Image data transmission method and device

Abstract

The invention discloses an image data transmission method and device, and relates to the technical field of Internet of Vehicles, and the method comprises the steps: monitoring the actual bandwidth of a communication link between a vehicle terminal and a glasses terminal; identifying an image content type of the to-be-transmitted image data, and determining a bandwidth condition required for transmitting the to-be-transmitted image according to the image content type; and under the condition that the actual bandwidth does not meet the bandwidth condition, reducing the data quality of the to-be-transmitted image data, and transmitting the to-be-transmitted image data of which the data quality is reduced to the glasses end. According to the method, the bandwidth requirement is dynamically matched according to the image content type, and the data quality is preferentially reduced instead of interrupting transmission when the bandwidth is insufficient, so that the problem of image transmission jitter caused by severe fluctuation of the bandwidth is effectively avoided, the phenomena of blockage, smear and delay of an AR picture are remarkably reduced, the continuity and the real-time performance of a visual effect are guaranteed, and the user experience is improved. And finally, the information acquisition effect of the user in the vehicle-mounted AR application scene is improved.

Description

Technical Field

[0001] This application relates to the field of vehicle networking technology, and in particular to an image data transmission method and device. Background Technology

[0002] When existing in-vehicle AR (Augmented Reality) systems are running, they typically rely on vehicle-to-everything (V2X) technology implemented through the vehicle's infotainment system to establish a wireless data connection with display devices such as AR glasses worn by the user, in order to achieve real-time transmission of image data.

[0003] However, the communication environment of vehicle-to-everything (V2X) is highly dynamic and unstable. Its network bandwidth is easily affected by various factors such as vehicle speed, surrounding environment, signal obstruction, and network congestion, resulting in drastic fluctuations. These bandwidth fluctuations directly lead to a decrease in the transmission quality of AR image data streams, causing significant image transmission jitter. Specifically, the AR image frame rate can drop sharply from a smooth 60fps (frames per second) or even higher to below 30fps. This significant reduction in frame rate directly causes stuttering, ghosting, and latency in AR visuals, severely disrupting the continuity and real-time performance of the visual effects and greatly reducing the effectiveness of information acquisition for users in in-vehicle AR application scenarios such as navigation, safety warnings, and information prompts. Summary of the Invention

[0004] The main purpose of this application is to provide an image data transmission method and device, which aims to solve the technical problem of screen stuttering that easily occurs during the use of current in-vehicle AR glasses.

[0005] To achieve the above objectives, this application proposes an image data transmission method, which includes: Monitor the actual bandwidth of the communication link between the vehicle-mounted device and the glasses-mounted device; Identify the image content type of the image data to be transmitted, and determine the bandwidth requirements for transmitting the image based on the image content type; If the actual bandwidth does not meet the bandwidth conditions, the data quality of the image data to be transmitted is reduced, and the image data to be transmitted with reduced data quality is transmitted to the glasses.

[0006] In one embodiment, the step of determining the bandwidth requirements for transmitting the image to be transmitted based on the image content type includes: If the image content type includes an image content type, query the reference bandwidth condition associated with the image content type, and use the reference bandwidth condition as the bandwidth condition required to transmit the image to be transmitted; When the image content type includes multiple image content types, the reference bandwidth conditions associated with each image content type are queried, and the reference bandwidth condition with the highest corresponding bandwidth threshold among the reference bandwidth conditions is taken as the bandwidth condition required to transmit the image to be transmitted.

[0007] In one embodiment, the bandwidth conditions include multiple bandwidth conditions corresponding to different bandwidth thresholds, and the step of reducing the data quality of the image data to be transmitted and transmitting the image data to the glasses with reduced data quality includes: Among the bandwidth conditions, at least one target bandwidth condition that the actual bandwidth does not meet is determined, and a data transmission optimization strategy corresponding to the target bandwidth condition is obtained, wherein one target bandwidth condition corresponds to one data transmission optimization strategy; The data transmission optimization strategy is executed to reduce the data quality of the image data to be transmitted, and the image data to be transmitted with reduced data quality is transmitted to the glasses.

[0008] In one embodiment, the data transmission optimization strategy includes a first optimization strategy, a second optimization strategy, and a third optimization strategy. The step of executing the data transmission optimization strategy to reduce the data quality of the image data to be transmitted and transmitting the image data to be transmitted with reduced data quality to the glasses includes: The first optimization strategy is executed to reduce the resolution of the image data to be transmitted, and the reduced-resolution image data is transmitted to the glasses; and / or The second optimization strategy is executed to perform inter-frame coding on the video stream constructed from the image data to be transmitted, and the inter-frame coded video stream is transmitted to the glasses; and / or The third optimization strategy is executed to reduce the frame rate of the video stream constructed from the image data to be transmitted, and the video stream with reduced frame rate is transmitted to the glasses.

[0009] In one embodiment, before the step of implementing the data transmission optimization strategy to reduce the data quality of the image data to be transmitted, the method further includes: Region identification is performed on the image data to be transmitted to determine key and non-key regions in the image data to be transmitted, so as to implement the data transmission optimization strategy to reduce the data quality of the key regions and the non-key regions respectively; The degree of data quality degradation in the critical areas is less than that in the non-critical areas.

[0010] In one embodiment, the data transmission optimization strategy further includes a fourth optimization strategy and a fifth optimization strategy. The step of executing the data transmission optimization strategy to reduce the data quality of the image data to be transmitted and transmitting the image data to be transmitted with reduced data quality to the glasses includes: The fourth optimization strategy is executed to reduce the resolution of image data in the critical area to a first resolution, reduce the resolution of image data in the non-critical area to a second resolution, and transmit the reduced-resolution image data to the glasses, wherein the first resolution is greater than the second resolution; and / or The fifth optimization strategy is executed to perform intra-frame encoding on key regions in the video stream constructed from the image data to be transmitted, and inter-frame encoding on non-key regions in the video stream. The encoded video stream is then transmitted to the glasses. The key regions in the video stream correspond to the key regions in the image data to be transmitted, and the non-key regions in the video stream correspond to the non-key regions in the image data to be transmitted.

[0011] In one embodiment, after the step of transmitting the image data to be transmitted with reduced data quality to the glasses, the method further includes: Monitor the smoothness index and feedback data of the video stream constructed from the image data to be transmitted received by the glasses; The bandwidth conditions and the corresponding data transmission optimization parameters are adjusted based on the smoothness index and the feedback data, wherein the data transmission optimization parameters are used to control the degree to which the data quality is reduced.

[0012] In one embodiment, the vehicle-mounted device and the glasses-mounted device are also connected to the cloud for communication. Before the step of identifying the image content type of the image data to be transmitted, the method further includes: Identify the task type of each image computing task, and determine the low computing power requirement computing task and the high computing power requirement computing task in each image computing task according to the task type, wherein the low computing power requirement computing task is used to calculate the image data to be transmitted. The high-computing-power-requirement computing task is migrated to the cloud, so that after the cloud executes the high-computing-power-requirement computing task, the obtained supplementary image data is transmitted to the glasses.

