An AVM algorithm architecture and vehicle panoramic surround view method based on openGL

Abstract

The present invention discloses an AVM algorithm architecture based on openGL and a vehicle panoramic surround view method, which relates to the field of vehicle panoramic surround view technology, including: an input capture module, a format conversion module, a projection transformation module, a color balancing module, a splicing module, a single view module and a trajectory module; the input capture module is used to collect vehicle data; the format conversion module is used to convert camera image data; the projection transformation module converts the converted camera image data into a bird's-eye view; the color balancing module is used to adjust the color of the bird's-eye view; the splicing module converts the bird's-eye view into a panoramic view; the single view module complements the single view perspective with the bird's-eye view; the trajectory module is used to display the estimated moving trajectory of the vehicle in the panoramic view. The AVM algorithm architecture based on openGL provided by the present invention is based on OpenGL high-precision pixel processing, optimizes the driver's visual experience, improves the real-time processing speed, and improves the collaboration efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle panoramic surround view, and in particular to an AVM algorithm architecture based on OpenGL and a vehicle panoramic surround view method. Background Art

[0002] The vehicle panoramic view method is an advanced driver assistance system for automobiles. It captures images around the vehicle through multiple cameras and synthesizes them into a 360-degree panoramic image in real time. It faces many challenges in image stitching, system complexity and real-time rendering. There are problems such as poor image stitching effect, slow image processing rate and high algorithm complexity. Summary of the invention

[0003] In view of the above-mentioned problems, the present invention is proposed.

[0004] Therefore, the technical problems solved by the present invention are: first, in the image stitching process of the existing vehicle panoramic view method, the seams between images are often improperly handled, resulting in visual incoherence, which seriously affects the user experience.

[0005] Secondly, due to insufficient image processing and rendering performance, the system is unable to meet real-time requirements, resulting in image delays or freezes.

[0006] Finally, the system architecture is complex, the dependencies between modules are strong, and development and maintenance are difficult, which affects the scalability of the system and the efficiency of multi-developer collaboration.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions: an AVM algorithm architecture based on OpenGL, comprising:

[0008] Input capture module, format conversion module, projection transformation module, color balancing module, stitching module, single view module and trajectory module;

[0009] The input capture module is used to collect vehicle data;

[0010] The format conversion module is used to convert camera image data;

[0011] The projection transformation module converts the converted camera image data into a bird's-eye view;

[0012] The color balancing module is used to adjust the color of the bird's-eye view;

[0013] The stitching module converts the bird's-eye view into a panoramic view;

[0014] The single view module complements the single view perspective with the bird's eye view;

[0015] The trajectory module is used to display the estimated moving trajectory of the vehicle in the panoramic view.

[0016] As a preferred solution of the vehicle panoramic view method of the present invention, wherein: the vehicle data includes camera images, vehicle CAN signals and driver click events;

[0017] The number of the cameras is four;

[0018] The converting camera image data comprises collecting image data in YUV format through four cameras;

[0019] Upload four YUV images to the graphics processing unit GPU respectively, create a texture object for each image, and bind it to four independent texture units;

[0020] In the fragment shader of the GPU, the bound YUV texture is sampled, and the color conversion formula is applied to map the data in the YUV color space to the RGBA color space to generate an RGBA image;

[0021] Render the converted RGBA image to the first framebuffer object;

[0022] The frame buffer object acts as a rendering target and stores the converted RGBA image data through different color attachments.

[0023] As a preferred solution of the vehicle panoramic surround view method of the present invention, wherein: the conversion into a bird's-eye view includes taking the first frame buffer object as input and binding its four image textures to the fragment shader of the projection transformation module;

[0024] In the fragment shader, sample the bound texture and use the mapping relationship between the spherical coordinate system and the plane coordinate system to convert the image into a bird's-eye view.

[0025] Render the four converted bird's-eye view images to the second frame buffer object, storing the bird's-eye view image data through different color attachments.

[0026] As a preferred solution of the vehicle panoramic view method of the present invention, the adjusting of the color of the bird's-eye view includes inputting: taking the second frame buffer object as input, binding four textures to the fragment shader of the color balancing module;

[0027] The fragment shader samples the texture and adjusts the colors of the four bird's-eye-view images through an algorithm;

[0028] Render the four color-balanced bird's-eye views to the third framebuffer object.

