved. Summary of the Invention

[0004] This application provides a camera angle adjustment and analysis method, apparatus, device, and storage medium, which can solve the technical problems existing in the above-mentioned related technologies.

[0005] In a first aspect, embodiments of this application provide a camera angle adjustment and analysis method, employing the following technical solution:

[0006] A camera angle adjustment and analysis method, the method comprising:

[0007] The detection deviation of the camera at a preset position and at various installation angles for identifying and detecting various different targets is obtained;

[0008] Based on the detection deviation of the camera at each installation angle when detecting multiple different targets, the overall deviation of the camera at that installation angle is determined.

[0009] Based on the comprehensive deviations of the camera at various installation angles, the installation angle corresponding to the smallest comprehensive deviation is determined as the optimal installation angle.

[0010] In conjunction with the first aspect, in one embodiment, the method of acquiring the detection deviation of the camera at a preset position and at multiple installation angles for identifying and detecting various different target objects includes the following steps:

[0011] The baseline deviation is obtained after the camera performs identification and detection on multiple different states of each different target object at each of the aforementioned installation angles at a preset position.

[0012] Based on the multiple said basic deviations, the detection deviation of the camera for each different target at each said installation angle is obtained.

[0013] In conjunction with the first aspect, in one implementation, obtaining the detection deviation of the camera for each different target at each of the multiple said basic deviations includes the following steps:

[0014] Based on the multiple longitudinal basic deviations obtained by the camera in identifying and detecting the target object in the longitudinal direction from the multiple basic deviations, the comprehensive longitudinal deviation of the camera for each target object at each installation angle is obtained;

[0015] Based on the multiple lateral basic deviations obtained by the camera in identifying and detecting the target object in the lateral direction from the multiple basic deviations, the comprehensive lateral deviation of the camera for each target object at each installation angle is obtained.

[0016] Based on the longitudinal and lateral integrated deviations, the detection deviation of the camera for each different target object at each of the installation angles is obtained.

[0017] In conjunction with the first aspect, in one implementation, the longitudinal baseline deviation is the variance of the error between the distance of the camera to the target object in different states at different distances in the longitudinal direction and the true distance value.

[0018] In conjunction with the first aspect, in one implementation, the target objects identified by the camera in the longitudinal direction include at least trucks, cars, two-wheeled vehicles, and pedestrians.

[0019] In conjunction with the first aspect, in one embodiment, the lateral base deviation is the variance of the error between the lane width of the straight lane identified by the camera in the lateral direction and the true value of the width, the variance of the error between the lane length of the straight lane identified by the camera and the true value of the length, and the variance of the error between the turning curvature of the curved lane identified by the camera and the true value of the curvature.

[0020] In conjunction with the first aspect, in one embodiment, the comprehensive deviation is obtained based on the comprehensive longitudinal deviation and the comprehensive lateral deviation.

[0021] The overall deviation is the sum of the product of the preset first weight and the overall longitudinal deviation, and the product of the preset second weight and the overall lateral deviation.

[0022] Secondly, embodiments of this application provide a camera angle adjustment and analysis device, which adopts the following technical solution:

[0023] A camera angle adjustment and analysis device, the camera angle adjustment and analysis device comprising:

[0024] The acquisition module is configured to acquire the detection deviation of the camera at a preset position and at multiple installation angles for recognizing and detecting various different targets.

[0025] The processing module determines the overall deviation of the camera at each installation angle by considering the detection deviation of the camera when detecting multiple different targets at each installation angle.

[0026] The analysis module is configured to determine the installation angle corresponding to the smallest comprehensive deviation as the optimal installation angle based on the comprehensive deviation of the camera at various installation angles.

[0027] Thirdly, embodiments of this application provide a camera angle adjustment and analysis device, which adopts the following technical solution:

[0028] A camera angle adjustment and analysis device includes a processor, a memory, and a camera angle adjustment and analysis program stored in the memory and executable by the processor. When the camera angle adjustment and analysis program is executed by the processor, it implements the steps of the camera angle adjustment and analysis method as described above.

[0029] Fourthly, embodiments of this application provide a storage medium, employing the following technical solution:

[0030] A storage medium storing a camera angle debugging and analysis program, wherein when the camera angle debugging and analysis program is executed by a processor, it implements the steps of the camera angle debugging and analysis method as described above.