[0013] Furthermore, to achieve the above objectives, this application also proposes an image data transmission method applied to an eyeglasses device, wherein the eyeglasses device is communicatively connected to an in-vehicle infotainment system. The image data transmission method includes: The system receives image data to be transmitted after its data quality has been reduced from the data transmitted by the vehicle-mounted terminal. The image data to be transmitted after its data quality has been reduced is obtained when the vehicle-mounted terminal detects that the actual bandwidth of the communication link between the vehicle-mounted terminal and the glasses terminal does not meet the bandwidth conditions required for transmitting the image data to be transmitted. The bandwidth conditions are determined by the vehicle-mounted terminal by identifying the image content type of the image data to be transmitted and based on the image content type. If the image data to be transmitted after the data quality reduction is a video stream with a reduced frame rate, the video stream is frame-interpolated, and the interpolated video stream is output.

[0014] In one embodiment, the vehicle-mounted terminal and the glasses terminal are also respectively connected to the cloud for communication, and the image data transmission method further includes: Receive supplementary image data transmitted from the cloud; The image data to be transmitted after the data quality has been reduced is combined with the supplementary image data to obtain complete image information, and the complete image information is then output.

[0015] In addition, to achieve the above objectives, this application also proposes an electronic device, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the image data transmission method as described above.

[0016] One or more technical solutions proposed in this application have at least the following technical effects: This application monitors the actual bandwidth of the communication link between the vehicle-mounted device and the glasses, and identifies the image content type of the image data to be transmitted to determine the bandwidth requirements for transmission. When the actual bandwidth does not meet these requirements, the data quality of the image data to be transmitted is proactively reduced before being transmitted to the glasses. This achieves adaptive adjustment to dynamic bandwidth fluctuations. Specifically, by dynamically matching bandwidth requirements according to the image content type and prioritizing data quality reduction rather than interruption when bandwidth is insufficient, it effectively avoids image transmission jitter caused by drastic bandwidth fluctuations. This significantly reduces AR screen stuttering, ghosting, and latency, ensuring the continuity and real-time nature of the visual effects, ultimately improving the information acquisition effect for users in in-vehicle AR application scenarios. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating an embodiment of the image data transmission method of this application. Figure 2 This is a flowchart illustrating Embodiment 2 of the image data transmission method of this application; Figure 3 This is a flowchart illustrating Embodiment 3 of the image data transmission method of this application; Figure 4 This is a flowchart illustrating Embodiment 4 of the image data transmission method of this application; Figure 5 This is a flowchart illustrating Embodiment 5 of the image data transmission method of this application; Figure 6 A simplified flowchart illustrating the image data transmission method provided in Embodiment 5 of this application; Figure 7 This is a schematic diagram of the device structure of the hardware operating environment involved in the image data transmission method in the embodiments of this application.

[0020] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0021] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0022] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0023] The main solution of this application embodiment is: monitoring the actual bandwidth of the communication link between the vehicle terminal and the glasses terminal; identifying the image content type of the image data to be transmitted, and determining the bandwidth conditions required to transmit the image data to be transmitted based on the image content type; if the actual bandwidth does not meet the bandwidth conditions, reducing the data quality of the image data to be transmitted, and transmitting the image data to be transmitted with reduced data quality to the glasses terminal.

[0024] Due to the highly dynamic and unstable communication environment of vehicle-to-everything (V2X) networks, network bandwidth is susceptible to drastic fluctuations caused by factors such as vehicle speed, surrounding environment, signal obstruction, and network congestion. These bandwidth fluctuations directly degrade the transmission quality of AR image data streams, leading to significant image transmission jitter. Specifically, the AR image frame rate can drop sharply from a smooth 60fps (frames per second) or even higher to below 30fps. This significant reduction in frame rate directly causes stuttering, ghosting, and latency in AR visuals, severely disrupting the continuity and real-time performance of the visual effects and greatly reducing the effectiveness of information acquisition for users in in-vehicle AR applications such as navigation, safety warnings, and information prompts.

[0025] This application provides a solution that monitors the actual bandwidth of the communication link between the vehicle-mounted device and the glasses, and identifies the image content type of the image data to be transmitted to determine the bandwidth requirements for transmission. When the actual bandwidth does not meet the specified bandwidth requirements, the solution proactively reduces the data quality of the image data to be transmitted and transmits it to the glasses. This achieves adaptive adjustment to dynamic bandwidth fluctuations. Specifically, by dynamically matching bandwidth requirements according to the image content type and prioritizing data quality reduction rather than interrupting transmission when bandwidth is insufficient, it effectively avoids image transmission jitter caused by drastic bandwidth fluctuations. This significantly reduces AR screen stuttering, ghosting, and latency, ensuring the continuity and real-time nature of the visual effects, ultimately improving the information acquisition effect for users in in-vehicle AR application scenarios.

[0026] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device, vehicle system, or glasses system capable of performing the above functions. The following description uses a vehicle system and a glasses system as examples to illustrate this embodiment and the subsequent embodiments.

[0027] Based on this, embodiments of this application provide an image data transmission method, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the image data transmission method of this application.

[0028] In this embodiment, the image data transmission method includes steps S10 to S30: Step S10: Monitor the actual bandwidth of the communication link between the vehicle-mounted terminal and the glasses terminal; It should be noted that the actual bandwidth is a comprehensive indicator reflecting the network transmission capacity at the current moment, obtained by real-time monitoring of the communication link between the vehicle-mounted system and the glasses. This parameter can be not only the theoretical maximum data transmission rate, but also the real-time downlink bandwidth that can be used to effectively transmit the image data to be transmitted in a dynamic and unstable vehicle-to-everything (V2X) environment. This parameter is the direct basis for the system to determine whether the current network resources are sufficient to support high-quality image transmission, and its fluctuations are the direct cause of image transmission jitter and frame rate drops.

[0029] The device form of the glasses may include, but is not limited to, glasses such as Mixed Reality (MR) glasses, Augmented Reality (AR) glasses, Virtual Reality (VR) glasses, Extended Reality (XR) glasses, or some combination thereof.

[0030] Step S20: Identify the image content type of the image data to be transmitted, and determine the bandwidth requirements for transmitting the image data to be transmitted based on the image content type; It should be noted that image content type is classified based on the functional importance or visual criticality of the information carried by the image data to be transmitted. For example, in in-vehicle AR applications, the image data to be transmitted may contain icons for safety warnings, arrows for navigation guidance, or other information such as road backgrounds and sky textures. By performing content recognition and classification on the image data to be transmitted, the system can distinguish the different requirements of different image content types for transmission quality and latency, thus laying the foundation for subsequent transmission strategies.

[0031] Bandwidth requirements are the minimum threshold or requirement for communication link bandwidth, preset to ensure that image data can be successfully transmitted to the glasses with acceptable quality and smoothness. This condition serves as the benchmark for the system's transmission strategy decisions, and its specific value or range is directly related to the type of image content. For example, the bandwidth requirement for transmitting images containing a large amount of critical security information will be higher than that for transmitting images containing only non-critical background information. When the monitored actual bandwidth does not meet (i.e., is lower than) this bandwidth requirement, a data quality degradation mechanism is triggered to prioritize the continuity of basic transmission within limited bandwidth resources.

[0032] It is understandable that different types of image data to be transmitted (e.g., dynamic and complex entertainment videos versus static and simple navigation icons) require different minimum transmission resources to achieve a basic usable display effect. If a single, fixed bandwidth threshold is used as the judgment standard, it will not accurately reflect the actual transmission needs of different content, leading to inaccurate decision-making. Therefore, this embodiment adopts a technical solution of dynamically setting judgment criteria based on content type. By identifying the overall image content type of the image data to be transmitted, a more accurate bandwidth condition is determined accordingly. This avoids the defects of potentially unnecessary premature degradation when transmitting simple content or delayed degradation decision-making when transmitting complex content caused by using a fixed threshold. It achieves a more accurate and reasonable judgment of insufficient bandwidth, providing a reliable decision-making basis for subsequent data quality adjustments.

