Area rendering method and device, electronic equipment, storage medium and product

Abstract

The present disclosure provides a region rendering method and device, electronic equipment, storage medium and product. The method comprises: obtaining scene information of an original rendering region; performing feature extraction on the scene information to obtain a scene feature index of the original rendering region; dividing the original rendering region into at least two rendering regions based on the scene feature index, and performing a corresponding rendering operation on each rendering region to obtain rendering data corresponding to each rendering region, the rendering priorities of the at least two rendering regions being different; evaluating the rendering quality of each rendering region based on the rendering data to obtain a rendering score of each rendering region; and updating the rendering strategy of the rendering region based on the rendering score, so as to adjust the rendering resource according to the real-time change of the scene, reduce the consumption of invalid computing power, improve the problems of picture lag and picture blur, and improve the overall rendering efficiency and hardware rendering resource utilization rate, while taking into account the scene rendering picture quality and terminal device running fluency.

Description

Technical Field

[0001] This disclosure relates to the field of artificial intelligence technology, and in particular to a region rendering method, apparatus, electronic device, storage medium, and product. Background Technology

[0002] In related solutions, a fixed and unified global rendering strategy is usually adopted. However, different areas of the original rendering area may have different lighting intensities and different user attention levels. Continuing to use this global rendering strategy can easily lead to a large amount of ineffective computing power waste. At the same time, traditional rendering solutions cannot dynamically adjust the rendering strategy according to the frame rate and clarity defects of the real-time rendered image. The allocation of rendering resources is lagging and fixed, which cannot adapt to dynamically changing rendering scenes and terminal devices with different performance. This can easily lead to problems such as screen stuttering, screen blurring, and low hardware resource utilization, making it difficult to balance the quality of the rendered image with the smoothness of the terminal device. Summary of the Invention

[0003] This disclosure provides a region rendering method, apparatus, electronic device, storage medium, and product to solve problems in the related art.

[0004] A first aspect of this disclosure provides a region rendering method, the method comprising:

[0005] Obtain scene information for the original rendering area; The scene information is used to extract features to obtain the scene feature index of the original rendering area; Based on the scene feature index, the original rendering area is divided into at least two rendering areas, and a corresponding rendering operation is performed on each rendering area to obtain the rendering data corresponding to each rendering area. The rendering priorities of the at least two rendering areas are different. The rendering quality of each rendering region is evaluated based on the rendering data to obtain a rendering score for each rendering region; The rendering strategy for the rendering region is updated based on the rendering score.

[0006] In one embodiment, obtaining scene information of the original rendering area includes: Obtain ambient lighting information and user viewpoint information for the original rendered area; The ambient lighting information and the user's viewpoint information are time-stamp aligned to obtain the scene information of the original rendering area.

[0007] In one embodiment, the scene feature index includes an ambient lighting fluctuation index and a user viewpoint change index. The step of dividing the original rendering area into at least two rendering areas based on the scene feature index includes: If the difference between the ambient light fluctuation index and the target ambient light fluctuation threshold is greater than or equal to the first adjustment threshold, the light intensity of the original rendering area is adjusted according to the target light intensity value. If the difference between the ambient light fluctuation index and the target ambient light fluctuation threshold is less than the first adjustment threshold, the original rendering area is divided into at least two rendering areas based on the difference between the user viewpoint change index and the target user viewpoint change threshold.

[0008] In one embodiment, the original rendering area is divided into at least two rendering areas based on the difference between the user's viewpoint change index and the target user's viewpoint change threshold, including: In response to the difference between the user's viewpoint change index and the target user's viewpoint change threshold being greater than or equal to a second adjustment threshold, a rendering operation is performed on the original rendering area. In response to the difference between the user viewpoint change index and the target user viewpoint change threshold being less than the second adjustment threshold, the original rendering area is divided into at least two rendering areas based on the user's position and user viewpoint.

[0009] In one embodiment, based on the user's location and viewpoint, the original rendering area is divided into at least two rendering areas, including: The circular area within the user's viewpoint, centered on the user's position and with a radius equal to a first preset threshold, is defined as the high-priority rendering area. The area outside the high-priority rendering area within the user's viewpoint, centered on the user's position and with a radius equal to the second preset threshold, is defined as the medium-priority rendering area, where the first preset threshold is less than the second preset threshold. The remaining area within the original rendering area, excluding the high-priority rendering area and the medium-priority rendering area, is defined as the low-priority rendering area.

[0010] In one embodiment, the rendering score includes a frame rate stability score and an image sharpness score, and the rendering strategy for updating the rendering region based on the rendering score includes: If the frame rate stability score is lower than the target frame rate stability threshold, and / or the image clarity score is lower than the target image clarity threshold, the rendering strategy for the rendering region is updated.

[0011] A second aspect of this disclosure provides a region rendering apparatus, the apparatus comprising: The acquisition unit is used to acquire scene information of the original rendering area; The feature extraction unit is used to extract features from the scene information to obtain the scene feature index of the original rendering area; A partitioning unit is used to divide the original rendering region into at least two rendering regions based on the scene feature index, and to perform a corresponding rendering operation on each rendering region to obtain rendering data corresponding to each rendering region, wherein the at least two rendering regions have different rendering priorities. An evaluation unit is used to evaluate the rendering quality of each rendering region based on the rendering data, and obtain a rendering score for each rendering region. An update unit is used to update the rendering strategy of the rendering region based on the rendering score.

[0012] A third aspect of this disclosure provides an electronic device comprising: 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 to enable the at least one processor to perform the methods described in the first aspect of this disclosure.

[0013] A fourth aspect of this disclosure provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to perform the methods described in the first aspect of this disclosure.

[0014] A fifth aspect of this disclosure provides a computer program product including a computer program that, when executed by a processor, implements the methods described in the first aspect of this disclosure.

[0015] In summary, this disclosure proposes a region rendering method, which includes: acquiring scene information of an original rendering region; extracting features from the scene information to obtain a scene feature index of the original rendering region; dividing the original rendering region into at least two rendering regions based on the scene feature index, and performing corresponding rendering operations on each rendering region to obtain rendering data corresponding to each rendering region, wherein the at least two rendering regions have different rendering priorities; evaluating the rendering quality of each rendering region based on the rendering data to obtain a rendering score for each rendering region; and updating the rendering strategy of the rendering region based on the rendering score.

[0016] According to the solution provided in this disclosure, by acquiring scene information of the original rendering area and extracting scene feature indices, different priority rendering areas are divided according to the dynamic changes of the scene and differentiated rendering is performed. Then, the rendering quality is evaluated by combining the rendering data of different priority rendering areas to obtain a rendering score. Finally, the rendering strategy is updated based on the score. This can dynamically allocate rendering resources according to real-time changes in the scene, reduce the consumption of ineffective computing power, and optimize the rendering scheme strategy in real time based on rendering quality feedback. This can improve the problems of screen stuttering and screen blurring, improve the overall rendering efficiency and hardware rendering resource utilization, and take into account both the scene rendering quality and the smoothness of terminal device operation.