[0031] The beneficial effects of the technical solutions provided in this application include:

[0032] By acquiring the detection deviations obtained after the camera captures different types of targets at various installation angles, a comprehensive analysis and verification of the detection results at each installation angle is performed across multiple scenarios. These detection deviations are then combined and analyzed to obtain the comprehensive deviation of the camera at that installation angle, thus achieving a more accurate verification result that conforms to real-world scenarios. Finally, the optimal installation angle is selected from multiple installation angles, enabling the camera to be more accurate in actual use. Attached Figure Description

[0033] Figure 1 This is a flowchart illustrating an embodiment of the camera angle adjustment and analysis method of this application;

[0034] Figure 2This is a functional module diagram of an embodiment of the camera angle adjustment and analysis device of this application;

[0035] Figure 3 This is a schematic diagram of the hardware structure of the camera angle adjustment and analysis device involved in the embodiments of this application. Detailed Implementation

[0036] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0037] With the development and popularization of intelligent driving assistance systems, intelligent driving assistance cameras have become mainstream. Whether it's a single-camera solution or a millimeter-wave radar + camera solution, they are all present. How to efficiently and quickly verify their current installation status has become a challenge for major OEMs. Camera verification solutions based on dark boxes have become the main verification method. By displaying the scene to be identified on the dark box's screen, the camera is controlled to detect and identify the scene from different positions. The detection and recognition performance of the camera in different positions is then analyzed to verify the camera's detection capabilities and ultimately find the appropriate installation angle.

[0038] However, the current analysis and verification process after capturing and displaying images using cameras is too simple. It often only analyzes the recognition and detection effect of a certain scene in different locations. In actual use, different targets need to be detected, and the recognition effect will also vary when the target is different. Therefore, the current verification process has limitations and needs to be further improved.

[0039] To address the aforementioned issues, this application provides a camera angle adjustment and analysis method, apparatus, device, and storage medium. The key point of the invention lies in acquiring the detection deviations obtained after the camera captures different types of target objects at various installation angles. This allows for comprehensive analysis and verification of the detection results at each installation angle across multiple scenarios. Furthermore, these detection deviations are combined and analyzed to obtain the comprehensive deviation of the camera at that installation angle. This results in a more accurate verification of the installation angle that aligns with real-world scenarios. Finally, the optimal installation angle is selected from multiple installation angles, enabling the camera to be more accurate in practical use.

[0040] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0041] In a first aspect, embodiments of this application provide a method for adjusting and analyzing camera angles.

[0042] In one embodiment, reference is made to Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the camera angle adjustment and analysis method of this application. Figure 1 As shown, the camera angle adjustment and analysis method includes:

[0043] S100: Obtain the detection deviation of the camera when it is installed at a preset position and at multiple angles to identify and detect various different targets;

[0044] S200. Based on the detection deviation of the camera at each installation angle when detecting multiple different targets, determine the comprehensive deviation of the camera at that installation angle.

[0045] S300. Based on the comprehensive deviations of the camera at various installation angles, determine the installation angle corresponding to the smallest comprehensive deviation as the optimal installation angle.

[0046] Specifically, the detection deviation obtained in step S100 is based on the camera dark box scenario. The camera dark box contains a display screen. The camera's preset position is aligned with the center point of the display screen in the y and z directions. The x-direction distance between the camera and the display screen ensures that the camera can completely capture the screen image. The specific calculation and positioning process of the preset position is not further limited in this application. After the camera is installed in the preset position, it will identify and detect the target object displayed on the screen at multiple installation angles to obtain information data about the target object. This data is then compared with the true value information set for the target object to obtain the detection deviation of the camera for identifying and detecting a target object at that installation angle. The installation angle includes the horizontal rotation angle of the camera in the horizontal direction and the vertical tilt angle in the vertical direction. Therefore, multiple installation angles are combinations of various horizontal rotation angles (a1, a2, a3, a4…) and various tilt angles (b1, b2, b3, b4…), such as (a1, b1), (a1, b2), (a1,…), (a2, b1), (a3, b1), (…, b1), etc. The targets to be photographed include, but are not limited to, trucks, cars, two-wheeled vehicles, pedestrians, straight lane lines, and curved lane lines. The relevant images are projected onto the display screen. The longitudinal and lateral recognition methods differ depending on the target. For example, for traffic participants such as trucks and cars in front of the camera, the distance to these targets needs to be determined, so longitudinal recognition is used. For targets on either side of vehicles, such as lane lines, lateral recognition is required to obtain information about the lane lines on both sides.

