Simulated cockpit display method and system according to human viewpoint position

Abstract

The invention relates to the technical field of simulation display, in particular to a simulation cockpit display method and system according to a human viewpoint position. According to the method, a camera or a sensor is used for capturing the viewpoint position of a driver in real time, and the eye position of the driver is determined through a face recognition algorithm; determining the sight direction of the driver based on the viewpoint position of the driver; dynamically adjusting the display content according to the viewpoint position and the sight direction to ensure that the picture is consistent with the actual driving scene; and rendering the adjusted display content in real time by using a graphics processor. According to the simulated cockpit display method based on real-time viewpoint capture and GPU rendering, the immersion degree, comfort and interactive experience of simulated driving can be remarkably improved. The system combines the advantages of high-precision monitoring, quick response, immersive display and efficient rendering, and is an important development direction of a cockpit simulation technology in the future.

Description

Technical Field

[0001] The present invention relates to the technical field of analog display, and particularly to an analog cockpit display method and system based on the position of a person's viewing point. Background Art

[0002] Vehicle simulation driving, also known as vehicle driving simulation, is to construct an artificial environment by means of high-tech means such as three-dimensional image instant generation technology, vehicle dynamics simulation physical system, large field of view display technology (such as multi-channel stereoscopic projection system), six-degree-of-freedom motion platform (or three-degree-of-freedom motion platform), user input hardware system, stereophonic sound, central control system, etc. Virtual driving enables the experiencer to experience a vehicle driving experience with visual, auditory and somatic sensations close to the real effect in a virtual driving environment. It has the advantages of realistic driving simulation effect, energy saving, safety, economy, being unrestricted by time, climate and site, high driving training efficiency, short training cycle, etc.

[0003] The existing traditional analog cockpit display method mainly displays from a fixed perspective and does not have a display adjustment technology, and the display content cannot respond to the driver's line-of-sight changes in real time. To solve this technical problem, an analog cockpit display method and system based on the position of a person's viewing point are proposed. Summary of the Invention

[0004] To solve the technical problems existing in the above-mentioned prior art, the present invention provides an analog cockpit display method and system based on the position of a person's viewing point.

[0005] To achieve the above object, the embodiments of the present invention provide the following technical solutions:

[0006] In a first aspect, in an embodiment provided by the present invention, an analog cockpit display method based on the position of a person's viewing point is provided, and the method includes the following steps:

[0007] Use a camera or sensor to capture the driver's viewing point position in real time, and determine the driver's eye position through a face recognition algorithm;

[0008] Dynamically adjust the display content according to the viewing point position and line-of-sight direction to ensure that the picture is consistent with the actual driving scene;

[0009] Use a graphics processor to render the adjusted display content in real time.

[0010] As a further solution of the present invention, it is characterized in that the determining the driver's eye position through the face recognition algorithm includes:

[0011] Use the Adaboost algorithm to locate the face area from the image;

[0012] After detecting a human face, determine the initial eye position data according to the geometric structure of the human face;

[0013] Based on the initial eye position data, use the open-source Mediapipe framework to extract facial feature points through a neural network and determine the driver's eye position.

[0014] As a further solution of the present invention, it is characterized in that the use of the Adaboost algorithm to locate the face region in the image includes:

[0015] Prepare face images and non-face images as training data;

[0016] Calculate all possible Haar features using the training data and use the integral image to accelerate the calculation;

[0017] Select the most effective Haar features through the Adaboost algorithm and construct a classifier;

[0018] Use the pre-trained classifier to detect the face region.

[0019] As a further solution of the present invention, dynamically adjust the display content according to the viewpoint position and the line of sight direction to ensure that the screen is consistent with the actual driving scene; it also includes: determining the driver's line of sight direction based on the driver's viewpoint position.