[0017] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure, and are not intended to unduly limit this disclosure.

[0019] Figure 1 A flowchart illustrating a region rendering method provided in an embodiment of this disclosure; Figure 2 A schematic diagram of a spatial coordinate system in a virtual reality scene provided in an embodiment of this disclosure; Figure 3 A schematic diagram of Euler angles from a user's perspective at a first time point, provided as an embodiment of this disclosure; Figure 4 A schematic diagram of Euler angles at a second time point from a user's perspective, provided as an embodiment of this disclosure; Figure 5 A schematic diagram of a virtual reality scene provided in an embodiment of this disclosure; Figure 6 A schematic diagram of yet another virtual reality scene provided in an embodiment of this disclosure; Figure 7 This is a schematic diagram of the structure of a region rendering apparatus provided in an embodiment of the present disclosure; Figure 8 This is a schematic diagram of the hardware composition structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0020] Embodiments of this disclosure are described in detail below. Examples of these embodiments are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this disclosure, and should not be construed as limiting this disclosure.

[0021] To facilitate a better understanding of the technical solutions described in the embodiments of this disclosure by those skilled in the art, the technical terms in the embodiments of this disclosure are explained as follows before introducing the embodiments of this disclosure.

[0022] With the rapid development of virtual reality technology, real-time rendering optimization methods based on deep learning have gradually become a key research direction for improving the immersion and interaction efficiency of virtual reality (VR) scenes. However, existing related technologies still have some shortcomings in terms of real-time performance, resource utilization efficiency, and the balance of rendering effects, making it difficult to fully meet the high-performance requirements of complex VR scenes.

[0023] The following is a brief introduction to two schemes of region rendering methods in related technologies: Solution A proposes to improve image rendering quality by combining neural radiation field technology to render the target object model and fusing the target object image into the environment object image. However, this solution mainly focuses on high-quality rendering of static scenes and has limited support for the real-time requirements of dynamic VR scenes. In addition, it relies on complex neural radiation field calculations, which may lead to high computational resource consumption, making it difficult to achieve efficient real-time rendering on resource-constrained devices.

[0024] Solution B proposes acquiring panoramic and scene region images, and then using deep learning to detect and match product information for real-time display. However, this solution primarily focuses on information matching and display in specific application scenarios, failing to adequately consider the impact of complex lighting and perspective changes in VR scenes on rendering quality. Furthermore, its algorithm design may not effectively handle the real-time rendering needs of large-scale scenes, leading to rendering latency or quality degradation.

[0025] The above solution has the following drawbacks: VR scene rendering technology based on deep learning still has certain shortcomings in terms of real-time performance, dynamic scene adaptability, and resource utilization efficiency.

[0026] To address the shortcomings of related technologies, this disclosure acquires scene information in real time and extracts scene feature indices. Based on dynamic changes in the scene, it adaptively divides rendering regions into different priority areas and performs differentiated rendering. Then, it combines the rendering data of different priority rendering regions to evaluate the rendering quality and obtain a rendering score. Finally, it updates the rendering strategy based on the score. This allows for dynamic allocation of rendering resources according to real-time changes in the scene, reducing unnecessary computing power consumption. At the same time, it optimizes the rendering scheme strategy in real time based on rendering quality feedback, which can improve issues such as screen stuttering and blurring, enhance overall rendering efficiency and hardware rendering resource utilization, and balance scene rendering quality with the smoothness of terminal device operation.

[0027] The present disclosure will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0028] The present disclosure provides a region rendering method that can be applied to virtual reality interactive scenarios, such as metaverse, VR virtual exhibition hall, VR virtual store tour, and VR entertainment interactive scenarios. The execution subject of the method can be a VR headset, a mobile VR device, or a cloud rendering server equipped with a rendering scheduler.

[0029] like Figure 1 As shown, Figure 1 This is a flowchart illustrating a region rendering method provided in an embodiment of this disclosure. The region rendering method provided in this embodiment includes the following steps: Step 101: Obtain scene information for the original rendering area; In one embodiment, the original rendering area refers to the complete 3D VR scene that the user is currently interacting with, including the entire virtual space within the view range of the VR headset.

[0030] In one embodiment, scene information refers to the dynamic perception information of the VR scene's real-time dynamic state. Scene information can include at least ambient lighting change information and user viewpoint dynamic information. Ambient lighting change information refers to the full amount of ambient lighting data collected from different priority rendering areas within the VR scene, such as spectral distribution intensity, the difference between the incident angle and the eye-view angle, and the polarization direction of the display device's electric field. This ambient lighting change information can be periodically collected by the VR-compatible lighting sensor. User viewpoint dynamic information includes the three-dimensional spatial coordinates of the head-mounted display at different times and Euler angles representing head posture. Euler angles can be divided into pitch angle, yaw angle, and roll angle. This user viewpoint dynamic information can be collected by the head-mounted display's built-in posture and position sensors.

[0031] In one embodiment, when acquiring scene information, timestamps can be added to both ambient lighting change information and user perspective dynamic information based on the timestamp of the data collection time to achieve time synchronization, which can avoid time misalignment leading to deviations in the calculation of scene feature indices.

[0032] Step 102: Extract features from the scene information to obtain the scene feature index of the original rendering area; In one embodiment, the scene feature index refers to a value calculated based on scene information. The scene feature index may include at least the ambient light fluctuation index and the user's perspective dynamic change index.

[0033] In one embodiment, the ambient light fluctuation index is used to indicate the degree of fluctuation in the brightness, spectrum, and polarization of scene lighting over a period of time; the larger the value of the ambient light fluctuation index, the more drastic the lighting changes, and the smaller the value of the ambient light fluctuation index, the more stable the lighting environment.

[0034] In one embodiment, the user's viewpoint dynamic change index is used to indicate the degree of drastic head rotation and spatial displacement; the larger the value of the user's viewpoint dynamic change index, the faster the user's viewpoint changes, and the smaller the value of the user's viewpoint dynamic change index, the more stable the user's line of sight.

[0035] In one embodiment, before calculating the dynamic change index of the user's viewpoint, a VR three-dimensional coordinate system is constructed with the initial position of the head-mounted display as the origin, and the index is solved based on Euler angle data in continuous time series, thereby determining the magnitude of head posture change.

[0036] Step 103: Based on the scene feature index, divide the original rendering area into at least two rendering areas, and perform corresponding rendering operations on each rendering area to obtain the rendering data corresponding to each rendering area. The rendering priorities of the at least two rendering areas are different. In one embodiment, the rendering area is a sub-region divided within the original complete VR scene based on scene feature indices, and all sub-regions are merged to cover the complete original rendering area.

[0037] In one embodiment, the rendering operation refers to a differentiated rasterization, image sampling, and texture loading process matched to different priority rendering regions, with different rendering logic executed for different priority regions.

[0038] In one embodiment, the rendering data refers to the real-time image data output after each sub-region is rendered, including information such as the resolution of different priority rendering regions, single-frame rendering time, pixel clarity, and real-time frame rate, which is used for subsequent rendering quality evaluation.