[0047] Finally, by acquiring the detection deviations obtained after the camera captures different types of targets at various installation angles, a comprehensive multi-scenario analysis and verification of the detection results at that installation angle is performed. These detection deviations are then combined and analyzed to obtain the comprehensive deviation of the camera at that installation angle, thus obtaining a more accurate verification result for that installation angle that conforms to the real-world scenario. Finally, the optimal installation angle is selected from multiple installation angles, enabling the camera to be more accurate in actual use.

[0048] Furthermore, in some embodiments, step S100, obtaining the detection deviation of the camera at a preset position and at multiple installation angles for identifying and detecting various different targets, includes the following steps:

[0049] S110. Obtain the basic deviation after the camera identifies and detects multiple different states of each different target object at each installation angle in a preset position;

[0050] Specifically, the different states of each target object refer to different states of the target object relative to the camera. For example, the distance between the target object and the camera may be different (e.g., the distance between the target object and the camera) or the shape of the target object may be adjusted (e.g., when a straight lane line is used as the target object, the width between the two lane lines changes; when a curved lane line is used as the target object, the curvature at the curve changes). When the longitudinal distance between the target object and the camera changes, it can be achieved by a camera position adjustment device installed in the dark box. When the shape of the target object itself is adjusted, it is specifically achieved by switching between different target object shapes on the display screen. The specific adjustment process will not be further described in this application.

[0051] This step requires the camera to identify and detect different states of each type of target object at each installation angle to obtain the basic deviation. For example, when the target object is a truck in front, the camera needs to detect and identify the truck at different distances at a certain installation angle to obtain multiple detection distances. Then, the basic deviation of the camera for the target object at that installation angle is obtained through multiple detection distances.

[0052] S120. Based on the multiple said basic deviations, obtain the detection deviation of the camera for each different target object at each said installation angle.

[0053] Specifically, after obtaining the basic deviations for each installation angle and each target object in step S110, the basic deviations of various targets at that installation angle can be combined and analyzed to obtain the detection deviation of the camera at that installation angle.

[0054] Furthermore, in some embodiments, step S120, obtaining the detection deviation of the camera for each different target object at each of the multiple said basic deviations, includes the following steps:

[0055] S121. Based on the multiple longitudinal basic deviations obtained by the camera in identifying and detecting the target object in the longitudinal direction from the multiple basic deviations, the comprehensive longitudinal deviation of the camera for each target object at each installation angle is obtained.

[0056] Specifically, in this embodiment, the longitudinal baseline deviation is the variance of the error between the distance detected by the camera to various targets in the longitudinal direction and the true distance value. For example, if the camera captures images of trucks at different positions from a certain installation angle, and then combines this with the true distance value to obtain the distance error for the trucks at different positions, and then calculates the variance of the distance error, we obtain the longitudinal baseline deviation for trucks as a type of target. In the specific calculation, each longitudinal composite deviation is multiplied by its corresponding calculation coefficient and then summed to obtain the longitudinal composite deviation. It is worth noting that the calculation coefficients corresponding to each longitudinal composite deviation satisfy the condition that the sum of them equals 1.

[0057] In this embodiment, the targets identified by the camera in the longitudinal direction include at least trucks, cars, two-wheeled vehicles, and pedestrians. Therefore, there is a longitudinal comprehensive bias corresponding to trucks, cars, two-wheeled vehicles, and pedestrians respectively.

[0058] S122. Based on the multiple lateral basic deviations obtained by the camera in identifying and detecting the target object in the lateral direction from the multiple basic deviations, the comprehensive lateral deviation of the camera for each target object at each installation angle is obtained.