[0020] As a further solution of the present invention, the determining the driver's line of sight direction based on the driver's viewpoint position includes:

[0021] Use the correspondence between facial key points and the standard 3D face model to calculate the head pose vector;

[0022] Use the pre-trained pupil detection model to detect the two-dimensional coordinates of the pupil; in the open-eye state, combine the grayscale image or depth image of the eye region to extract the center position of the pupil;

[0023] Based on the three-dimensional face model and the pre-acquired eye anatomical structure, calculate the three-dimensional center coordinates of the eyeball; combine the two-dimensional coordinates of the pupil and the three-dimensional coordinates of the eyeball center, and calculate the three-dimensional vector of the pupil center relative to the eyeball center through geometric methods to determine the driver's line of sight direction.

[0024] As a further solution of the present invention, the head pose vector includes pitch angle, yaw angle and roll angle.

[0025] As a further solution of the present invention, using the correspondence between facial key points and the standard 3D face model to calculate the head pose vector includes:

[0026] Calculate the head pose vector through the Perspective-n-Point algorithm.

[0027] As a further solution of the present invention, the two-dimensional coordinates of the pupil are detected by using a pre-trained pupil detection model; in the open-eye state, the central position of the pupil is extracted by combining the grayscale image or depth image of the eye region, including:

[0028] Collect a number of eye images under different lighting conditions and different perspectives as the training data set of the pupil detection model, and pre-train the pupil detection model by using the pre-processed image pre-processing;

[0029] Perform image pre-processing on the image to be detected;

[0030] Load the pupil detection model, input the pre-processed image into the pupil detection model, and detect the two-dimensional coordinates of the pupil.

[0031] Use the ellipse fitting method to extract the pupil contour, and calculate the center of the ellipse as the central position of the pupil.

[0032] As a further solution of the present invention, the pupil detection model can be a YOLOv5 model or a YOLOv8 model.

[0033] As a further solution of the present invention, the adjusted display content is rendered in real time by using a graphics processor, including: adopting a dynamic computing power allocation algorithm, and adjusting the GPU resource allocation in real time according to the scene complexity and data stream priority; during the rendering process, semi-precision floating-point operations are used for non-critical areas to reduce the calculation latency.

[0034] In a second aspect, in another embodiment provided by the present invention, a simulated cockpit display system according to the driver's viewpoint position is provided. The system includes: a viewpoint position acquisition module, a line-of-sight direction determination module, a content determination module, and a display content rendering module.

[0035] The viewpoint position acquisition module is used to use a camera or a sensor to capture the driver's viewpoint position in real time, and determine the driver's eye position through a face recognition algorithm.

[0036] The line-of-sight direction determination module is used to determine the driver's line-of-sight direction based on the driver's viewpoint position.

[0037] The content determination module is used to dynamically adjust the display content according to the viewpoint position and the line-of-sight direction to ensure that the picture is consistent with the actual driving scene.

[0038] The display content rendering module is used to use a graphics processor to render the adjusted display content in real time.

[0039] The technical solution provided by the present invention has the following beneficial effects:

[0040] The real-time capture technology of the present invention can quickly respond to the changes in the driver's line of sight, ensure the dynamic adjustment of the cockpit display content to be synchronized with the driver's line of sight, enhance driving safety and comfort. The face recognition algorithm can accurately locate the position of the driver's eyes, provide a reliable basis for subsequent calculation of the line of sight direction, and dynamically adjust the display content according to the viewpoint position and line of sight direction, which can provide the driver with an immersive cockpit interaction experience and reduce visual fatigue. The powerful parallel computing ability of the GPU can quickly process complex graphics tasks, significantly improve the rendering speed, and ensure the real-time update of the display content.

[0041] These aspects or other aspects of the present invention will be more clearly understood in the following description of the embodiments. It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other embodiments can be obtained based on these drawings.

[0043] Figure 1 It is a flowchart of a simulated cockpit display method according to the human viewpoint position in an embodiment of the present invention.

[0044] Figure 2 It is a specific flowchart of step S10 in the simulated cockpit display method according to the human viewpoint position in an embodiment of the present invention.

[0045] Figure 3 It is a specific flowchart of step S101 in the simulated cockpit display method according to the human viewpoint position in an embodiment of the present invention.

[0046] Figure 4 It is a specific flowchart of step S20 in the simulated cockpit display method according to the human viewpoint position in an embodiment of the present invention.