[0033] In specific implementation, step S20, which involves determining the bandwidth requirements for transmitting the image to be transmitted based on the image content type, may further include steps S21 to S23: Step S21: If the image content type includes an image content type, query the reference bandwidth condition associated with the image content type, and use the reference bandwidth condition as the bandwidth condition required to transmit the image to be transmitted. It should be noted that the reference bandwidth conditions are one or more quantized bandwidth thresholds pre-associated and bound to a specific image content type within the system's preset configuration information. These thresholds are used to determine whether the bandwidth meets the basic transmission requirements of that type of image. These conditions are baseline values ​​pre-set through testing or experience. For example, a lower reference bandwidth condition can be set for the "navigation arrow" type, while a higher reference bandwidth condition can be set for the "real-time video" type. When it is necessary to determine the bandwidth conditions required for transmitting an image, the system queries these preset correspondences and uses the matched reference bandwidth conditions as the decision-making basis for the current transmission task. This achieves the goal of dynamically adjusting the bandwidth sufficiency judgment criteria according to different content types.

[0034] Step S22: When the image content type includes multiple image content types, query the reference bandwidth conditions associated with each image content type, and take the reference bandwidth condition with the highest corresponding bandwidth threshold among the reference bandwidth conditions as the bandwidth condition required to transmit the image to be transmitted.

[0035] It is understandable that, since the image data to be transmitted may be composed of multiple image content types, such as a screen containing both navigation arrows and a background map, each image content type has different associated reference bandwidth conditions. If a lower threshold is used as the overall bandwidth condition, the system may not initiate optimization when bandwidth is slightly insufficient, leading to the risk of stuttering in the entire screen, including high-requirement types. Therefore, this implementation adopts a compatibility approach based on the highest requirements. After identifying multiple image content types, it actively queries all associated reference bandwidth conditions and selects the condition with the highest bandwidth threshold as the final unified bandwidth condition. This effectively avoids insufficient transmission guarantee for high-requirement content types caused by using too low a judgment standard in mixed content scenarios, which could lead to stuttering or blurring in some key areas of the screen. It achieves a more accurate assessment of the overall transmission requirements of composite images, ensuring that the system can reserve sufficient network resources for the most complex and demanding content types, thereby guaranteeing the basic quality baseline of the final composite screen's overall display effect at the decision-making source.

[0036] For example, the system pre-defines a lookup table that stores the correspondence between different image content types and reference bandwidth conditions. For instance, "navigation icons" are associated with 5Mbps, and "real-time video" is associated with 15Mbps. When the system detects that the image data to be transmitted contains both "navigation icons" and "real-time video" image content types, it retrieves two reference bandwidth conditions: 5Mbps and 15Mbps. Then, by comparison, it selects 15Mbps, which has the highest bandwidth threshold, as the final bandwidth condition required to transmit the composite image. Thus, by setting a unified judgment standard based on the most demanding content type, the system ensures that composite images containing high-bandwidth content receive sufficient resource guarantees during transmission decisions.

[0037] Step S30: If the actual bandwidth does not meet the bandwidth conditions, reduce the data quality of the image data to be transmitted, and transmit the image data to be transmitted with reduced data quality to the glasses.

[0038] Understandably, when the actual bandwidth is determined to be insufficient to meet the basic transmission requirements of the image data to be transmitted, i.e., when the bandwidth conditions are not met, insisting on transmitting the original data will inevitably lead to data packet congestion, increased latency, or even transmission interruption, directly causing screen stuttering. Therefore, this embodiment performs proactive adaptive degradation. Once insufficient bandwidth is determined, a global data quality reduction operation is immediately implemented on the image data to be transmitted, such as reducing the overall resolution or encoding bitrate, and the degraded data is still transmitted. This approach avoids the problems of image transmission jitter and sharp drop in frame rate caused by insufficient bandwidth and the lack of an adaptation strategy. It achieves the priority of ensuring continuous transmission of image data streams and basic display smoothness at the cost of controllable image quality loss under poor network conditions, thereby maintaining the core functions of the vehicle-mounted AR system.

[0039] For example, the vehicle-mounted system first continuously monitors the actual bandwidth of the communication link between the vehicle-mounted system and the glasses. Then, it identifies the image content type by real-time analysis of the image data to be transmitted, such as classifying it into "navigation information" or "entertainment video," and determines the fixed minimum bandwidth threshold corresponding to that type as the bandwidth requirement for transmission. When the actual bandwidth is determined to be lower than this threshold, the system initiates a unified degradation strategy, such as globally reducing the encoding bitrate of the image data to be transmitted, thereby reducing its overall data quality. The image data stream with the reduced bitrate is then transmitted to the glasses. This approach, by judging the image content as a whole type and implementing uniform, non-differentiated quality compression, ensures continuous data transmission when bandwidth is insufficient, effectively avoiding transmission interruptions and screen stuttering caused by network fluctuations, and maintaining basic smoothness of AR display in complex vehicle-to-everything (V2X) environments.

[0040] This embodiment provides an image data transmission method. By monitoring the actual bandwidth of the communication link between the vehicle-mounted device and the glasses, and identifying the image content type of the image data to be transmitted, the required bandwidth conditions for transmission are determined. When the actual bandwidth does not meet the bandwidth conditions, the data quality of the image data to be transmitted is actively reduced and transmitted to the glasses. This achieves adaptive adjustment to dynamic bandwidth fluctuations. In other words, by dynamically matching bandwidth requirements according to the image content type, and prioritizing data quality reduction rather than interrupting transmission when bandwidth is insufficient, the image transmission jitter problem caused by drastic bandwidth fluctuations is effectively avoided. This significantly reduces AR screen stuttering, ghosting, and latency, ensuring the continuity and real-time performance of the visual effect, and ultimately improving the information acquisition effect for users in in-vehicle AR application scenarios.

[0041] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in Embodiment 1 above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 2 The bandwidth conditions include multiple bandwidth conditions corresponding to different bandwidth thresholds, and step S30 may further include steps S31 to S32: Step S31: Determine at least one target bandwidth condition that does not meet the actual bandwidth condition among the bandwidth conditions, and obtain the data transmission optimization strategy corresponding to the target bandwidth condition, wherein one target bandwidth condition corresponds to one data transmission optimization strategy; It should be noted that the target bandwidth condition refers to the specific bandwidth conditions among multiple preset bandwidth conditions corresponding to different bandwidth thresholds, which the system determines are insufficient to meet the actual bandwidth of the current communication link. For example, if the system presets two bandwidth conditions, "Smoothness Condition (requires 20Mbps)" and "Basic Condition (requires 10Mbps)," and the current actual bandwidth is only 8Mbps, then both of these conditions become target bandwidth conditions; if the current actual bandwidth is 15Mbps, then the Smoothness Condition becomes the target bandwidth condition. This condition is used to accurately identify the deficiencies of the current network environment relative to all preset quality levels, thus providing a clear target for subsequently selecting a matching optimization strategy.