[0059] Specifically, in this embodiment, the lateral foundation deviation is the variance of the error between the lane width of the straight lane identified by the camera and its true value, the variance of the error between the lane length of the straight lane identified by the camera and its true value, and the variance of the error between the turning curvature of the curved lane identified by the camera and its true value. Consistent with the method for calculating the longitudinal comprehensive deviation, the lateral comprehensive deviation is obtained by weighted summation of multiple lateral foundation deviations.

[0060] S123. Based on the longitudinal comprehensive deviation and the lateral comprehensive deviation, the detection deviation of the camera for each different target object at each of the installation angles is obtained.

[0061] Specifically, the comprehensive deviation is the sum of the product of the preset first weight and the comprehensive longitudinal deviation, and the product of the preset second weight and the comprehensive lateral deviation.

[0062] Secondly, embodiments of this application also provide a camera angle adjustment and analysis device.

[0063] In one embodiment, referring to FIG. n, FIG. n is a functional block diagram of an embodiment of the camera angle adjustment and analysis device of this application. As shown in FIG. n, the camera angle adjustment and analysis device includes:

[0064] The acquisition module is configured to acquire the detection deviation of the camera at a preset position and at multiple installation angles for recognizing and detecting various different targets.

[0065] The processing module determines the overall deviation of the camera at each installation angle by considering the detection deviation of the camera when detecting multiple different targets at each installation angle.

[0066] The analysis module is configured to determine the installation angle corresponding to the smallest comprehensive deviation as the optimal installation angle based on the comprehensive deviation of the camera at various installation angles.

[0067] The functions of each module in the camera angle adjustment and analysis device correspond to the steps in the camera angle adjustment and analysis method embodiment, and their functions and implementation processes will not be described in detail here.

[0068] Thirdly, embodiments of this application provide a camera angle adjustment and analysis device, which can be a personal computer (PC), laptop computer, server, or other device with data processing capabilities.

[0069] Reference Figure 3 , Figure 3 This is a schematic diagram of the hardware structure of the camera angle adjustment and analysis device involved in the embodiments of this application. In the embodiments of this application, the camera angle adjustment and analysis device may include a processor, a memory, a communication interface, and a communication bus.

[0070] The communication bus can be of any type and is used to interconnect the processor, memory, and communication interface.

[0071] The communication interface includes input / output (I / O) interfaces, physical interfaces, and logical interfaces used for interconnecting internal components of the camera angle debugging and analysis device, as well as interfaces used for interconnecting the camera angle debugging and analysis device with other devices (such as other computing devices or user equipment). Physical interfaces can be Ethernet interfaces, fiber optic interfaces, ATM interfaces, etc.; user equipment can be displays, keyboards, etc.

[0072] Memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0073] The processor can be a general-purpose processor, which can call the camera angle debugging and analysis program stored in the memory and execute the camera angle debugging and analysis method provided in the embodiments of this application. For example, the general-purpose processor can be a central processing unit (CPU). The method executed when the camera angle debugging and analysis program is called can be referred to in various embodiments of the camera angle debugging and analysis method of this application, and will not be repeated here.

[0074] Those skilled in the art will understand that Figure 3 The hardware structure shown does not constitute a limitation of this application and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0075] Fourthly, embodiments of this application also provide a storage medium.

[0076] The storage medium of this application stores a camera angle debugging and analysis program, wherein when the camera angle debugging and analysis program is executed by the processor, it implements the steps of the camera angle debugging and analysis method described above.

[0077] The method implemented when the camera angle debugging and analysis program is executed can be referred to in various embodiments of the camera angle debugging and analysis method of this application, and will not be repeated here.

[0078] Fifthly, a camera angle adjustment and analysis system is also provided, which mainly consists of a camera mounting platform, a horizontal slide rail, a vertical slide rail mechanism, a camera pitch angle adjustment motor, a horizontal angle adjustment motor, a display screen, a fan, a host computer, host computer scene software, and host computer automatic debugging software.