[0047] Figure 5 It is a specific flowchart of step S202 in the simulated cockpit display method according to the human viewpoint position in an embodiment of the present invention.

[0048] Figure 6 It is a structural framework diagram of a simulated cockpit display system according to the human viewpoint position in an embodiment of the present invention.

[0049] In the figure: viewpoint position acquisition module - 100, line of sight direction determination module - 200, content determination module - 300, display content rendering module - 400. Detailed implementation manners

[0050] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0051] The flowcharts shown in the accompanying drawings are only illustrative examples, and do not necessarily include all contents and operations / steps, nor do they necessarily need to be executed in the described order. For example, some operations / steps can be decomposed, combined, or partially merged, so the actual execution order may change according to the actual situation.

[0052] It should be understood that the terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an", and "the" are intended to include the plural forms.

[0053] Specifically, the embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0054] Please refer to Figure 1 , Figure 1 which is a flowchart of a simulated cockpit display method according to the human viewpoint position provided by an embodiment of the present invention. As Figure 1 shown, the simulated cockpit display method according to the human viewpoint position includes steps S10 to step S40.

[0055] S10. Use a camera or a sensor to capture the driver's viewpoint position in real time, and determine the driver's eye position through a face recognition algorithm.

[0056] In the embodiment of the present invention, the camera can be an infrared camera or a depth camera to improve the capture accuracy.

[0057] Please refer to Figure 2 , in the embodiment of the present invention, the determining the driver's eye position through the face recognition algorithm includes:

[0058] S101. Use the Adaboost algorithm to locate the face area in the image; the Adaboost method based on the integral image can quickly detect faces and is suitable for real-time systems;

[0059] Please refer to Figure 3 , step S101, using the Adaboost algorithm to locate the face region from the image, includes:

[0060] S1011. Prepare face images and non-face images as training data;

[0061] S1012. Calculate all possible Haar features using the training data, and use the integral image to accelerate the calculation;

[0062] Haar features are simple and effective image features used to describe edges, lines, and textures in images. Common Haar features include: edge features, line features, central symmetric features, and diagonal features.

[0063] S1013. Select the most effective Haar features through the Adaboost algorithm and construct a classifier;

[0064] S1014. Detect the face region using the pre-trained classifier.

[0065] The advantages of the Adaboost algorithm in face detection are mainly reflected in aspects such as efficient feature selection, fast detection ability, high detection rate and low false alarm rate, flexibility and adaptability, real-time performance and robustness. These characteristics make Adaboost a very effective algorithm in the field of face detection.

[0066] S102. After detecting the face, determine the initial position data of the eyes according to the geometric structure of the face;

[0067] S103. Based on the initial position data of the eyes, use the Mediapipe open-source framework to extract face feature points through a neural network and determine the driver's eye position.

[0068] S20. Dynamically adjust the display content according to the viewpoint position and the line of sight direction to ensure that the screen is consistent with the actual driving scenario.

[0069] The step S20, dynamically adjusting the display content according to the viewpoint position and the line of sight direction to ensure that the screen is consistent with the actual driving scenario, further includes:

[0070] Based on the driver's viewpoint position, determine the driver's line of sight direction.

[0071] Please refer to Figure 4 , in the embodiment of the present invention, based on the driver's viewpoint position, determining the driver's line of sight direction includes:

[0072] S01. Use the correspondence between face key points and the standard 3D face model to calculate the head pose vector; where the head pose vector includes pitch angle, yaw angle, and roll angle.

[0073] Specifically, the head pose vector can be calculated by the Perspective-n-Point (PnP) algorithm.

[0074] The calculation by the Perspective-n-Point (PnP) algorithm can calculate the head pose vector through the solvePnP or solvePnPRansac function.

[0075] Through the solvePnP or solvePnPRansac function of OpenCV, the head pose vector can be calculated efficiently. Selecting appropriate PnP algorithms and methods for handling outliers can significantly improve the accuracy and robustness of pose estimation.

[0076] Specifically, the goal of the solvePnP function is to minimize the reprojection error, that is:

[0077]

[0078] where n is the number of corresponding points, is the actual projection point in the image, is the estimated point calculated through the projection model.