[0039] In one embodiment, rendering priority is used to differentiate the computing power allocation weights of different rendering regions. The higher the priority, the more computing power of the graphics processing unit (GPU) / central processing unit (CPU) is allocated and the higher the rendering resolution. High priority ensures the details of the picture, while low priority reduces the rendering load.

[0040] In one embodiment, frame rate, resolution, and rendering time data can be extracted synchronously after each frame is rendered, and the rendering data corresponding to each rendering region can be stored in real time; alternatively, a statistical window of 1 second can be used to aggregate all frame rendering metrics within the window, and the average rendering data of the window can be output to evaluate the rendering data corresponding to each rendering region.

[0041] Step 104: Evaluate the rendering quality of each rendering region based on the rendering data to obtain a rendering score for each rendering region; In one embodiment, the rendering score is a numerical value used to measure the smoothness and clarity of the image in a single rendering area. The lower the rendering score, the more obvious the rendering defects are, and the more necessary it is to adjust the allocation of hardware resources.

[0042] In one embodiment, the rendering quality assessment includes metrics such as frame rate stability and image clarity. Frame rate stability can be obtained by calculating the standard deviation of frame rate fluctuation per unit time; a larger standard deviation indicates more severe stuttering and frame drops. Image clarity can be obtained by the terminal image processor reading the pixel features of different priority rendering areas.

[0043] In one embodiment, a stability threshold and a sharpness threshold can be pre-configured. When either index is lower than the corresponding threshold, a low rendering score is generated for that area, and a resource scheduling trigger signal is output synchronously.

[0044] In one embodiment, differentiated evaluation thresholds can be configured for different priority rendering regions, with higher standard image quality judgment thresholds set for high-priority core gaze regions to ensure the visual experience of the center of the image for the human eye.

[0045] In one embodiment, multiple index ranges can be pre-divided, with different ranges corresponding to fixed scores. The rendering quality of each rendering region is evaluated based on the rendering data, and the rendering score of each rendering region is obtained quickly, reducing the amount of real-time calculation.

[0046] Step 105: Update the rendering strategy for the rendering region based on the rendering score.

[0047] In one embodiment, the rendering strategy may include parameters such as the CPU and GPU hardware resource allocation ratio, resolution sampling rules for each rendering region, and adaptive region division rules.

[0048] In one embodiment, if the rendering score indicates that the frame rate stability is not up to standard, the proportion of GPU resource allocation is increased to accelerate the rasterization rendering process and reduce screen stuttering; if the rendering score indicates that the image clarity is not up to standard, the GPU image processing and sampling algorithms are optimized to improve the image details in the core area.

[0049] In one embodiment, the rendering strategy is updated dynamically and in real time, without requiring the VR application to be restarted. The adjustment process is free of screen interruptions or blackouts, ensuring a continuous interactive experience.

[0050] By acquiring scene information from the original rendering area; extracting features from the scene information to obtain scene feature indices; dividing the complete VR scene into multiple priority rendering areas based on the feature indices and collecting rendering data in a differentiated manner; quantifying the rendering quality of each area based on the rendering data to obtain a rendering score; and finally dynamically updating the rendering strategy based on the score, the system can achieve real-time adaptive allocation of rendering computing power according to VR scene lighting and user head viewpoint, balancing image clarity and terminal hardware load, solving the problems of lagging resource allocation, high latency in dynamic scenes, and wasted computing power in traditional VR rendering, and improving the real-time interactive smoothness of VR devices and the user's visual immersion.

[0051] In one embodiment, obtaining scene information of the original rendering area includes: Obtain ambient lighting information and user viewpoint information for the original rendered area; In one embodiment, ambient lighting information refers to data on the ambient light level within the original VR rendering area. Ambient lighting information may include, but is not limited to, domain spectral distribution intensity of rendering areas with different priorities, the difference between the angle of light incidence and the angle of human eye line of sight, and the polarization direction of the electric field of the display device, etc., which are used to represent the real-time changes in scene lighting and shadow.

[0052] In one embodiment, user perspective information refers to data on the user's observation posture collected by the head-mounted display. User perspective information may include, but is not limited to, the three-dimensional spatial coordinates of the head-mounted display at different time points and Euler angles that characterize head posture. Euler angles include three types of parameters: pitch angle, yaw angle, and roll angle, which are used to represent the user's real-time observation position and head rotation posture.

[0053] In one embodiment, ambient lighting information can be obtained by continuously collecting data from different priority rendering areas of a lighting sensor deployed within a VR scene, generating an ambient lighting sequence based on the collection time.

[0054] In one embodiment, the user's perspective information can be obtained by sampling in real time and continuously recording spatial coordinates and Euler angles at various times through the position sensor and attitude gyroscope built into the head-mounted display.

[0055] In one embodiment, ambient lighting information and user perspective information can also be collected synchronously according to a preset fixed sampling period to ensure that the collection frequency of ambient lighting information and user perspective information is consistent and to reduce alignment calculation overhead.

[0056] In one embodiment, ambient lighting information and user viewpoint information of the original rendering area can also be collected through event triggering. For example, the collection frequency is low under normal conditions, and the collection frequency is automatically increased when a sudden change in light intensity or a large change in the user's head is detected. This can balance data collection accuracy and terminal computing power consumption.

[0057] For example, ambient lighting information includes the following data: spectral distribution intensity (relative energy values ​​of each wavelength in the 380nm-780nm visible light band), the difference between the incident angle and the eye-view angle (the difference between the incident angle of the object's light rays and the eye-view angle), and the electric field polarization direction (the direction of vibration of the electric field vector of the light wave), and is divided into segmented lighting sequences according to the scene space region. User perspective information includes the following data: three-dimensional coordinates P(t) with the initial position of the head-mounted display as the origin (x-axis horizontal to the right, y-axis vertical upward, z-axis forward), head Euler angles (pitch angle, yaw angle, roll angle) at each time point, recording the user's displacement and head turning actions in the virtual space.

[0058] The ambient lighting information and the user's viewpoint information are time-stamp aligned to obtain the scene information of the original rendering area.

[0059] In one embodiment, timestamp alignment processing refers to marking each set of ambient light sampling data and each set of user perspective sampling data with a unified time sequence number, mapping the two types of data streams asynchronously collected by different sensors to the same time axis, and eliminating data misalignment caused by the time difference of collection.

[0060] In one embodiment, the hardware sampling trigger time can be used as the reference timestamp and synchronously appended to each data point in the lighting sequence and viewpoint attitude sequence; alternatively, interpolation can be used to linearly interpolate and fill in lighting or viewpoint data that are missing the same timestamp, ensuring that each time-series node has complete lighting and viewpoint paired data.

[0061] In one embodiment, after alignment is completed, the synchronized ambient lighting data and user view data are encapsulated into a unified structured data stream, which is the scene information of the original rendering area.

[0062] For example, using time series numbers t=1,2,3…T as a unified label, the domain lighting data of different priority rendering areas at time t, the three-dimensional coordinates of the head-mounted display at time t, and the Euler angles are bound into a complete set of time series data. After merging all time series groups, synchronous scene information is generated.