[0029] As a preferred solution of the vehicle panoramic surround view method of the present invention, wherein: the converting of the bird's-eye view into the panoramic view comprises binding four textures of the third frame buffer object to the fragment shader of the splicing module;

[0030] The fragment shader samples the texture and uses an algorithm to crop and stitch the four color-balanced bird's-eye views into a panoramic view image.

[0031] Renders the panorama view image directly to the screen.

[0032] As a preferred solution of the vehicle panoramic surround view method of the present invention, wherein: the complementing of the single view perspective with the bird's eye view includes inputting a first frame buffer object, using a vehicle signal and a driver click event as inputs of a view determination module, determining the view that should be currently displayed, and binding a texture corresponding to the view in the first frame buffer object to a fragment shader of the single view module;

[0033] The fragment shader samples the texture and performs dedistortion.

[0034] Renders a single view image directly to the screen.

[0035] As a preferred solution of the vehicle panoramic view method of the present invention, wherein: the display of the estimated moving trajectory of the vehicle in the panoramic view includes taking the vehicle signal and the driver's click event as input;

[0036] Calculate the specific coordinate points based on the input;

[0037] Render the trajectory line to the screen. Before submitting the rendering command, please wait for both the stitching module and the single view module to complete the command submission, so as to attach the trajectory line to the stitching and single view images.

[0038] Another object of the present invention is to provide a vehicle panoramic view method based on the AVM algorithm architecture of OpenGL, which can solve the visual incoherence problem and insufficient real-time rendering performance problem caused by image splicing seams in the existing vehicle panoramic view method through image processing and real-time rendering technology based on OpenGL.

[0039] To solve the above technical problems, the present invention provides the following technical solutions: a vehicle panoramic view method based on the AVM algorithm architecture of openGL, comprising: collecting YUV format image data from four cameras of the vehicle through an input capture module, obtaining the vehicle's CAN signal and the driver's click event signal; uploading the collected four YUV format images to the GPU through a format conversion module, creating a texture object, and binding it to an independent texture unit; in the fragment shader of the GPU, sampling the bound YUV texture, applying a color conversion formula, converting the YUV format image into an RGBA format image; rendering the converted RGBA image into a first frame buffer object; passing the image texture in the first frame buffer object output by the format conversion module as input to a projection transformation module; the fragment shader converts the four images into a bird's-eye view perspective through a mapping relationship between a spherical coordinate system and a plane coordinate system; rendering the generated bird's-eye view to a second frame buffer object; As input, it is passed to the color balancing module; the image is sampled through the fragment shader, and the color of the bird's-eye view is adjusted through the color balancing algorithm to ensure the color uniformity of the image; the equalized image is rendered to the third frame buffer object; through the stitching module, the four image textures in the third frame buffer object output by the color balancing module are used as input; the fragment shader crops and stitches the textures to combine the four bird's-eye views into a panoramic view; the generated panoramic view is directly rendered to the screen; through the single view module, the image of the first frame buffer object of the format conversion module is input, and the current viewing angle required to be displayed is determined in combination with the vehicle signal and the driver's click event; the fragment shader dedistorts the texture of the selected viewing angle; a single view is directly rendered to the screen; through the trajectory module, the vehicle signal and the driver's click event are input to calculate the expected movement trajectory of the vehicle; after the stitching module and the single view module are rendered, the trajectory is rendered to the panoramic view or the single view; the trajectory is displayed on the screen and the rendering is completed by attaching it to the corresponding image.

[0040] A computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned vehicle panoramic view method when executing the computer program.

[0041] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the vehicle panoramic view method as described above.

[0042] Beneficial effects of the present invention: The vehicle panoramic view method provided by the present invention is based on OpenGL high-precision pixel processing, which ensures pixel continuity and optimizes the driver's visual experience.

[0043] OpenGL can utilize the parallel processing capabilities of the GPU to accelerate graphics rendering and calculation, improve real-time processing speed, and meet real-time requirements in terms of performance.