[0079] Projection model:

[0080] 3D point P w is transformed to the camera coordinate system through the rotation matrix R and the translation vector t:

[0081] P c = RP w + t

[0082] Then, it is projected onto the image plane through the camera intrinsic matrix K:

[0083] p = KP c

[0084] Finally, the optimization goal is to minimize the reprojection error.

[0085] S02. Detect the two-dimensional coordinates of the pupil using a pre-trained pupil detection model; in the open-eye state, combine the grayscale image or depth image of the eye region to extract the center position of the pupil.

[0086] Please refer to Figure 5 For S202, which detects the two-dimensional coordinates of the pupil using a pre-trained pupil detection model; in the open-eye state, combines the grayscale image or depth image of the eye region to extract the center position of the pupil, it includes:

[0087] S021. Collect several eye images under different lighting conditions and different perspectives as the training dataset for the pupil detection model, and use the preprocessed images to pre-train the pupil detection model; the pupil detection model can be a YOLOv5 model or a YOLOv8 model.

[0088] S022. Perform image preprocessing on the image to be detected.

[0089] S023. Load the pupil detection model, input the preprocessed image into the pupil detection model, and detect the two-dimensional coordinates of the pupil.

[0090] S024. Use the ellipse fitting method to extract the pupil contour and calculate the center of the ellipse as the center position of the pupil.

[0091] Through the above method, high-precision pupil detection can be achieved, and the center position of the pupil can be extracted by combining the grayscale or depth image of the eye region, providing support for subsequent line-of-sight direction estimation.

[0092] S03. Based on the three-dimensional face model and the pre-acquired eye anatomical structure, calculate the three-dimensional center coordinates of the eyeball; combine the two-dimensional coordinates of the pupil and the three-dimensional coordinates of the eyeball center, and calculate the three-dimensional vector of the pupil center relative to the eyeball center through geometric methods to determine the driver's line-of-sight direction.

[0093] S30. Use the graphics processing unit (GPU) to render the adjusted display content in real time.

[0094] S40. Using the graphics processing unit (GPU) to render the adjusted display content in real time includes: adopting a dynamic computing power allocation algorithm to adjust the GPU resource allocation in real time according to the scene complexity and data stream priority; during the rendering process, use half-precision floating-point operations for non-critical areas to reduce the calculation latency.

[0095] Determine the fixation point area according to the line-of-sight direction, and use high-resolution rendering in this area, while using low-resolution rendering for the visual field edge, which can significantly reduce the GPU load while maintaining the high quality of the visual focus area.

[0096] The real-time capture technology of the present invention can quickly respond to the changes in the driver's line of sight, ensure the dynamic adjustment of the cockpit display content to be synchronized with the driver's line of sight, enhance driving safety and comfort. The face recognition algorithm can accurately locate the driver's eye position, providing a reliable basis for subsequent calculation of the line of sight direction. Dynamically adjusting the display content according to the viewpoint position and line of sight direction can provide the driver with an immersive cockpit interaction experience and reduce visual fatigue. The powerful parallel computing ability of the GPU can quickly process complex graphics tasks, significantly improve the rendering speed, and ensure the real-time update of the display content. The simulated cockpit display method based on real-time viewpoint capture and GPU rendering of the present invention can significantly improve the immersion, comfort and interaction experience of simulated driving. It combines the advantages of high-precision monitoring, fast response, immersive display and efficient rendering, and is an important development direction of future intelligent cockpit technology.

[0097] It should be understood that although the above is described in a certain order, these steps are not necessarily executed in the above order successively. Unless there is a clear indication in this article, there is no strict order limit for the execution of these steps, and these steps can be executed in other orders. Moreover, a part of the steps of this embodiment may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same moment, but can be executed at different moments. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or steps or stages in other steps.

[0098] In one embodiment, as shown in Figure 6 In the embodiment of the present invention, a simulated cockpit display system according to the human viewpoint position is further provided. The system includes a viewpoint position acquisition module 100, a content determination module 200, and a display content rendering module 300.