[0063] This embodiment collects ambient lighting information and user view information from the original rendering area separately, and then performs timestamp alignment processing on the data from the two types of heterogeneous sensors to generate scene information with unified time sequence. This can avoid the distortion of subsequent calculation of lighting fluctuation index and dynamic change index caused by the time sequence misalignment of lighting and view data, and ensure that the judgment basis for subsequent rendering area division and resource scheduling is accurate and reliable.

[0064] In one embodiment, the scene feature index includes an ambient lighting fluctuation index and a user viewpoint change index. The step of dividing the original rendering area into at least two rendering areas based on the scene feature index includes: If the difference between the ambient light fluctuation index and the target ambient light fluctuation threshold is greater than or equal to the first adjustment threshold, the light intensity of the original rendering area is adjusted according to the target light intensity value. In one embodiment, the ambient light fluctuation index is used to represent the degree of drastic change in the light of a VR scene over a period of time. It may include, but is not limited to, the light fluctuation quantization value calculated based on continuous time-series full light data. The larger the value, the more drastic the changes in the scene's lighting, brightness, spectrum, and polarization state. The smaller the value, the more stable the lighting environment.

[0065] In one embodiment, the target ambient light fluctuation threshold is a pre-set light stability judgment benchmark value, used to distinguish between stable light scenes and scenes with severe light fluctuations.

[0066] In one embodiment, the first adjustment threshold is a preset difference threshold, used to determine whether the illumination fluctuation amplitude reaches the standard that requires global illumination correction.

[0067] In one embodiment, a difference between the ambient light fluctuation index and the target ambient light fluctuation threshold that is greater than or equal to a first adjustment threshold indicates that the scene light and shadow are shaking violently.

[0068] In one embodiment, the target light intensity value is the average value of ambient light data over a period of time, which is calculated by averaging the spectral distribution intensity, incident angle, and polarization data collected at multiple consecutive time points.

[0069] In one embodiment, the ambient light fluctuation index can be obtained by traversing all ambient light data, calculating the difference between the light data at each sampling time and the reference light data, and performing variance calculation; alternatively, a sliding window can be used to segment and statistically analyze the light change amplitude, and output the ambient light fluctuation index within the window segment by segment.

[0070] For example, using T consecutive sampling times as a sliding window, the spectral intensity, light incidence angle, and device polarization parameters of each region within the window are collected. The change amplitude of the illumination data is compared frame by frame to calculate the ambient illumination fluctuation index corresponding to the window. The difference between this index and the target ambient illumination fluctuation threshold is calculated. If the difference is greater than or equal to the first adjustment threshold, it means that the current scene illumination is fluctuating and the light and shadow are fluctuating violently, which will directly affect the visual experience of the rendering. Therefore, the average value of all illumination data within the window is taken as the target illumination intensity value, and the global illumination parameters of the entire original rendering area are uniformly corrected to eliminate the screen flickering and color distortion problems caused by violent light and shadow fluctuations.

[0071] If the difference between the ambient light fluctuation index and the target ambient light fluctuation threshold is less than the first adjustment threshold, the original rendering area is divided into at least two rendering areas based on the difference between the user viewpoint change index and the target user viewpoint change threshold.

[0072] In one embodiment, the difference between the ambient light fluctuation index and the target ambient light fluctuation threshold is less than a first adjustment threshold, indicating that the scene lighting is stable.

[0073] In one embodiment, the user's viewpoint change index is a numerical indicator used to indicate the magnitude of changes in the user's head displacement and head turning posture. It may include, but is not limited to, the quantified value of viewpoint change calculated based on the three-dimensional coordinates of the continuous time-series head-mounted display and Euler angles (pitch angle, yaw angle, roll angle). The higher the value, the faster the user turns their head and the greater the spatial displacement. The lower the value, the more stable the user's line of sight and the smaller the slight movement.

[0074] In one embodiment, the target user's perspective change threshold is a pre-set perspective stability judgment benchmark value, used to distinguish between the user's fast-moving perspective and the stationary stable perspective.

[0075] In one embodiment, the user's viewing angle change index can be obtained by weighting the displacement difference and Euler angle change of the three-dimensional coordinate P(t) of the head-mounted display at continuous time points; alternatively, the user's viewing angle change index can be obtained by calculating the variance of the angle change using only the head Euler angle time series data.

[0076] For example, once the lighting environment stabilizes, the continuous coordinates and Euler angles of the user's head-mounted display within the sliding window are read to calculate the user's field of view change index; if the index difference is small, it means that the user is staring at a fixed area of ​​the scene.

[0077] This embodiment first determines whether to uniformly correct scene lighting based on the ambient light fluctuation index. After the lighting stabilizes, it dynamically divides multiple priority rendering areas according to the user's perspective change index. It processes two types of scene variables, namely lighting disturbance and perspective dynamics, in a layered manner. This avoids the fragmentation of light and shadow layers caused by rendering different priority rendering areas directly when the lighting fluctuates drastically. At the same time, in scenes with stable lighting, it adaptively allocates rendering computing power according to the user's line of sight movement, taking into account the consistency of VR screen lighting and shadow, real-time rendering performance and human visual perception. This solves the defects of traditional fixed rendering strategies, such as wasted computing power and unbalanced image quality in dynamic scenes.

[0078] In one embodiment, the original rendering area is divided into at least two rendering areas based on the difference between the user's viewpoint change index and the target user's viewpoint change threshold, including: In response to the difference between the user's viewpoint change index and the target user's viewpoint change threshold being greater than or equal to a second adjustment threshold, a rendering operation is performed on the original rendering area. In response to the difference between the user viewpoint change index and the target user viewpoint change threshold being less than the second adjustment threshold, the original rendering area is divided into at least two rendering areas based on the user's position and user viewpoint.

[0079] In one embodiment, the second adjustment threshold is a preset difference threshold, which is used to determine whether the fluctuation amplitude of the viewpoint reaches the standard that requires uniform rendering across the entire domain.

[0080] In one embodiment, if the difference between the user viewpoint change index and the target user viewpoint change threshold is greater than or equal to a second adjustment threshold, it indicates that the user viewpoint is undergoing a significant change, and therefore it is necessary to perform rendering operations on the entire region (i.e., the original rendering region) simultaneously.

[0081] In one embodiment, if the difference between the user's viewpoint change index and the target user's viewpoint change threshold is less than the second adjustment threshold, it indicates that the user's viewpoint is relatively stable. The area within the user's viewpoint needs to be set as a high-priority core gaze area, and the high-priority core gaze area should be the focus of rendering.

[0082] In one embodiment, the user's position is the real-time spatial coordinate of the head-mounted display in the VR three-dimensional coordinate system. A three-dimensional spatial reference is established with the initial placement position of the head-mounted display as the origin of the coordinate system. The X-axis is horizontal to the right, the Y-axis is vertical to the up, and the Z-axis is the user's positive orientation.

[0083] In one embodiment, the user's perspective is the Euler angle of the head acquired by the head-mounted display sensor, which includes pitch angle, yaw angle, and roll angle, and is used to define the effective field of view.