[0044] By modularizing the algorithm, the code is easier to read and understand. Multiple developers can work on different modules at the same time, which improves collaboration efficiency and reduces the difficulty of system development and maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0046] Figure 1 An overall structural diagram of an AVM algorithm architecture based on OpenGL provided for one embodiment of the present invention. DETAILED DESCRIPTION

[0047] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0048] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0049] Example 1, reference Figure 1 , as an embodiment of the present invention, provides an AVM algorithm architecture based on OpenGL, including:

[0050] An input capture module 100 , a format conversion module 200 , a projection transformation module 300 , a color balancing module 400 , a stitching module 500 , a single view module 600 and a trajectory module 700 .

[0051] The input capture module 100, as the overall input module of the AVM algorithm architecture, needs to collect images from the four cameras at the front, back, left and right, the vehicle CAN signal (including gear position, steering wheel angle) and the driver's click events in advance, which are divided into four events: click on the front view / click on the right view / click on the left view / click on the rear view, and pass the signals to each module.

[0052] Format conversion module 200, the data collected by the camera is usually in YUV format, and most displays and screens use RGBA color model to display images. In order to correctly display images on these devices, the YUV format needs to be converted to RGBA format, the steps are as follows:

[0053] 1) Image input and texture upload: Four YUV images are uploaded to the GPU as texture objects. Each texture is bound to four different texture units for shader access.

[0054] 2) Shader processing: In the shader stage of the GPU, these YUV textures are sampled using fragment shaders and YUV to RGBA conversion is performed. The fragment shader maps the data in the YUV color space to the RGBA color space by implementing the corresponding color conversion formula to generate the final RGBA image;

[0055] 3) FBO rendering output: Render the converted RGBA image to the frame buffer object FBO1. These FBO1s are used as rendering targets to store the converted RGBA image data through different color attachments. Four converted RGBA image data are stored in FBO1. And this FBO1 is the output of this module for use by subsequent modules.

[0056] The projection transformation module 300 is mainly used to transform the panoramic image captured by the fisheye lens into a bird's-eye view through the mapping relationship between the spherical coordinate system and the plane coordinate system. The steps are as follows:

[0057] 1) Input: Use FBO1 as the input of this module and bind the four image textures of FBO1 to the fragment shader of the projection module;

[0058] 2) Shader processing: The fragment shader samples these textures and converts the image into a bird's-eye view through mapping relationships;

[0059] 3) FBO rendering output: Render the four converted bird's-eye view images into the frame buffer object FBO2. These FBO2s are used as rendering targets to store the bird's-eye view image data through different color attachments. The four converted bird's-eye view images are stored in FBO2, and the FBO2 is used as the output of this module for use by subsequent modules.

[0060] The color balancing module 400 adjusts the colors of the four images through an algorithm to achieve a uniform color without obvious color difference. The steps are as follows:

[0061] 1) Input: Use FBO2 as the input of this module and bind the four textures of FBO2 to the fragment shader of the color balance module;

[0062] 2) Shader processing: The fragment shader samples these textures and calculates adjustment coefficients for the three RGB channels of the image, and adjusts the colors of the four bird's-eye views according to the calculated coefficients;

[0063] 3) FBO rendering output: Render the four color-balanced bird's-eye view images into the frame buffer object FBO3. These FBO3s are used as rendering targets, and the color-balanced bird's-eye view image data is stored through different color attachments. The four color-balanced bird's-eye view image outputs are stored in FBO3. And the FBO3 is the output of this module for use by subsequent modules.

[0064] The stitching module 500 combines the four bird's-eye views into a panoramic view through image cropping and stitching algorithms, and the steps are as follows:

[0065] 1) Input: Use FBO3 as the input of this module and bind the four textures of FBO3 to the fragment shader of the splicing and fusion module;

[0066] 2) Shader processing: The fragment shader samples these textures and uses an algorithm to crop and stitch the four color-balanced bird's-eye views into a panoramic view image;

[0067] 2) Shader processing: The fragment shader samples these textures and stitches the four color-balanced bird's-eye views into a panoramic view image through algorithms such as image cropping, transparency channel adjustment, and image fusion;

[0068] 3) Screen rendering output: Render the panoramic view image directly to the screen and bind FBOBuffer to 0.