[0042] Data transmission optimization strategies are specific operational plans, pre-associated with specific target bandwidth conditions, that guide how to reduce the data quality of the image data to be transmitted. Each strategy clearly specifies the data quality adjustments to be made to adapt to a specific level of bandwidth insufficiency, and may include specific instructions such as "reducing the overall resolution to 720p," "enabling inter-frame coding," or "limiting the frame rate to 30fps." This strategy ensures that the system can perform graded data quality reduction operations that match the severity of the bandwidth insufficiency.

[0043] Step S32: Execute the data transmission optimization strategy to reduce the data quality of the image data to be transmitted, and transmit the image data to be transmitted with reduced data quality to the glasses.

[0044] Understandably, a single bandwidth condition and degradation strategy are often insufficient to adapt to the complex and fluctuating bandwidth of vehicle-to-everything (V2X) networks. Setting only a fixed degradation threshold and a single optimization method may lead to unnecessary image quality loss due to an overly aggressive strategy when bandwidth is slightly insufficient, or to ineffective lag mitigation due to an overly mild strategy when bandwidth is severely insufficient. Therefore, this embodiment employs a technical solution that sets multiple tiered bandwidth conditions and pre-associates them with different levels of data transmission optimization strategies. When the actual bandwidth is detected to be inconsistent with one or more target bandwidth conditions, the system can precisely trigger optimization strategies of varying degrees based on the specific severity of the bandwidth deficiency. This approach avoids the imbalance between image quality and smoothness caused by a single, coarse-grained degradation strategy. It achieves refined and gradual control of data quality based on the severity of network degradation, thereby ensuring smooth transmission in a tiered manner while maintaining relatively good image quality, achieving a better balance between bandwidth resources and visual experience.

[0045] In specific implementation, the data transmission optimization strategy includes a first optimization strategy, a second optimization strategy, and a third optimization strategy. Step S32 may include one or more steps A321 to A323: Step A321: Execute the first optimization strategy to reduce the resolution of the image data to be transmitted, and transmit the image data to be transmitted with reduced resolution to the glasses. It should be noted that the first optimization strategy is a specific operational scheme that reduces the amount of data in the image data to be transmitted by lowering its resolution. This strategy directly reduces the size of the image pixel matrix, for example, from 1920x1080 to 1280x720, thereby significantly reducing the total amount of data in the image data to be transmitted while maintaining acceptable visual clarity, in order to adapt to transmission environments with insufficient bandwidth.

[0046] Step A322: Execute the second optimization strategy to perform inter-frame coding on the video stream constructed from the image data to be transmitted, and transmit the inter-frame coded video stream to the glasses. It should be noted that the second optimization strategy is a data processing scheme that improves compression efficiency by changing the encoding method of the video stream. The core of this strategy is the use of inter-frame coding technology. By reducing the number of keyframes (I-frames) in the video stream and increasing the proportion of predicted frames (P-frames, B-frames) that utilize the correlation between preceding and following frames for compression, a higher overall compression ratio and data reduction are achieved while maintaining continuous playback. Inter-frame coding is a video compression technique that does not independently encode all information in each frame. Instead, for multiple consecutive frames in a video sequence, only one frame (the reference frame or I-frame) is fully encoded. For subsequent frames (P-frames or B-frames), only the motion information and residual data that differ from the reference frame are encoded. This encoding method, which utilizes temporal redundancy, can significantly reduce the total data volume of the video stream.

[0047] Step A323: Execute the third optimization strategy to reduce the frame rate of the video stream constructed from the image data to be transmitted, and transmit the video stream with reduced frame rate to the glasses.

[0048] It should be noted that the third optimization strategy is a scheme to reduce the total amount of data transmitted per unit time by reducing the frame rate of the video stream constructed from the image data to be transmitted. This strategy directly reduces the number of image frames transmitted per second, for example, from 60fps to 30fps. By sacrificing the smoothness of dynamic images in exchange for a reduction in data transmission load, it is also an effective means to deal with severe bandwidth shortages.

[0049] It is understandable that due to different degrees of bandwidth degradation and image content characteristics, there are different requirements for the dimensions of data quality reduction. If only a single type of optimization method is provided, such as only reducing the resolution, it is difficult to achieve the best balance between image quality loss and smoothness guarantee in all scenarios. Therefore, this implementation provides a variety of data transmission optimization strategies that can be executed independently or in combination. Specifically, it includes reducing the resolution through the first optimization strategy, enabling inter-frame coding to improve compression efficiency through the second optimization strategy, and reducing the frame rate through the third optimization strategy. This avoids the problem of poor adjustment effect under specific network conditions or content types and inability to flexibly adapt to diverse needs caused by a single optimization method. It enables targeted or combined adjustments to data quality from multiple physical dimensions, namely spatial resolution, coding efficiency, and temporal frame rate, according to specific scenarios. This greatly enhances the system's ability to adapt to complex network environments and diverse content, and achieves a more refined and effective trade-off between saving bandwidth and maintaining usable visual quality.

[0050] Furthermore, it should be noted that the execution order of the first, second, and third optimization strategies is not fixed. Instead, it can be dynamically adjusted and combined based on the characteristics of the image data to be transmitted, the specific degree of network degradation, and the priority requirements for specific quality dimensions (such as static clarity or dynamic smoothness). For example, the system can prioritize configuring the third optimization strategy for the target bandwidth condition with the highest corresponding bandwidth threshold, in order to quickly reduce the data load by executing the third optimization strategy that reduces the frame rate. Alternatively, it can prioritize configuring the first optimization strategy for the target bandwidth condition with the highest corresponding bandwidth threshold, in order to execute the first optimization strategy that reduces the resolution to maintain the frame rate. This flexible configuration of the execution order allows the system to avoid the problem of poor adjustment effects in certain specific scenarios caused by fixed pipeline processing, thereby achieving the optimal effect of multi-dimensional and adaptive adjustment of data quality according to real-time needs.

[0051] In this embodiment, by employing multiple bandwidth conditions corresponding to different bandwidth thresholds and associating each condition with a specific data transmission optimization strategy, a gradient decision-making and execution mechanism is established. This avoids the problem of mismatch between the degree of image quality degradation and the degree of network deterioration caused by using a single, fixed optimization strategy when bandwidth fluctuates, and the lack of flexibility in the adjustment process. It effectively realizes the precise triggering of corresponding levels of data quality optimization operations based on the specific insufficiency of the actual bandwidth relative to multiple preset thresholds. Thus, while ensuring basic transmission smoothness, it achieves more refined utilization of network resources and better protection of image quality.

[0052] In one possible implementation, step S301 may be included before step S32: Step S301: Perform region identification on the image data to be transmitted to determine the key regions and non-key regions in the image data to be transmitted, so as to execute the data transmission optimization strategy to reduce the data quality of the key regions and the non-key regions respectively. The degree of data quality degradation in the critical areas is less than that in the non-critical areas.

[0053] It's important to clarify that critical areas refer to image regions in the transmitted image data that carry visual information crucial to user experience or safety. These regions typically contain information that users need to clearly, accurately, and promptly identify, such as navigation route arrows, forward collision warning icons, and text information like vehicle speed. Ensuring the display quality of these areas is vital for maintaining the core functionality of in-vehicle AR applications. Non-critical areas, on the other hand, refer to image regions in the transmitted image data whose information importance is lower than that of critical areas, or whose visual fidelity requirements are not high. These areas typically constitute the background or surrounding visual elements of an image, such as road textures, the sky, and the sides of buildings. Even if the data quality in these areas is significantly reduced, it will not significantly affect the user's acquisition of critical information or pose a safety risk.