[0084] In one embodiment, performing a rendering operation on the original rendering area means not performing spatial hierarchical processing on the original rendering area, but using the same set of resolutions and sampling rules to render the entire space of the VR scene synchronously.

[0085] For example, user head-mounted display posture data can be collected in a fixed-duration sliding window to calculate the corresponding user viewpoint change index within the window. This index is then compared with a target user viewpoint change threshold, and finally compared to a second adjustment threshold. If the difference between the user viewpoint change index and the target user viewpoint change threshold is greater than or equal to the second adjustment threshold, it is determined that the user is rapidly turning their head and significantly shifting their viewpoint. In this case, global unified rendering needs to be performed on the original rendering area. In this scenario, the user's gaze quickly sweeps across the scene without a fixed focal area. Rendering different priority rendering areas would frequently switch resolutions, causing screen flickering and visual tearing. Global unified rendering ensures a smooth, uninterrupted image. If the difference between the user viewpoint change index and the target user viewpoint change threshold is less than the second adjustment threshold, it is determined that the user's head is slightly moving and their gaze is focused on a fixed area for a long time. In this case, multi-priority rendering areas are divided based on the real-time spatial coordinates of the head-mounted display and the head's viewing direction. Different rendering rules are configured for each priority rendering area, ensuring detail in the center of the image while reducing computational consumption.

[0086] This embodiment compares the difference between the user's perspective change index and the target user's perspective change threshold, and matches corresponding rendering processing rules for two scenarios. When the user rotates the viewpoint violently, a unified global rendering is used to ensure smooth and continuous visuals. When the user's gaze is stable, computing power is allocated differently based on the user's position and perspective, dividing the rendering areas into multiple priority areas. This approach balances the integrity of the VR dynamic scene visuals with the utilization rate of terminal hardware resources, avoiding problems such as stuttering, wasted computing power, and screen flickering caused by a single fixed rendering strategy, and improving the real-time interactive experience of VR scenes.

[0087] In one embodiment, based on the user's location and viewpoint, the original rendering area is divided into at least two rendering areas, including: The circular area within the user's viewpoint, centered on the user's position and with a radius equal to a first preset threshold, is defined as the high-priority rendering area. The area outside the high-priority rendering area within the user's viewpoint, centered on the user's position and with a radius equal to the second preset threshold, is defined as the medium-priority rendering area, where the first preset threshold is less than the second preset threshold. The remaining area within the original rendering area, excluding the high-priority rendering area and the medium-priority rendering area, is defined as the low-priority rendering area.

[0088] In one embodiment, the first preset threshold and the second preset threshold are pre-configured spatial radius values, and the first preset threshold is less than the second preset threshold; the high-priority rendering area and the medium-priority rendering area are concentric ring-shaped layered structures, and all areas are superimposed to cover the complete original rendering area.

[0089] In one embodiment, the high-priority rendering area is the core gaze area, which is the central area where the user's gaze is focused and the human eye's visual discrimination ability is strongest; the medium-priority rendering area is the peripheral perception area, which is the transition area that the human eye can vaguely perceive with peripheral vision; and the low-priority rendering area is the non-attention area, which is the distant scene area with extremely low user visual attention.

[0090] In one embodiment, the first preset threshold and the second preset threshold can be uniformly configured based on the hardware parameters of the VR device and the physiological parameters of human vision; alternatively, the two spatial radius thresholds can be dynamically adjusted according to the computing power level of the terminal device. For low-end devices, the first preset threshold can be automatically reduced to compress the high-definition rendering range and further reduce computing power consumption.

[0091] For example, a first preset threshold of R1 and a second preset threshold of R2 are pre-set, satisfying R1 < R2: the circular area enclosed by a radius of R1 with the real-time acquired 3D coordinates of the head-mounted display (user position) as the center is the high-priority core gaze area. This area is the user's visual focus and is rendered using native resolution rasterization to fully preserve model textures, text, and special effects details; the annular area enclosed by a radius of R2 with the same user position as the center, minus the inner circle of R1, is the medium-priority peripheral perception area. This area is rendered using dynamic downsampling to moderately compress the pixel sampling amount and reduce the GPU computing load; in the original rendering area, excluding the circle enclosed by the radius R2, the remaining annular area is the low-priority non-concern area, which is rendered using only extremely low resolution object outlines and does not load fine texture maps.

[0092] In one embodiment, when the user makes a slight head movement, the boundaries of each level of rendering area can be updated simply by synchronously shifting the center of the rendering area (the user's position) of the different priority rendering areas. The layering rules do not need to be changed, and there will be no screen flickering problem caused by frequent resolution switching.

[0093] This embodiment divides the rendering regions into three concentric circles with the user's real-time location as the center and two preset radii, thus differentiating the spatial ranges with different levels of user visual attention. It matches corresponding rendering sampling strategies for different regions, ensuring high-definition viewing in the central area of ​​the human eye while reducing the ineffective computing power overhead in distant areas. This balances the rendering quality of VR images with the hardware load of lightweight terminal devices, effectively solving the problems of excessive GPU usage and screen stuttering caused by uniform high-resolution rendering across the entire scene.

[0094] In one embodiment, the rendering score includes a frame rate stability score and an image sharpness score, and the rendering strategy for updating the rendering region based on the rendering score includes: If the frame rate stability score is lower than the target frame rate stability threshold, and / or the image clarity score is lower than the target image clarity threshold, the rendering strategy for the rendering region is updated.

[0095] In one embodiment, the frame rate stability score is used to measure the smoothness of continuous playback of the rendered screen. The score range of the frame rate stability score can be uniformly set to 0 to 100 points. The higher the frame rate stability score, the smaller the frame rate fluctuation per unit time, and the less frame drop, stuttering, and screen delay. The lower the frame rate stability score, the greater the frame rate fluctuation, and the more obvious the screen stuttering during VR interaction.

[0096] In one embodiment, the image sharpness score is a quantitative score used to measure the ability of the rendered image to reproduce details. The score range of the image sharpness score can be uniformly set to 0 to 100 points. The higher the image sharpness score, the more complete the image texture details, the smooth edges, and the absence of blur and ghosting. The lower the image sharpness score, the more severe the loss of image details and the more excessive downsampling that causes the image to be blurry.

[0097] In one embodiment, the target frame rate stability threshold is a preset smoothness qualification benchmark score, used to determine whether the current rendering frame rate fluctuation meets the minimum smoothness requirements for user interaction; the target image clarity threshold is a preset image quality qualification benchmark score, used to determine whether the image details meet the visual perception standard.

[0098] In one embodiment, the rendering strategy refers to the rendering control parameters configured for each priority rendering region. The rendering strategy may include, but is not limited to, parameters such as the CPU and GPU hardware resource allocation ratio, the sampling downsampling ratio of each priority rendering region, the rasterization rendering resolution, and image processing optimization algorithms.