[0069] In the single view module 600, in the panoramic surround view system, the perspective of a single view provides more specific details and local information. These perspectives can complement the bird's eye view to provide the driver with comprehensive and accurate environmental information. The steps of the single view module are as follows:

[0070] 1) Input: FBO1 is used as the image input of this module, and the vehicle signal and the driver's click event are used as the input of the view angle judgment module. In the view angle judgment module, it is calculated that the current view angle to be displayed is one of the front, back, left, and right, and the texture corresponding to a certain view angle in FBO1 is bound to the fragment shader of the single view module;

[0071] 2) Shader processing: The fragment shader samples these textures and performs dedistortion processing;

[0072] 3) Screen rendering output: Render the single view image directly to the screen and bind FBOBuffer to 0. This means binding the current frame buffer object to the default value 0.

[0073] The track line module 700 displays the estimated moving track of the vehicle in the panoramic view, and renders multiple coordinate points through OpenGL to form track line lines.

[0074] 1) Input: vehicle signals and driver click events are used as input;

[0075] 2) Shader processing: calculate the specific coordinate points based on the input;

[0076] 3) Screen rendering output: Render the trajectory line to the screen. Before submitting the rendering command, please wait for both the stitching module and the single view module to complete the command submission, so as to attach the trajectory line to the stitching and single view images.

[0077] Embodiment 2 is an embodiment of the present invention, which provides an AVM algorithm architecture based on OpenGL, including:

[0078] Through the input capture module, the YUV format image data from the four cameras of the vehicle are collected to obtain the vehicle's CAN signal and the driver's click event signal;

[0079] Through the format conversion module, the four acquired YUV format images are uploaded to the GPU, texture objects are created, and bound to independent texture units;

[0080] In the fragment shader of the GPU, sample the bound YUV texture and apply the color conversion formula to convert the YUV format image into an RGBA format image;

[0081] Render the converted RGBA image into the first framebuffer object;

[0082] The image texture in the first frame buffer object output by the format conversion module is passed as input to the projection transformation module;

[0083] The fragment shader converts the four images into a bird's-eye view through the mapping relationship between the spherical coordinate system and the plane coordinate system;

[0084] Render the generated bird's-eye view to the second frame buffer object;

[0085] The image of the second frame buffer object output by the projection transformation module is passed as input to the color balancing module;

[0086] The image is sampled through the fragment shader, and the color of the bird's-eye view is adjusted through the color balancing algorithm to ensure the color uniformity of the image;

[0087] Render the equalized image to the third frame buffer object;

[0088] The four image textures in the third frame buffer object output by the color balancing module are used as input through the stitching module;

[0089] The fragment shader performs cropping and stitching operations on the textures to combine the four bird's-eye views into a panoramic view;

[0090] Render the generated panoramic view directly to the screen;

[0091] The image of the first frame buffer object of the input format conversion module is input through the single view module, and the vehicle signal and the driver's click event are combined to determine the current viewing angle required for display;

[0092] The fragment shader dedistorts the texture at the selected view angle;

[0093] Render a single view directly to the screen;

[0094] Through the trajectory module, vehicle signals and driver click events are input to calculate the vehicle's expected movement trajectory;

[0095] After the stitching module and the single view module are rendered, the trajectory line is rendered on the panoramic view or the single view;

[0096] The trajectory lines are displayed on the screen and rendered in a manner that they are attached to the corresponding images.

[0097] Embodiment 3, an embodiment of the present invention, is different from the first two embodiments in that:

[0098] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0099] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0100] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0101] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0102] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An AVM algorithm architecture based on openGL, characterized in that: include: An input capture module (100), a format conversion module (200), a projection transformation module (300), a color balancing module (400), a splicing module (500), a single view module (600), and a trajectory module (700); The input capture module (100) is used to collect vehicle data; The format conversion module (200) is used to convert camera image data; The projection transformation module (300) transforms the transformed camera image data into a bird's-eye view; The color balancing module (400) is used to adjust the color of the bird's-eye view; The splicing module (500) converts the bird's-eye view into a panoramic view; The single view module (600) complements the single view perspective with the bird's eye view; The trajectory module (700) is used to display the estimated moving trajectory of the vehicle in the panoramic view.

2. The AVM algorithm architecture based on OpenGL as claimed in claim 1, characterized in that: The vehicle data includes camera images, vehicle CAN signals, and driver click events; The number of the cameras is four; The converting camera image data comprises collecting image data in YUV format through four cameras; Upload four YUV images to the graphics processing unit GPU respectively, create a texture object for each image, and bind it to four independent texture units; In the fragment shader of the GPU, the bound YUV texture is sampled, and the color conversion formula is applied to map the data in the YUV color space to the RGBA color space to generate an RGBA image; Render the converted RGBA image to the first framebuffer object; The frame buffer object acts as a rendering target and stores the converted RGBA image data through different color attachments.