[0054] Key and non-key areas are identified and determined through real-time intelligent content analysis of the image data to be transmitted. That is, the system comprehensively uses computer vision technology and specific rules. For example, it uses object recognition algorithms to locate the areas where predefined key objects such as safety warning icons and navigation symbols are located and classifies them as key areas. At the same time, it can combine gaze tracking technology to determine the area where the user is currently focused and classify it as a key area as well. Other areas that are not identified as containing key information or are located at the edge of the user's field of vision are classified as non-key areas.

[0055] Understandably, when actual bandwidth is insufficient, indiscriminately reducing the global data quality of all areas of the image data to be transmitted, while ensuring smooth transmission, can lead to critical information (such as safety warnings) becoming blurry, thus impairing the core function of AR display. Therefore, this implementation method employs region recognition and differentiated processing techniques. First, it identifies key and non-key areas in the image data to be transmitted. Then, when implementing data transmission optimization strategies, it applies a smaller degree of data quality reduction to key areas and a larger degree of data quality reduction to non-key areas. This avoids the problem of impaired display quality of key information and impact on user understanding and safety interpretation caused by global uniform degradation. It achieves accurate and intelligent compression of data volume under limited bandwidth resources, thereby effectively alleviating transmission pressure while maximizing the clarity and usability of core information in the image, and improving the overall display performance in bandwidth-constrained scenarios.

[0056] In the specific implementation process, step S32 may also include steps B321 to B322: Step B321: Execute the fourth optimization strategy to reduce the resolution of image data in the critical area to a first resolution, reduce the resolution of image data in the non-critical area to a second resolution, and transmit the reduced-resolution image data to the glasses, wherein the first resolution is greater than the second resolution; and / or Step B322: Execute the fifth optimization strategy to perform intra-frame encoding on key regions in the video stream constructed from the image data to be transmitted, perform inter-frame encoding on non-key regions in the video stream, and transmit the encoded video stream to the glasses. The key regions in the video stream correspond to the key regions in the image data to be transmitted, and the non-key regions in the video stream correspond to the non-key regions in the image data to be transmitted.

[0057] It should be noted that intra-frame coding is another video compression technique characterized by the independent and complete encoding of a single image frame, without relying on any other image frames before or after it. During the encoding process, spatial redundancy within the frame—that is, the correlation between adjacent pixels within the same frame—is utilized for compression using techniques such as discrete cosine transform. This encoding method can generate independently decodeable complete frames, ensuring the clarity and accuracy of the image within that frame, but its compression efficiency is relatively low. Therefore, in this embodiment, intra-frame coding is specifically used to process image data in critical areas to ensure that this important information retains high fidelity after transmission.

[0058] It is understandable that simply applying different levels of data quality reduction to different regions may not fully utilize bandwidth resources, as different quality adjustment dimensions (such as resolution and encoding method) have different impact mechanisms on visual fidelity and data volume. Therefore, this implementation adopts a combined approach of implementing differentiated resolution adjustment and differentiated encoding method selection for different regions. Specifically, it executes the fourth optimization strategy to reduce the resolution of key regions to a higher first resolution and non-key regions to a lower second resolution, and / or executes the fifth optimization strategy to use intra-frame encoding for key regions to maintain sharpness and inter-frame encoding for non-key regions to improve compression efficiency. This avoids the possibility of not achieving the optimal balance between compression efficiency and visual quality when only adjusting a single dimension or using the same encoding strategy for different regions. It achieves fine-grained differentiation processing at both the pixel precision and encoding algorithm levels, thereby providing the highest level of quality assurance for key information within a given limited bandwidth, while maximizing the data compression benefits of non-key regions, achieving more extreme bandwidth utilization efficiency and a better overall visual experience.

[0059] Furthermore, it should be noted that the execution order of the fourth and fifth optimization strategies is not fixed. Instead, it can be flexibly selected and combined based on the current network conditions, the specific content of the image data to be transmitted, and the emphasis on real-time requirements. For example, the system can prioritize configuring the fourth optimization strategy for the target bandwidth condition with the highest corresponding bandwidth threshold to quickly reduce the data volume in non-critical areas. Conversely, it can prioritize configuring the fifth optimization strategy for the target bandwidth condition with the highest corresponding bandwidth threshold to utilize the efficient compression characteristics of inter-frame coding. This configurability in execution order and combination allows the system to avoid problems such as poor optimization effects or insufficient resource utilization in specific scenarios caused by fixed and rigid processing flows. This achieves the optimal effect of multi-dimensional, adaptive quality adjustment of critical and non-critical areas according to real-time requirements.

[0060] In this embodiment, by first identifying key and non-key areas in the image data to be transmitted, and then applying different degrees of data quality reduction to both when executing the data transmission optimization strategy, the problem of simultaneous decline in the display quality of key information and impact on the user's cognition and interpretation of core content caused by global uniform degradation of the image due to insufficient bandwidth is effectively avoided. This achieves intelligent and targeted compression of data volume under limited bandwidth conditions, thereby effectively ensuring smooth transmission while maximizing the maintenance of the display quality of key areas, significantly improving the accuracy of information transmission and user experience in bandwidth-constrained scenarios.

[0061] Based on the first and / or second embodiments of this application, in the third embodiment of this application, the content that is the same as or similar to that in embodiments one and two above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 3 After step S30, the image data transmission method may further include steps S40-S50: Step S40: Monitor the smoothness index and feedback data of the video stream constructed from the image data to be transmitted received by the glasses. It should be noted that smoothness metrics are objective measurement parameters used to quantitatively evaluate the smoothness of video stream playback received by the glasses. These metrics may include, but are not limited to, the actual frame rate received by the glasses, the latency between video frames, and the number of stutters caused by data packet loss or delay. By monitoring these metrics, the system can objectively determine whether the currently adopted transmission strategy effectively guarantees basic visual smoothness.

[0062] Feedback data originates from qualitative or quantitative information about user interaction behavior or subjective experience on the glasses. This type of data can include user evaluations of image quality submitted through specific interfaces, such as "smooth" or "laggy," or it may include experience quality data indirectly inferred by the system through monitoring user interactions, such as the synchronization between head movements and image updates. This data is an important supplement to objective smoothness indicators, reflecting the user's subjective perception.

[0063] Step S50: Adjust the bandwidth conditions and the data transmission optimization parameters corresponding to the bandwidth conditions according to the smoothness index and the feedback data, wherein the data transmission optimization parameters are used to control the degree of reduction in data quality.

[0064] It should be noted that data transmission optimization parameters refer to various adjustable variables used to specifically control the degree of data quality degradation when executing data transmission optimization strategies. For example, in a strategy to reduce resolution, the parameter is the specific value of the target resolution, such as 720p or 480p; in a strategy to reduce frame rate, the parameter is the specific value of the target frame rate, such as 30fps or 15fps. By adjusting these parameters, the system can precisely control the extent of data quality degradation.