[0099] In one embodiment, the frame rate stability score can be obtained by statistically analyzing the rendering time of consecutive frames within a fixed duration, calculating the standard deviation of frame rate fluctuation, and then mapping the standard deviation to the range of 0 to 100; alternatively, the frame rate stability score can be obtained by statistically analyzing the number of dropped frames and the maximum difference between frame intervals.

[0100] In one embodiment, image detail features can be extracted using image edge detection and texture feature extraction algorithms, and the features can be quantized and mapped to a 0 to 100 range for standardization to obtain an image sharpness score; alternatively, peak signal-to-noise ratio and structural similarity index can be used to convert and obtain an image sharpness score.

[0101] In one embodiment, when the frame rate stability score is lower than the target frame rate stability threshold, or the image clarity score is lower than the target image clarity threshold, or both scores are lower than the corresponding thresholds, the rendering strategy update process is triggered to adjust the corresponding rendering resources and rendering parameters for the two types of problems: stuttering and blurring.

[0102] In one embodiment, when the frame rate stability score is lower than the target frame rate stability threshold, the rendering process is accelerated by increasing GPU resources, and the rendering strategy of the rendering area is updated, thereby reducing screen stuttering.

[0103] In one embodiment, when the image sharpness score is lower than the target image sharpness threshold, the rendering strategy of the rendering area is updated by optimizing the GPU's image processing algorithm, thereby improving the image detail performance.

[0104] For example, output screen data from each rendering region can be collected in a 1-second statistical window to calculate frame rate stability and image clarity scores. For frame rate stability, the standard deviation of frame rate fluctuation can be calculated by the rendering output interval of each frame within the statistical window. The smaller the standard deviation, the higher the score, with a maximum score of 100. The target frame rate stability threshold is preset to 70 points. If the frame rate stability score is lower than 70 points, the screen is considered to be stuttering, and the GPU resource allocation ratio needs to be increased to speed up rasterization and screen rendering operations. For image clarity, the core gaze area texture and text edge features can be extracted by the image processor to quantify the detail integrity. The target image clarity threshold is preset to 75 points. If the image clarity score is lower than 75 points, the screen details are considered to be lost, and the GPU texture sampling and image filtering algorithms need to be optimized to improve the detail restoration capability of high-priority areas.

[0105] This embodiment sets frame rate stability scores and image clarity scores, and updates the rendering strategy by combining the scores with the corresponding thresholds. It can accurately adjust hardware resources and rendering algorithms for two types of rendering defects: screen stuttering and screen blurring. This achieves simultaneous optimization of VR rendering smoothness and image quality, and continuously balances interactive smoothness and human visual clarity under limited terminal computing power.

[0106] In one embodiment, the following is a specific region rendering method provided by this disclosure, comprising: acquiring ambient lighting data in a VR scene through a light sensor, and forming an ambient lighting sequence according to region division, wherein the ambient lighting sequence is represented as: ,in Indicates the ambient lighting sequence. This indicates that the full ambient lighting data of the VR scene is obtained in the nth region.

[0107] The complete ambient lighting data includes: spectral intensity distribution under illumination, the difference between the incident angle and the viewing angle, and the electric field polarization direction of the display device. Here, n represents the total number of ambient lighting data acquisition areas in the VR scene; spectral intensity distribution describes the energy distribution of different wavelengths (colors) in light, reflecting the relative intensity of light in the visible light band (typically 380nm-780nm); and the difference between the incident angle and the viewing angle represents the direction in which light is received by the object's surface (incident angle θ).i ) and the direction of human eye observation (viewing angle θ) v The angular difference between the two points indicates that the direction of electric field polarization of the display device is the direction of vibration of the electric field vector in the light wave, which can describe the degree of polarization of the light.

[0108] like Figure 2 As shown, Figure 2 This is a schematic diagram of a spatial coordinate system in a virtual reality scene provided by an embodiment of this disclosure. The initial position of the head-mounted display is taken as the origin, the horizontal direction to the right of the origin is the x-axis, the vertical direction upwards from the origin is the y-axis, and the forward direction of the user's orientation from the origin is the z-axis. A three-dimensional coordinate system based on the VR scene is established. The position of the user's viewpoint at different time points is obtained by the position change of the head-mounted display, and is represented as follows: ,like Figure 2 As shown, This represents the user's viewpoint coordinates on the x-axis. This represents the user's viewpoint coordinates on the y-axis. This represents the user's viewpoint coordinates on the z-axis; The Euler angles of the user's viewpoint at different times are obtained through sensors built into the head-mounted display (e.g., ...). Figure 3 , Figure 4 As shown, Figure 3 This is a schematic diagram of Euler angles from a user's perspective at a first time point, provided as an embodiment of the present disclosure. Figure 4 (A schematic diagram of Euler angles from a user's perspective at a second time point provided in an embodiment of this disclosure), shown as... ,in Euler angles represent the user's perspective at different points in time. Euler angles include pitch, yaw, and roll, denoted by _____. , and express; Based on the analysis of the full ambient light data, the ambient light fluctuation index is expressed mathematically as follows:

[0109] in The ambient light fluctuation index is represented by t = 1, 2, 3, ..., T, where t represents the time series number and T represents the total number of data collection points in the time series. The ambient light fluctuation index is used to adjust the light intensity of the VR scene based on the difference between the ambient light fluctuation index and a preset light analysis threshold. When the difference between the ambient light fluctuation index and the preset light analysis threshold is greater than or equal to the preset adjustment threshold, the light intensity of the VR scene is adjusted, and the mean of the entire ambient light data series is used as the adjustment value. When the difference between the ambient light fluctuation index and the preset light analysis threshold is less than the preset adjustment threshold, no light intensity adjustment is performed on the VR scene. Based on Euler angle analysis of the user's perspective at different points in time, the dynamic change index of the user's perspective is expressed mathematically as follows:

[0110] in, The index represents the dynamic change from the user's perspective, t=1, 2, 3, ..., T, where t represents the time series number and T represents the total number of data collection points in the time series.

[0111] When the difference between the ambient light fluctuation index and the preset lighting analysis threshold is less than the preset adjustment threshold, a rendering resource allocation command is automatically sent. The purpose of the ambient light fluctuation index is to determine whether the lighting environment is stable. When the difference between the ambient light fluctuation index and the preset lighting analysis threshold is less than the preset adjustment threshold, it indicates that the lighting environment is relatively stable. At this time, a rendering command is sent under stable lighting conditions. The rendering priority of the user's perspective is adjusted based on the difference between the dynamic change index of the user's perspective and the preset perspective analysis threshold. When the difference between the dynamic viewpoint change index and the preset viewpoint analysis threshold is greater than or equal to the preset adjustment threshold, it indicates that the user's viewpoint is changing significantly, and the priority rendering unit performs rendering operations on the entire area simultaneously. Conversely, when the difference between the dynamic change index of the viewpoint and the preset viewpoint analysis threshold is less than the preset adjustment threshold, it indicates that the user's viewpoint is relatively stable, and the priority rendering unit sets the area within the user's viewpoint as the high-priority core gaze area.