[0079] Camera mounting platform: used for installing and securing cameras;

[0080] Horizontal slider: Enables the camera to move back and forth in the X direction, adjusting the distance between the camera and the display screen;

[0081] Vertical sliding rail: Enables the camera to move up and down in the Z direction, adjusting the height relationship between the camera and the display screen;

[0082] Camera pitch angle adjustment motor: Enables the camera to rotate along the Y direction, adjusting the camera's pitch angle relative to the display screen to ensure target distance recognition and lane detection;

[0083] Horizontal angle adjustment motor: Enables the camera to rotate along the Z direction, adjusts the torsion angle of the camera relative to the display screen, and ensures the detection of lane lines and targets in different lanes;

[0084] Display screen: Used for displaying test scenarios of intelligent driving cameras. The cameras can accurately capture scene data and output perception results.

[0085] Control module: Completes the adjustment and control of the X, Y, Z movement and Y, Z rotation of the platform camera.

[0086] Acquisition module: Completes real-time acquisition of CAN signals output by the camera, which are used for data analysis by the host computer software.

[0087] Fan: Used to cool the environment of the camera during testing, serving as ventilation and cooling in the darkroom environment;

[0088] Host computer: Used for bench control and process debugging, and synchronously collects data during the bench debugging process;

[0089] Host computer scenario software: Constructs functional scenarios for debugging and testing, such as roads, lane lines, vehicles, etc.

[0090] The host computer automatic debugging software automatically generates the debugging position of the camera, controls the control frame to be in the corresponding position, calculates the measurement results of key parameters at different positions, performs automatic analysis of the results, and generates the optimal debugging position.

[0091] When using the above system to collect relevant detection deviations, the following steps are included:

[0092] F1: Calculate the camera's mounting position based on the display screen size (L1×H) to ensure the camera captures the entire screen image. The calculation process for the camera's mounting distance from the screen (i.e., its mounting position in the X direction) is as follows:

[0093] The camera's mounting position in the Y and Z directions should be aligned with the center of the screen, i.e., X. c =L,Y c =Y 屏 Z c =Z 屏 .

[0094] F2: Input the calculation results from step 1 into the position parameters in the control software of the host computer, and adjust the camera to the corresponding position;

[0095] F3: The host computer's automatic debugging software analyzes the camera installation position and outputs the analysis results to the control software, which then adjusts the angle information of each camera.

[0096] Step 4: After receiving the camera's installation and debugging location, the control software adjusts to the corresponding position according to the target location. The debugging scene is projected onto the darkroom display screen through the scene software. The camera's recognition results for different target types at different distances are collected, and the left and right recognition distances, longitudinal distances, and curvature alarms for lane lines are collected in straight and curved road environments. The debugging and data collection are performed through the following process.

[0097] Step 5: Analyze the target distance information and lane information output by the camera under different rotation angles (αn, βn) using the aforementioned camera angle adjustment analysis to obtain the optimal adjustment angle position, which is the final installation angle selected for testing.

[0098] It should be noted that the sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0099] The terms "comprising" and "having," and any variations thereof, in the specification, claims, and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus. The terms "first," "second," and "third," etc., are used to distinguish different objects, etc., and do not indicate a sequence, nor do they limit "first," "second," and "third" to different types.

[0100] In the description of the embodiments of this application, terms such as "exemplary," "for example," or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "exemplary," "for example," or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary," "for example," or "for instance" is intended to present the relevant concepts in a concrete manner.

[0101] In the description of the embodiments of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of this application, "multiple" means two or more.

[0102] In some processes described in the embodiments of this application, multiple operations or steps are included in a specific order. However, it should be understood that these operations or steps may not be executed in the order they appear in the embodiments of this application, or they may be executed in parallel. The sequence number of the operation is only used to distinguish different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed sequentially or in parallel, and these operations or steps may be combined.

[0103] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device to execute the methods described in the various embodiments of this application.

[0104] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A method for adjusting and analyzing camera angles, characterized in that, The method includes: The detection deviation of a camera at a preset position and various installation angles for identifying and detecting different targets is obtained. The obtained detection deviation is based on a camera dark box scenario, in which a display screen is installed. The preset position of the camera is aligned with the center point of the display screen in the y and z directions, and the x-direction distance between the camera and the display screen ensures that the camera can completely capture the screen image. After the camera is installed at the preset position, it will identify and detect the target image presented on the display screen at multiple installation angles to obtain information data about the target. This data is then compared with the true value information set for the target to obtain the detection deviation of the camera for identifying and detecting a target at that installation angle. Based on the detection deviation of the camera at each installation angle when detecting multiple different targets, the overall deviation of the camera at that installation angle is determined. Based on the comprehensive deviations of the camera at various installation angles, the installation angle corresponding to the smallest comprehensive deviation is determined as the optimal installation angle.