[0065] It is understandable that the initially preset bandwidth conditions and data transmission optimization parameters may not always remain optimal in the complex real-world vehicle network environment. Fixed settings are difficult to adapt to the dynamically changing network characteristics and user subjective experiences in the long term, resulting in the system performance gradually deviating from the best state. Therefore, this embodiment adopts closed-loop feedback and adaptive optimization techniques. That is, after the data quality is reduced and transmitted, the smoothness index and feedback data of the glasses are continuously monitored, and the bandwidth threshold and data transmission optimization parameters that control the degree of data quality reduction are dynamically adjusted based on these real-time effect evaluations. This can effectively avoid the problem that the optimization effect gradually declines or remains unsatisfactory due to the inability of fixed system parameters to adapt to long-term network environment changes and user personalized needs. It realizes continuous self-calibration and long-term adaptive optimization of system parameters, thereby ensuring that the image data transmission method can intelligently track and adapt to changes in the external environment and user habits, and always maintain efficient and stable optimization effects.

[0066] For example, the system continuously collects the actual frame rate and inter-frame jitter of the video stream as smoothness indicators through sensors built into the glasses, and records the "screen acceleration" command triggered by the user by touching the temples as feedback data. When the analysis shows that the frame rate is stable but the jitter value exceeds the standard or the user frequently requests acceleration, the system automatically increases the "optimization threshold" from 15Mbps to 18Mbps, and simultaneously adjusts the frame rate parameter in the third optimization strategy from 30fps to 40fps, thereby achieving closed-loop parameter optimization based on objective performance and explicit interaction.

[0067] In another example, the system uses clock synchronization between the vehicle-mounted system and the glasses to accurately measure end-to-end transmission latency as a core smoothness indicator, while simultaneously collecting pupil focusing response time when the user continuously gazes at a specific AR icon as implicit feedback data. When a transmission latency exceeding 50ms or a significant increase in focusing response is detected, the system automatically adjusts the "protection threshold" from 8Mbps to 10Mbps and reverts the resolution parameter of non-critical areas in the fourth optimization strategy from 480p to 720p, thereby achieving adaptive parameter calibration based on physiological behavior data and precise timing measurements.

[0068] In this embodiment, by continuously monitoring the smoothness index and feedback data of the glasses, and dynamically adjusting the bandwidth conditions and data transmission optimization parameters accordingly, the problem of the system optimization effect gradually deteriorating or never reaching the optimal level due to the inability to adapt to long-term network environment changes and personalized user needs caused by fixed preset parameters is avoided. This realizes the system's continuous self-learning and closed-loop optimization of the transmission strategy, thereby ensuring that the image data transmission method can intelligently adapt to changes in the external environment and user habits, and maintain a high-efficiency and stable display smoothness improvement effect in the long term.

[0069] Based on the first and / or second and / or third embodiments of this application, in the fourth embodiment of this application, the content that is the same as or similar to the above-described embodiments one, two, and three can be referred to the above description and will not be repeated hereafter. Based on this, please refer to... Figure 4 The vehicle-mounted device and the glasses-mounted device are also connected to the cloud for communication. Before step S20, the image data transmission method may further include steps S100 to S200: Step S100: Identify the task type of each image computing task, and determine the low computing power requirement computing task and the high computing power requirement computing task in each image computing task according to the task type, wherein the low computing power requirement computing task is used to calculate the image data to be transmitted. It's important to note that image computing tasks are specific computational units performed to generate, render, or process image data to be transmitted. These tasks can include a series of steps such as building a 3D model from raw data, adding textures to the model, performing lighting calculations, and finally generating a 2D image frame. This is the fundamental process for generating AR visual content. The task types of image computing tasks are categorized based on their computational resource consumption, real-time processing requirements, and algorithmic complexity. For example, they can be divided into different types such as "graphical user interface rendering," "simple geometric transformations," or "complex physics simulations," each corresponding to different computational resource requirements.

[0070] Low-computing-power-requirement computing tasks refer to those with low computational complexity, which can be completed quickly without powerful parallel computing capabilities, and whose processing results can be directly used to construct the image data to be transmitted. These tasks typically have deterministic algorithms and short processing latency, such as the synthesis of 2D navigation icons and the rasterization of text information.

[0071] High-computing-power-demand computing tasks refer to those involving complex calculations, requiring substantial computing resources and significant time to complete. These tasks typically involve large-scale data processing or complex algorithms, such as real-time rendering of high-precision 3D city models, calculation of global illumination effects, or generation of complex particle effects.

[0072] Additionally, it should be noted that low-computing-power-requirement and high-computing-power-requirement computing tasks are identified by analyzing the computational characteristics of each task and based on preset rules. The system analyzes each image computing task according to preset computational complexity classification rules associated with the task type. For example, tasks involving 2D interface rendering or simple geometric transformations are identified as low-computing-power-requirement tasks, while tasks involving complex 3D model rendering or large-scale physical simulations are identified as high-computing-power-requirement tasks, thereby achieving automated differentiation of task computational power requirements.

[0073] Step S200: The high-computing-power-requirement computing task is migrated to the cloud, so that after the cloud executes the high-computing-power-requirement computing task, the obtained supplementary image data is transmitted to the glasses.

[0074] It should be noted that the supplementary image data refers to the portion of image data generated and sent to the glasses after the cloud performs high-computing-demand tasks migrated from the vehicle's infotainment system. This data includes complex rendering results that the vehicle's infotainment system cannot complete in real time due to limited local computing power, such as high-precision 3D models, complex lighting effects, or dynamic particle effects. These data need to be combined with the image data to be transmitted from the vehicle's infotainment system on the glasses to form the complete image information displayed at the end.

[0075] Understandably, given the limited local computing resources on both the vehicle-mounted system and the glasses, executing all image computation tasks locally would make it difficult to simultaneously guarantee the quality of generating highly complex image content and the real-time performance of the final transmission. This is especially true when dealing with complex 3D scenes, where local computing bottlenecks can directly lead to delays in generating image data to be transmitted, exacerbating the burden on the transmission process. Therefore, this embodiment employs a cloud-based collaborative rendering solution. This involves first identifying the task type of each image computation task to distinguish between low-computing-power-requirement and high-computing-power-requirement tasks. Then, high-computing-power-requirement tasks are migrated to the cloud for execution. After complex rendering is completed in the cloud, the resulting supplementary image data is directly sent to the glasses. This avoids delays in generating image data to be transmitted due to local computing resource overload, which in turn affects the real-time performance and stability of the entire transmission link. It achieves efficient allocation of computing load between the cloud and local systems, thereby reducing the processing pressure on the vehicle-mounted system at the source, ensuring that image data to be transmitted is ready for transmission in a timely manner, and improving the overall system response speed and display real-time performance.

[0076] For example, the system first identifies the computational tasks required to generate the AR navigation interface as "road model rendering" and "navigation arrow drawing." Using predefined rules, the computationally intensive "road model rendering" is classified as a high-power-requirement task, while the simpler "navigation arrow drawing" is classified as a low-power-requirement task. Subsequently, the system migrates the "road model rendering" task to a cloud server for execution. After rendering is completed in the cloud, the generated supplementary image data containing the 3D road model is directly sent to the glasses. Simultaneously, the vehicle's infotainment system locally executes the "navigation arrow drawing" task to generate image data to be transmitted, which can be adjusted for quality before being transmitted to the glasses. Finally, the glasses synthesize the received image data to be transmitted (navigation arrows) with the supplementary image data (road model) to output a complete AR navigation image, thus achieving optimized allocation of computing resources through cloud-based collaborative resource sharing.