[0112] The area outside the user's field of view is set as the medium-priority peripheral perception area and the low-priority non-attention area. The high-priority core gaze area is a circular area with a radius of a preset first threshold centered on the user's current head-mounted display position coordinates. The medium-priority peripheral perception area is a circular area with a radius of a preset second threshold centered on the user's current head-mounted display position coordinates. The low-priority non-attention area is the remaining area. The 3D scene is converted into a 2D image fragment by rasterization rendering. The high-priority core gaze area is rendered at native resolution to ensure clear details. The medium-priority peripheral perception area is dynamically downsampled to reduce the computational load. The low-priority non-concern area is rendered at extremely low resolution, only the outline is rendered, and the region rendering data is collected in real time.

[0113] Based on the real-time regional rendering data collected by the rendering resource allocation module, the regional rendering quality is quantitatively evaluated. The evaluation indicators include: frame rate stability and image sharpness. Frame rate stability is obtained by calculating the standard deviation of frame rate fluctuations per unit time. Image sharpness is directly obtained through the image processor. When the frame rate stability or image sharpness is lower than the preset stability threshold or the image sharpness is lower than the preset sharpness threshold, a dynamic adjustment mechanism is triggered.

[0114] A dynamic adjustment mechanism is activated, which intelligently adjusts the resource allocation ratio between the GPU and CPU based on the degree of deviation in the evaluation results: when the frame rate stability is lower than the preset stability threshold, GPU resources are increased to accelerate the rendering process and reduce screen stuttering; when the image clarity is lower than the preset clarity threshold, the GPU's image processing algorithm is optimized to improve the image detail.

[0115] In one embodiment, such as Figure 5 As shown, Figure 5 This is a schematic diagram of a virtual reality scene provided in an embodiment of this disclosure. Figure 5 The central content pop-up (high-priority rendering area) is the user's primary focus, while the left and right side controls and bottom navigation are secondary focus areas (medium-priority rendering areas), and the distant architectural environment (low-priority rendering area) receives almost no visual attention. If a traditional, uniform global rendering strategy is adopted, the low-priority distant areas will consume the same amount of rendering power, resulting in wasted computing power; furthermore, if... Figure 6 As shown, Figure 6 This is a schematic diagram of another virtual reality scene provided by an embodiment of the present disclosure. It can be seen that the region rendering method of this application can divide different priority rendering regions based on the user's perspective and scene lighting, render the central pop-up window in high definition, downsample the side controls appropriately, render the outline of the distant environment, and at the same time evaluate the frame rate and clarity of each region in real time and dynamically update the rendering strategy.

[0116] In summary, the solution provided in this public disclosure is as follows: By acquiring scene information in real time and extracting scene feature indices, the system adaptively divides different priority rendering areas based on dynamic scene changes and performs differentiated rendering. Then, it combines the rendering data of different priority rendering areas to evaluate the rendering quality and obtain a rendering score. Finally, it updates the rendering strategy based on the score. This allows for dynamic allocation of rendering resources according to real-time scene changes, reducing unnecessary computing power consumption. At the same time, it optimizes the rendering scheme strategy in real time based on rendering quality feedback, which can improve issues such as screen stuttering and blurring, enhance overall rendering efficiency and hardware rendering resource utilization, and balance scene rendering quality with the smoothness of terminal device operation.

[0117] In one embodiment, to implement the region rendering method provided by this disclosure, this disclosure also provides a region rendering system, including: a scene data acquisition module, a feature data extraction module, a rendering resource allocation module, a rendering effect evaluation module, and a resource scheduling center module; wherein, the scene data acquisition module is used to acquire multi-source data streams in the VR scene, the multi-source data streams including ambient light changes and viewpoint dynamic information, and to form a unified data input sequence through timestamp synchronization; the feature data extraction module extracts features from the ambient light changes and viewpoint dynamic information, and analyzes the ambient light fluctuation index and the user viewpoint dynamic change index; the rendering resource allocation module generates priority rendering regions based on the ambient light fluctuation index and the user viewpoint dynamic change index combined with an adaptive rendering strategy, prioritizes the processing of core regions within the user's field of view, and collects region rendering data in real time; the rendering effect evaluation module quantitatively evaluates the region rendering quality based on the region rendering data collected in real time by the rendering resource allocation module, and the evaluation indicators include frame rate stability and image clarity; the resource scheduling center module feeds back the evaluation results to the resource scheduling center, and the resource scheduling center dynamically adjusts the resource allocation ratio of GPU and CPU according to the evaluation results, and optimizes the adaptive rendering strategy structure.

[0118] To implement the region rendering method provided in this disclosure, this disclosure also provides a region rendering apparatus, such as... Figure 7 As shown. Figure 7 This is a schematic diagram of the structure of a region rendering apparatus provided in an embodiment of the present disclosure. The region rendering apparatus 700 includes: Acquisition unit 701 is used to acquire scene information of the original rendering area; The feature extraction unit 702 is used to extract features from the scene information to obtain the scene feature index of the original rendering area; The partitioning unit 703 is used to divide the original rendering area into at least two rendering areas based on the scene feature index, and to perform a corresponding rendering operation on each rendering area to obtain rendering data corresponding to each rendering area, wherein the at least two rendering areas have different rendering priorities. Evaluation unit 704 is used to evaluate the rendering quality of each rendering region based on the rendering data, and obtain a rendering score for each rendering region; The update unit 705 is used to update the rendering strategy of the rendering region based on the rendering score.

[0119] In one embodiment, the acquisition unit 701 is specifically used for: Obtain ambient lighting information and user viewpoint information for the original rendered area; The ambient lighting information and the user's viewpoint information are time-stamp aligned to obtain the scene information of the original rendering area.

[0120] In one embodiment, the scene characteristic index includes the ambient light fluctuation index and the user's perspective change index.

[0121] In one embodiment, the dividing unit 703 is specifically used for: If the difference between the ambient light fluctuation index and the target ambient light fluctuation threshold is greater than or equal to the first adjustment threshold, the light intensity of the original rendering area is adjusted according to the target light intensity value. If the difference between the ambient light fluctuation index and the target ambient light fluctuation threshold is less than the first adjustment threshold, the original rendering area is divided into at least two rendering areas based on the difference between the user viewpoint change index and the target user viewpoint change threshold.

[0122] In one embodiment, the dividing unit 703 is specifically used for: In response to the difference between the user's viewpoint change index and the target user's viewpoint change threshold being greater than or equal to a second adjustment threshold, a rendering operation is performed on the original rendering area. In response to the difference between the user viewpoint change index and the target user viewpoint change threshold being less than the second adjustment threshold, the original rendering area is divided into at least two rendering areas based on the user's position and user viewpoint.

[0123] In one embodiment, the dividing unit 703 is specifically used for: The circular area within the user's viewpoint, centered on the user's position and with a radius equal to a first preset threshold, is defined as the high-priority rendering area. The area outside the high-priority rendering area within the user's viewpoint, centered on the user's position and with a radius equal to the second preset threshold, is defined as the medium-priority rendering area, where the first preset threshold is less than the second preset threshold. The remaining area within the original rendering area, excluding the high-priority rendering area and the medium-priority rendering area, is defined as the low-priority rendering area.