[0099] The viewpoint position acquisition module 100 is used to use a camera or a sensor to capture the driver's viewpoint position in real time, and determine the driver's eye position through a face recognition algorithm.

[0100] The content determination module 200 is used to dynamically adjust the display content according to the viewpoint position and the line of sight direction to ensure that the picture is consistent with the actual driving scene.

[0101] The display content rendering module 300 is used to use a graphics processing unit (GPU) to render the adjusted display content in real time.

[0102] In one embodiment, in the embodiment of the present invention, a computer device is further provided, including a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete mutual communication through the communication bus.

[0103] A memory for storing a computer program;

[0104] A processor, when executing the computer program stored in the memory, executes the above-described simulated cockpit display method based on the human viewpoint position. When the processor executes instructions, it implements the steps in the above method embodiments:

[0105] S10. Use a camera or sensor to capture the driver's viewpoint position in real time, and determine the driver's eye position through a face recognition algorithm;

[0106] S20. Dynamically adjust the display content according to the viewpoint position and the line-of-sight direction to ensure that the picture is consistent with the actual driving scene;

[0107] S30. Use a graphics processor to render the adjusted display content in real time.

[0108] The communication bus mentioned in the above terminal may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of simplicity, only a thick line is shown in the figure, but it does not mean that there is only one bus or one type of bus.

[0109] The communication interface is used for communication between the above terminal and other devices.

[0110] The memory may include a Random Access Memory (RAM), and may also include a non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located far from the aforementioned processor.

[0111] The above-mentioned processor may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0112] The computer device includes a user device and a network device. Among them, the user device includes, but is not limited to, a computer, a smart phone, a PDA, etc.; the network device includes, but is not limited to, a single network server, a server group composed of multiple network servers, or a cloud composed of a large number of computers or network servers based on cloud computing (Cloud Computing). Among them, cloud computing is a type of distributed computing and is a super virtual computer composed of a group of loosely coupled computer sets. Among them, the computer device can operate independently to implement the present invention, or can be connected to a network and implement the present invention through interaction with other computer devices in the network. Among them, the network where the computer device is located includes, but is not limited to, the Internet, a wide area network, a metropolitan area network, a local area network, a VPN network, etc.

[0113] It should also be understood that the term "and / or" used in the specification and appended claims of the present invention refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0114] In an embodiment of the present invention, a storage medium is further provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above method embodiment are implemented:

[0115] S10. Use a camera or a sensor to capture the viewpoint position of the driver in real time, and determine the eye position of the driver through a face recognition algorithm;

[0116] S20. Dynamically adjust the display content according to the viewpoint position and the line of sight direction to ensure that the picture is consistent with the actual driving scene;

[0117] S30. Use a graphics processor to render the adjusted display content in real time.

[0118] Those of ordinary skill in the art can understand that all or part of the processes in the above method embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above method embodiments. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided by the present invention can include at least one of non-volatile and volatile memories.

[0119] It should be understood that, as used herein, unless the context clearly supports the exception, the singular form "a" is intended to also include the plural form. It should also be understood that "and / or" as used herein refers to any and all possible combinations of one or more of the associated listed items. The serial numbers of the disclosed embodiments of the present invention above are only for description and do not represent the advantages or disadvantages of the embodiments.

[0120] Those of ordinary skill in the art should understand that the discussion of any of the above embodiments is only exemplary and is not intended to imply that the scope of the disclosure of the embodiments of the present invention (including the claims) is limited to these examples; under the concept of the embodiments of the present invention, the technical features in the above embodiments or different embodiments can also be combined, and there are many other variations in different aspects of the embodiments of the present invention as described above, which are not provided in detail for the sake of brevity. Therefore, any omission, modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present invention shall be included within the protection scope of the embodiments of the present invention.

Claims

1. A simulation cockpit display method based on the human viewing point position, characterized in that, The method includes: Using a camera or sensor to capture the driver's viewpoint position in real time, and determining the driver's eye position through a face recognition algorithm; Dynamically adjusting the display content according to the viewpoint position and line of sight direction to ensure that the picture is consistent with the actual driving scene; Using a graphics processor to render the adjusted display content in real time.