[0077] In this embodiment, by identifying the task type of image computing tasks and distinguishing between low-computing-power and high-computing-power-requirement computing tasks, high-computing-power-requirement computing tasks are migrated to the cloud for execution. This avoids the problem that high-complexity rendering tasks cannot be completed in time due to limited local computing resources on the vehicle-mounted system, which would cause delays in the generation of image data to be transmitted and affect the real-time performance and stability of the entire transmission link. This achieves efficient collaborative allocation of computing load between the cloud and local devices, thereby ensuring the timely generation and readiness of image data to be transmitted from the source, and improving the system's ability to process complex image content and the real-time performance of the overall display.

[0078] Based on the first and / or second and / or third and / or fourth embodiments of this application, in the fifth embodiment of this application, the content that is the same as or similar to the above-described embodiments one, two, three, and four can be referred to the above description and will not be repeated hereafter. Based on this, please refer to... Figure 5 The image data transmission method provided in this embodiment is applied to the glasses end, which is communicatively connected to the vehicle's infotainment system. The image data transmission method includes steps S01-S02: Step S01: Receive image data to be transmitted after the data quality has been reduced from the data transmitted by the vehicle-mounted terminal. The image data to be transmitted after the data quality has been reduced is obtained by the vehicle-mounted terminal reducing the data quality of the image data to be transmitted when it detects that the actual bandwidth of the communication link between the vehicle-mounted terminal and the glasses terminal does not meet the bandwidth conditions required for transmitting the image data to be transmitted. The bandwidth conditions are determined by the vehicle-mounted terminal by identifying the image content type of the image data to be transmitted and based on the image content type. Step S02: If the image data to be transmitted after the data quality reduction is a video stream with a reduced frame rate, frame interpolation is performed on the video stream, and the interpolated video stream is output.

[0079] It is understandable that, due to insufficient bandwidth, the vehicle-mounted system may adopt a third optimization strategy of reducing the video stream frame rate. This will directly lead to a decrease in the native frame rate of the video stream transmitted to the glasses. If the glasses simply play this low frame rate stream, users will experience obvious screen stuttering and motion discontinuity. Therefore, this embodiment adopts a terminal frame interpolation compensation technique. When the glasses receive the video stream with a reduced frame rate, they use their built-in processing capabilities to intelligently generate and insert intermediate frames between adjacent native frames. This effectively avoids the problems of screen jumping, ghosting, and loss of motion continuity caused by the source actively reducing the frame rate. Under the condition of limited transmission bandwidth, the visual frame rate is restored to a smooth level through terminal post-processing. Thus, without increasing the transmission load, the final visual smoothness experience is effectively improved, compensating for the negative visual experience caused by the source frame reduction strategy.

[0080] For example, after the glasses receive a video stream consisting of image data to be transmitted from the vehicle's head unit, whose frame rate has been reduced from 60fps to 30fps due to insufficient bandwidth, the glasses use its built-in image signal processor to calculate and generate intermediate frames in real time based on the pixel motion trajectory between two adjacent frames using a motion compensation algorithm. This increases the actual display frame rate of the video stream from 30fps back to 60fps, and finally outputs a smooth video with interpolated frames. Thus, under the premise that the amount of transmitted data has been reduced, the terminal compensation mechanism effectively eliminates the stuttering caused by the frame rate reduction at the source end.

[0081] In this embodiment, by performing motion compensation and frame interpolation on the received video stream with reduced frame rate at the glasses end, the problems of discontinuous motion, stuttering, and ghosting in the terminal display caused by the reduction of video stream frame rate at the vehicle-mounted system to save bandwidth are avoided. This achieves the restoration of the visual frame rate to a smooth level through terminal post-processing under the premise that the amount of transmitted data has been reduced. Thus, without increasing the transmission load, the final visual smoothness experience is effectively improved, and the negative visual experience caused by the source end frame reduction strategy is compensated.

[0082] In one feasible implementation, the vehicle-mounted terminal and the glasses terminal are also respectively connected to the cloud for communication, and the image data transmission method may further include steps S03-S04: Step S03: Receive supplementary image data transmitted from the cloud; Step S04: Combine the image data to be transmitted after the data quality reduction with the supplementary image data to obtain complete image information, and output the complete image information.

[0083] It should be noted that the complete image information is generated by the glasses through image compositing, which merges the image data to be transmitted from the vehicle's infotainment system (which has reduced data quality) with supplementary image data from the cloud. This results in the final image that the user can directly view. This information is an organic combination of the core information rendered locally on the vehicle's infotainment system and the high-quality, complex rendering result completed in the cloud, together forming a visually and functionally complete and unified augmented reality display.

[0084] Understandably, since the glasses ultimately need to display a complete augmented reality image, which may be composed of basic image data to be transmitted processed by the vehicle's infotainment system and high-quality supplementary image data processed by the cloud, if the glasses only process a single data stream from the vehicle's infotainment system, it cannot present the complex visual elements rendered by the cloud, resulting in incomplete final image information. Therefore, this implementation method performs multi-source data reception and image synthesis. That is, while receiving the image data to be transmitted from the vehicle's infotainment system (which has reduced data quality), the glasses also receive supplementary image data transmitted from the cloud, and fuse these two parts of data at the terminal. This avoids the problems of fragmented final display, missing visual elements, or incoherent context caused by distributed rendering tasks. It achieves seamless integration of image data from different computing nodes into a unified and complete visual image at the terminal, thereby ensuring that the end user sees a complete and visually unified augmented reality image while utilizing cloud computing power to improve image quality richness.

[0085] For example, the glasses simultaneously receive a navigation arrow video stream from the vehicle's infotainment system (which has undergone data quality downgrading) and pre-rendered high-precision 3D road model data from the cloud as supplementary image data. The glasses then utilize their built-in compositing engine to spatially align and layer-blend the dynamic navigation arrows with the static 3D road model, generating a complete AR navigation screen with correct spatial relationships containing all necessary visual elements, and outputting it for display. This achieves seamless integration and unified presentation of distributed rendering results through terminal compositing.

[0086] For example, to help understand the implementation flow of the image data transmission method obtained by combining this embodiment with the above embodiment one, please refer to... Figure 6 , Figure 6 A simplified flowchart of an image data transmission method is provided, specifically: The system begins by monitoring the real-time bandwidth of the vehicle-to-everything (V2X) network, specifically the actual bandwidth of the communication link between the vehicle's infotainment system and the AR glasses. Based on bandwidth sufficiency, it makes branching decisions: if bandwidth is sufficient, the image data is transmitted at its original quality; if bandwidth is insufficient, a dynamic adjustment strategy is initiated. This strategy's core components include: intelligent content analysis to distinguish between critical and non-critical areas, performing differentiated area transmission accordingly, supplemented by adaptive encoding compression, adaptive frame rate, and frame interpolation. It also encompasses cloud-edge collaborative rendering to share the computational load. Finally, all processing results are displayed on the AR glasses, and a feedback optimization loop is formed through continuous monitoring of display smoothness and user experience, dynamically adjusting the parameters of each step. This fully realizes the entire process from bandwidth perception and intelligent degradation to terminal compensation and self-optimization.

[0087] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the image data transmission method of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0088] This application provides an electronic device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the image data transmission method in Embodiment 1 above.