3. The AVM algorithm architecture based on openGL as claimed in claim 2, characterized in that: The conversion to the bird's eye view includes taking the first frame buffer object as input and binding its four image textures to the fragment shader of the projection transformation module (300); In the fragment shader, sample the bound texture and use the mapping relationship between the spherical coordinate system and the plane coordinate system to convert the image into a bird's-eye view. Render the four converted bird's-eye view images to the second frame buffer object, storing the bird's-eye view image data through different color attachments.

4. The AVM algorithm architecture based on OpenGL as claimed in claim 3, characterized in that: The adjusting of the color of the bird's eye view includes inputting: taking the second frame buffer object as input, binding four textures to the fragment shader of the color equalization module (400); The fragment shader samples the texture and adjusts the colors of the four bird's-eye-view images through an algorithm; Render the four color-balanced bird's-eye views to the third framebuffer object.

5. The AVM algorithm architecture based on OpenGL as claimed in claim 4, characterized in that: Converting the bird's-eye view to the panoramic view includes binding four textures of the third frame buffer object to the fragment shader of the stitching module (500); The fragment shader samples the texture and uses an algorithm to crop and stitch the four color-balanced bird's-eye views into a panoramic view image. Renders the panorama view image directly to the screen.

6. The AVM algorithm architecture based on OpenGL as claimed in claim 5, characterized in that: The method of complementing the single view perspective with the bird's eye view includes inputting a first frame buffer object, using a vehicle signal and a driver click event as inputs to a view determination module, determining a view that should be currently displayed, and binding a texture corresponding to the view in the first frame buffer object to a fragment shader of the single view module (600); The fragment shader samples the texture and performs dedistortion. Renders a single view image directly to the screen.

7. The AVM algorithm architecture based on OpenGL as claimed in claim 6, characterized in that: The displaying of the estimated moving trajectory of the vehicle in the panoramic view includes taking a vehicle signal and a driver click event as input; Calculate the specific coordinate points based on the input; Render the trajectory line on the screen. Before submitting the rendering command, please wait for the stitching module (500) and the single view module (600) to complete the command submission, so as to attach the trajectory line to the stitching and single view images.

8. A vehicle panoramic view method using the AVM algorithm architecture based on OpenGL as claimed in any one of claims 1 to 7, characterized in that: include: Through the input capture module, the YUV format image data from the four cameras of the vehicle are collected to obtain the vehicle's CAN signal and the driver's click event signal; Through the format conversion module, the four acquired YUV format images are uploaded to the GPU, texture objects are created, and bound to independent texture units; In the fragment shader of the GPU, sample the bound YUV texture and apply the color conversion formula to convert the YUV format image into an RGBA format image; Render the converted RGBA image into the first framebuffer object; The image texture in the first frame buffer object output by the format conversion module is passed as input to the projection transformation module; The fragment shader converts the four images into a bird's-eye view through the mapping relationship between the spherical coordinate system and the plane coordinate system; Render the generated bird's-eye view to the second frame buffer object; The image of the second frame buffer object output by the projection transformation module is passed as input to the color balancing module; The image is sampled through the fragment shader, and the color of the bird's-eye view is adjusted through the color balancing algorithm to ensure the color uniformity of the image; Render the equalized image to the third frame buffer object; The four image textures in the third frame buffer object output by the color balancing module are used as input through the stitching module; The fragment shader performs cropping and stitching operations on the textures to combine the four bird's-eye views into a panoramic view; Render the generated panoramic view directly to the screen; The image of the first frame buffer object of the input format conversion module is input through the single view module, and the vehicle signal and the driver's click event are combined to determine the current viewing angle required for display; The fragment shader dedistorts the texture at the selected view angle; Render a single view directly to the screen; Through the trajectory module, vehicle signals and driver click events are input to calculate the vehicle's expected movement trajectory; After the stitching module and the single view module are rendered, the trajectory line is rendered onto the panoramic view or the single view; the trajectory line is displayed on the screen and the rendering is completed in a manner of being attached to the corresponding image.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the vehicle panoramic view method according to claim 1 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the vehicle panoramic view method according to claim 1 are implemented.

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