2. The method for simulating cockpit display according to the human viewpoint position as described in claim 1, characterized in that, The determining of the driver's eye position through the face recognition algorithm includes: Using the Adaboost algorithm to locate the face region in the image; After detecting the face, determining the initial eye position data according to the geometric structure of the face; Based on the initial eye position data, using the Mediapipe open-source framework to extract facial feature points through a neural network to determine the driver's eye position.

3. The simulated cockpit display method according to the human viewpoint position as described in claim 2, wherein, The using of the Adaboost algorithm to locate the face region in the image includes: Preparing face images and non-face images as training data; Calculating all possible Haar features using the training data and accelerating the calculation using an integral image; Selecting the most effective Haar features through the Adaboost algorithm and constructing a classifier; Using the pre-trained classifier to detect the face region.

4. The simulated cockpit display method according to the human viewpoint position as described in claim 1, characterized in that, Dynamically adjusting the display content according to the viewpoint position and line of sight direction to ensure that the picture is consistent with the actual driving scene further includes: determining the driver's line of sight direction based on the driver's viewpoint position.

5. The simulated cockpit display method according to the human viewpoint position as described in claim 1, wherein The determining of the driver's line of sight direction based on the driver's viewpoint position includes: Using the correspondence between facial key points and a standard 3D face model to calculate the head pose vector; Using a pre-trained pupil detection model to detect the two-dimensional coordinates of the pupil; in the open-eye state, combining the grayscale image or depth image of the eye region to extract the center position of the pupil; Based on the 3D face model and the pre-acquired eye anatomical structure, calculating the three-dimensional center coordinates of the eyeball; combining the two-dimensional coordinates of the pupil and the three-dimensional coordinates of the eyeball center, and calculating the three-dimensional vector of the pupil center relative to the eyeball center through a geometric method to determine the driver's line of sight direction.

6. The method for simulating cockpit display according to the position of the human viewing point as claimed in claim 5, wherein, Using the correspondence between facial key points and a standard 3D face model to calculate the head pose vector includes: Calculating the head pose vector through the Perspective-n-Point algorithm.

7. The simulated cockpit display method according to the human viewpoint position as claimed in claim 5, characterized in that The using of a pre-trained pupil detection model to detect the two-dimensional coordinates of the pupil; In the open-eye state, combining the grayscale image or depth image of the eye region to extract the center position of the pupil includes: Collecting several eye images under different lighting conditions and different viewpoints as the training data set of the pupil detection model, and pre-training the pupil detection model using the pre-processed images; Performing image pre-processing on the image to be detected; Loading the pupil detection model, inputting the pre-processed image into the pupil detection model to detect the two-dimensional coordinates of the pupil; Using the ellipse fitting method to extract the pupil contour and calculating the center of the ellipse as the center position of the pupil.

8. The method for simulating cockpit display according to the human viewpoint position as claimed in claim 1, wherein, The pupil detection model can be a YOLOv5 model or a YOLOv8 model.

9. The method for simulating cockpit display according to the human viewpoint position as described in claim 1, wherein, The real-time rendering of the adjusted display content using a graphics processing unit includes: adopting a dynamic computing power allocation algorithm to adjust the GPU resource allocation in real time according to the scene complexity and data stream priority; during the rendering process, using half-precision floating-point operations for non-critical areas to reduce the calculation latency.

10. A simulated cockpit display system according to the position of a person's viewing point, characterized in that, The system includes: a viewpoint position acquisition module, a line-of-sight direction determination module, a content determination module, and a display content rendering module; the viewpoint position acquisition module is used to capture the driver's viewpoint position in real time using a camera or sensor, and determine the driver's eye position through a face recognition algorithm; The line-of-sight direction determination module is used to determine the driver's line-of-sight direction based on the driver's viewpoint position; The content determination module is used to dynamically adjust the display content according to the viewpoint position and line-of-sight direction to ensure that the screen is consistent with the actual driving scene; The display content rendering module is used to render the adjusted display content in real time using a graphics processing unit.

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