[0089] The following is for reference. Figure 7This document illustrates a structural diagram of an electronic device suitable for implementing the embodiments of this application. The electronic device in the embodiments of this application may include, but is not limited to, a tablet computer, a personal computer, a mobile phone, or an electronic device, vehicle system, or glasses system capable of achieving the aforementioned functions. The glasses system may include, but is not limited to, head-mounted display devices such as Mixed Reality (MR) glasses, Augmented Reality (AR) glasses, Virtual Reality (VR) glasses, Extended Reality (XR) glasses, or some combination thereof. In this embodiment, for ease of description, a wearable device will be used as the execution subject for the following description. Figure 7 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0090] like Figure 7 As shown, the electronic device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory 1002 or a program loaded from a storage device 1003 into a random access memory 1004. The random access memory 1004 also stores various programs and data required for the operation of the electronic device. The processing unit 1001, the read-only memory 1002, and the random access memory 1004 are interconnected via a bus 1005. An input / output interface 1006 is also connected to the bus. Typically, the following systems can be connected to the input / output interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. The communication device 1009 allows the electronic device to communicate wirelessly or wiredly with other devices to exchange data. Although the diagrams show electronic devices with various systems, it should be understood that it is not required to implement or have all of the systems shown. More or fewer systems may be implemented alternatively.

[0091] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from read-only memory 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0092] The electronic device provided in this application, employing the image data transmission method described in the above embodiments, can solve the technical problem of screen stuttering that easily occurs during the use of current in-vehicle AR glasses. Compared with the prior art, the beneficial effects of the electronic device provided in this application are the same as those of the image data transmission method provided in the above embodiments, and other technical features of this electronic device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0093] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0094] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0095] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. An image data transmission method, characterized by, The image data transmission method is applied to a car machine end in communication connection with a glasses end, and comprises the following steps: Monitoring an actual bandwidth of a communication link between the car machine end and the glasses end; Identifying an image content type of image data to be transmitted, and determining a bandwidth condition required for transmitting the image data to be transmitted according to the image content type; In a case where the actual bandwidth does not meet the bandwidth condition, reducing data quality of the image data to be transmitted, and transmitting the image data to be transmitted with reduced data quality to the glasses end.

2. The image data transmission method of claim 1, wherein, The step of determining the bandwidth condition required for transmitting the image data to be transmitted according to the image content type comprises: In a case where the image content type includes one image content type, querying a reference bandwidth condition associated with the image content type, and taking the reference bandwidth condition as the bandwidth condition required for transmitting the image data to be transmitted; In a case where the image content type includes multiple image content types, querying reference bandwidth conditions associated with the image content types, and taking a reference bandwidth condition with the highest corresponding bandwidth threshold value among the reference bandwidth conditions as the bandwidth condition required for transmitting the image data to be transmitted.

3. The image data transmission method of claim 1, wherein, The bandwidth condition includes multiple bandwidth conditions corresponding to different bandwidth threshold values, and the step of reducing data quality of the image data to be transmitted and transmitting the image data to be transmitted with reduced data quality to the glasses end comprises: Determining at least one target bandwidth condition in which the actual bandwidth does not meet in each bandwidth condition, and obtaining a data transmission optimization strategy corresponding to the target bandwidth condition, wherein one target bandwidth condition corresponds to one data transmission optimization strategy; Executing the data transmission optimization strategy to reduce data quality of the image data to be transmitted, and transmitting the image data to be transmitted with reduced data quality to the glasses end.

4. The image data transmission method of claim 3, wherein, The data transmission optimization strategy includes a first optimization strategy, a second optimization strategy and a third optimization strategy, and the step of executing the data transmission optimization strategy to reduce data quality of the image data to be transmitted and transmitting the image data to be transmitted with reduced data quality to the glasses end comprises: Executing the first optimization strategy to reduce resolution of the image data to be transmitted, and transmitting the image data to be transmitted with reduced resolution to the glasses end; and / or Executing the second optimization strategy to inter-frame encode a video stream constructed by the image data to be transmitted, and transmitting the inter-frame encoded video stream to the glasses end; and / or Executing the third optimization strategy to reduce frame rate of a video stream constructed by the image data to be transmitted, and transmitting the video stream with reduced frame rate to the glasses end.

5. The image data transmission method of claim 3, wherein, Before the step of executing the data transmission optimization strategy to reduce data quality of the image data to be transmitted, the method further comprises the following steps: Performing region identification on the image data to be transmitted to determine a key region and a non-key region in the image data to be transmitted, so as to execute the data transmission optimization strategy to reduce data quality of the key region and the non-key region respectively; The data quality reduction degree of the key region is less than the data quality reduction degree of the non-key region.

6. The image data transmission method of claim 5, wherein, The data transmission optimization strategy further comprises a fourth optimization strategy and a fifth optimization strategy, and the step of executing the data transmission optimization strategy to reduce the data quality of the to-be-transmitted image data and transmitting the to-be-transmitted image data with reduced data quality to the glasses end comprises: the fourth optimization strategy is executed to reduce the resolution of the image data in the key area to a first resolution, reduce the resolution of the image data in the non-key area to a second resolution, and transmit the to-be-transmitted image data with reduced resolution to the glasses end, wherein the first resolution is greater than the second resolution; and / or the fifth optimization strategy is executed to intra-code the key area in the video stream constructed by the to-be-transmitted image data, inter-code the non-key area in the video stream, and transmit the coded video stream to the glasses end, wherein the key area in the video stream corresponds to the key area in the to-be-transmitted image data, and the non-key area in the video stream corresponds to the non-key area in the to-be-transmitted image data.

7. The image data transmission method of claim 1, wherein, After the step of transmitting the to-be-transmitted image data with reduced data quality to the glasses end, the method further comprises: monitoring the smoothness index and feedback data of the video stream constructed by the to-be-transmitted image data received by the glasses end; adjusting the bandwidth condition and the data transmission optimization parameter corresponding to the bandwidth condition according to the smoothness index and the feedback data, wherein the data transmission optimization parameter is used to control the degree of reducing the data quality.

8. The image data transmission method of claim 1, wherein, The car machine end and the glasses end are also respectively connected with the cloud end, and before the step of identifying the image content type of the to-be-transmitted image data, the method further comprises: identifying the task type of each image computing task, and determining the low-computing-power-demand computing task and the high-computing-power-demand computing task in the each image computing task according to the task type, wherein the low-computing-power-demand computing task is used to calculate the to-be-transmitted image data; migrating the high-computing-power-demand computing task to the cloud end, so that the cloud end transmits the obtained supplementary image data to the glasses end after executing the high-computing-power-demand computing task.

9. An image data transmission method characterized by, The glasses end is applied to, and the glasses end is connected with the car machine end, and the image data transmission method comprises: receiving the to-be-transmitted image data with reduced data quality transmitted by the car machine end, wherein the to-be-transmitted image data with reduced data quality is obtained by the car machine end in the case that the actual bandwidth of the communication link between the car machine end and the glasses end monitored by the car machine end does not meet the bandwidth condition required for transmitting the to-be-transmitted image data, and the bandwidth condition is determined by the car machine end by identifying the image content type of the to-be-transmitted image data and according to the image content type; in the case that the to-be-transmitted image data with reduced data quality is a video stream with reduced frame rate, the video stream is inserted, and the inserted video stream is output.

10. The image data transmission method of claim 9, wherein, The car machine end and the glasses end are also respectively connected with the cloud end, and the image data transmission method further comprises: receiving the supplementary image data transmitted by the cloud end; The data quality reduced to-be-transmitted image data is picture-synthesized with the supplementary image data to obtain complete image information, and the complete image information is output.

11. An electronic device, comprising: The device comprises a memory, a processor, and a computer program stored on the memory and executable on the processor, and the computer program is configured to implement the steps of the image data transmission method according to any one of claims 1 to 9.

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