[0124] In one embodiment, the rendering score includes a frame rate stability score and an image sharpness score.

[0125] In one embodiment, the update unit 705 is specifically used for: If the frame rate stability score is lower than the target frame rate stability threshold, and / or the image clarity score is lower than the target image clarity threshold, the rendering strategy for the rendering region is updated.

[0126] It should be noted that the region rendering apparatus provided in the above embodiments is only illustrated by the division of the above program modules. In practical applications, the above processing can be assigned to different program modules as needed, that is, the internal structure of the region rendering apparatus can be divided into different program modules to complete all or part of the processing described above. In addition, the region rendering apparatus provided in the above embodiments and the region rendering method embodiments provided in this disclosure belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0127] Figure 8 This is a schematic diagram of the hardware composition structure of the electronic device provided in the embodiments of this disclosure, such as... Figure 8 As shown, the electronic device 800 includes at least one processor 802; and a memory 801 communicatively connected to the at least one processor 802; wherein the memory 801 stores instructions executable by the at least one processor 802, the instructions being executed by the at least one processor 802 to implement the steps of the region rendering method of the present disclosure embodiments.

[0128] Optionally, the electronic device may specifically be a region rendering device in the embodiments of this application, and the electronic device may implement the corresponding processes implemented by the region rendering device in the various methods of the embodiments of this application. For the sake of brevity, it will not be described in detail here.

[0129] It is understood that the electronic device also includes a communication interface 803. Various components in the electronic device are coupled together via a bus system 804. It is understood that the bus system 804 is used to implement communication between these components. In addition to a data bus, the bus system 804 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 8 The general labeled all buses as Bus System 804.

[0130] It is understood that memory 801 can be volatile memory or non-volatile memory, or both. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), ferromagnetic random access memory (FRAM), flash memory, magnetic surface memory, optical disc, or compact disc read-only memory (CD-ROM); magnetic surface memory can be disk storage or magnetic tape storage. Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), SyncLink Dynamic Random Access Memory (SLDRAM), and Direct Rambus Random Access Memory (DRRAM).The memory 801 described in the embodiments of the present invention is intended to include, but is not limited to, these and any other suitable types of memory.

[0131] The methods disclosed in the above embodiments can be applied to or implemented by processor 802. Processor 802 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above methods can be completed by integrated logic circuits in the hardware of processor 802 or by instructions in software form. Processor 802 may be a general-purpose processor, DSP, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 802 can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. A general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the methods disclosed in the embodiments of this invention can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software modules may be located in a storage medium, specifically memory 801. Processor 802 reads information from memory 801 and, in conjunction with its hardware, completes the steps of the aforementioned methods.

[0132] In an exemplary embodiment, the electronic device may be implemented by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), FPGAs, general-purpose processors, controllers, MCUs, microprocessors, or other electronic components to perform the aforementioned method.

[0133] This disclosure also provides a non-transitory computer-readable storage medium storing computer instructions, which are used to cause a computer to execute the steps of the region rendering method of the present invention.

[0134] Optionally, the computer-readable storage medium can be applied to the region rendering apparatus in the embodiments of this application, and the computer instructions cause the computer to execute the corresponding processes implemented by the region rendering apparatus in the various methods of the embodiments of this application. For the sake of brevity, these will not be described in detail here.

[0135] This disclosure also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the region rendering method provided in this embodiment of the invention.

[0136] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0137] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0138] In addition, in the various embodiments of the present invention, each functional unit can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0139] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0140] Alternatively, if the integrated units of this invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0141] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A region rendering method, characterized in that, include: Obtain scene information for the original rendering area; The scene information is used to extract features to obtain the scene feature index of the original rendering area; Based on the scene feature index, the original rendering area is divided into at least two rendering areas, and a corresponding rendering operation is performed on each rendering area to obtain the rendering data corresponding to each rendering area. The rendering priorities of the at least two rendering areas are different. The rendering quality of each rendering region is evaluated based on the rendering data to obtain a rendering score for each rendering region; The rendering strategy for the rendering region is updated based on the rendering score.

2. The method according to claim 1, characterized in that, The process of obtaining scene information of the original rendering area includes: Obtain ambient lighting information and user viewpoint information for the original rendered area; The ambient lighting information and the user's viewpoint information are time-stamp aligned to obtain the scene information of the original rendering area.

3. The method according to claim 1, characterized in that, The scene feature index includes an ambient lighting fluctuation index and a user perspective change index. Based on the scene feature index, the original rendering area is divided into at least two rendering areas, including: If the difference between the ambient light fluctuation index and the target ambient light fluctuation threshold is greater than or equal to the first adjustment threshold, the light intensity of the original rendering area is adjusted according to the target light intensity value. If the difference between the ambient light fluctuation index and the target ambient light fluctuation threshold is less than the first adjustment threshold, the original rendering area is divided into at least two rendering areas based on the difference between the user viewpoint change index and the target user viewpoint change threshold.

4. The method according to claim 3, characterized in that, The step of dividing the original rendering area into at least two rendering areas based on the difference between the user's perspective change index and the target user's perspective change threshold includes: In response to the difference between the user's viewpoint change index and the target user's viewpoint change threshold being greater than or equal to a second adjustment threshold, a rendering operation is performed on the original rendering area. In response to the difference between the user viewpoint change index and the target user viewpoint change threshold being less than the second adjustment threshold, the original rendering area is divided into at least two rendering areas based on the user's position and user viewpoint.

5. The method according to claim 4, characterized in that, The process of dividing the original rendering area into at least two rendering areas based on the user's location and perspective includes: The circular area within the user's viewpoint, centered on the user's position and with a radius equal to a first preset threshold, is defined as the high-priority rendering area. The area outside the high-priority rendering area within the user's viewpoint, centered on the user's position and with a radius equal to the second preset threshold, is defined as the medium-priority rendering area, where the first preset threshold is less than the second preset threshold. The remaining area within the original rendering area, excluding the high-priority rendering area and the medium-priority rendering area, is defined as the low-priority rendering area.

6. The method according to claim 1, characterized in that, The rendering score includes a frame rate stability score and an image sharpness score. The rendering strategy for updating the rendering region based on the rendering score includes: If the frame rate stability score is lower than the target frame rate stability threshold, and / or the image clarity score is lower than the target image clarity threshold, the rendering strategy for the rendering region is updated.

7. A region rendering apparatus, characterized in that, include: The acquisition unit is used to acquire scene information of the original rendering area; The feature extraction unit is used to extract features from the scene information to obtain the scene feature index of the original rendering area; A partitioning unit is used to divide the original rendering region into at least two rendering regions based on the scene feature index, and to perform a corresponding rendering operation on each rendering region to obtain rendering data corresponding to each rendering region, wherein the at least two rendering regions have different rendering priorities. An evaluation unit is used to evaluate the rendering quality of each rendering region based on the rendering data, and obtain a rendering score for each rendering region. An update unit is used to update the rendering strategy of the rendering region based on the rendering score.

8. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1 to 6.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 6.

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