2. The camera angle adjustment and analysis method as described in claim 1, characterized in that, The acquisition of detection deviations when the camera is installed at a preset position and at various angles to identify and detect various different targets includes the following steps: The baseline deviation is obtained after the camera performs identification and detection of multiple different states of each different target object at each of the aforementioned installation angles at a preset position. Based on the multiple said basic deviations, the detection deviation of the camera for each different target at each said installation angle is obtained.

3. The camera angle adjustment and analysis method as described in claim 2, characterized in that, The step of obtaining the detection deviation of the camera for each different target at each installation angle based on the multiple said basic deviations includes the following steps: Based on the multiple longitudinal basic deviations obtained by the camera in identifying and detecting the target object in the longitudinal direction, each longitudinal basic deviation is multiplied by its corresponding calculation coefficient and then summed to obtain the comprehensive longitudinal deviation of the camera for each target object at each installation angle. Based on the multiple lateral basic deviations obtained by the camera in identifying and detecting the target object in the lateral direction, each lateral basic deviation is multiplied by its corresponding calculation coefficient and then summed to obtain the comprehensive lateral deviation of the camera for each target object at each installation angle. Based on the longitudinal and lateral integrated deviations, the detection deviation of the camera for each different target object at each of the installation angles is obtained.

4. The camera angle adjustment and analysis method as described in claim 3, characterized in that, The longitudinal baseline deviation is the variance of the error between the distance of the camera to the target object under different distance states in the longitudinal direction and the true distance value.

5. The camera angle adjustment and analysis method as described in claim 4, characterized in that, The targets identified by the camera in the vertical direction include at least trucks, cars, two-wheeled vehicles, and pedestrians.

6. The camera angle adjustment and analysis method as described in claim 3, characterized in that, The lateral base deviation is the variance of the error between the lane width of the straight lane identified by the camera in the lateral direction and the true value of the width, the variance of the error between the lane length of the straight lane identified by the camera and the true value of the length, and the variance of the error between the turning curvature of the curved lane identified by the camera and the true value of the curvature.

7. The camera angle adjustment and analysis method as described in claim 3, characterized in that, The overall deviation is obtained based on the longitudinal overall deviation and the lateral overall deviation. The overall deviation is the sum of the product of the preset first weight and the longitudinal overall deviation, and the product of the preset second weight and the lateral overall deviation.

8. A camera angle adjustment and analysis device, characterized in that, The camera angle adjustment and analysis device includes: The acquisition module is configured to acquire the detection deviation of the camera at a preset position and at multiple installation angles for identifying and detecting various different targets. The acquired detection deviation is based on a camera dark box scenario, in which a display screen is installed. The preset position of the camera is aligned with the center point of the display screen in the y and z directions, and the x-direction distance between the camera and the display screen ensures that the camera can completely capture the screen image. After the camera is installed at the preset position, it will identify and detect the target image presented on the display screen at multiple installation angles to obtain information data about the target. This data is then compared with the true value information set for the target to obtain the detection deviation of the camera for identifying and detecting a target at that installation angle. The processing module determines the overall deviation of the camera at each installation angle by considering the detection deviation of the camera when detecting multiple different targets at each installation angle. The analysis module is configured to determine the installation angle corresponding to the smallest comprehensive deviation as the optimal installation angle based on the comprehensive deviation of the camera at various installation angles.

9. A camera angle adjustment and analysis device, characterized in that, The camera angle debugging and analysis device includes a processor, a memory, and a camera angle debugging and analysis program stored in the memory and executable by the processor, wherein when the camera angle debugging and analysis program is executed by the processor, it implements the steps of the camera angle debugging and analysis method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium stores a camera angle debugging and analysis program, wherein when the camera angle debugging and analysis program is executed by the processor, it implements the steps of the camera angle debugging and analysis method as described in any one of claims 1 to 7.

Images