Urban three-dimensional visual interaction method and system based on virtual reality

Abstract

The invention discloses an urban three-dimensional visualization interaction method and system based on virtual reality, and relates to the technical field of urban three-dimensional visualization data processing. The method comprises the following steps: dividing a city three-dimensional model into a plurality of sub-regions, preprocessing virtual reality three-dimensional hardware load related data and virtual reality three-dimensional software load related data, comprehensively evaluating a hardware load evaluation coefficient and a software load evaluation coefficient to obtain a rendering load evaluation coefficient, and evaluating the rendering load evaluation coefficient according to the rendering load evaluation coefficient. And executing a balanced rendering quality optimization scheme for real-time rendering of the sub-region according to a threshold comparison result of the rendering load evaluation coefficient. According to the method and the device, the balance rendering quality optimization scheme is executed on the real-time rendering of the sub-region according to the threshold comparison result of the rendering load evaluation coefficient, so that the effects of accelerating the real-time rendering speed and improving the frame rate are achieved; the problem that the virtual reality three-dimensional real-time rendering precision is insufficient during virtual reality three-dimensional visualization complex interaction in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of urban three-dimensional visualization data processing, and particularly to a method and system for urban three-dimensional visualization interaction based on virtual reality. Background Art

[0002] The complexity of modern urban planning and management is increasing day by day. Traditional two-dimensional floor plans and static models can no longer meet people's needs for intuitive, dynamic, and multi-dimensional information display. With the continuous maturity of virtual reality technology, by constructing a highly realistic three-dimensional virtual urban environment, users can freely roam, explore, and perform various interactive operations in it, such as modifying building designs, simulating traffic flows, etc., thus providing a brand-new and efficient tool and method for fields such as urban planning, design, and management.

[0003] Existing visualization interaction systems are realized through three-dimensional modeling technology, real-time visualization technology, and multi-source data collection and integration technology.

[0004] Three-dimensional modeling technology: Obtain the three-dimensional coordinates and texture information of objects in the real world through technologies such as laser scanning and photogrammetry, and establish a realistic three-dimensional model.

[0005] Real-time visualization technology: Integrate the established three-dimensional model with traffic data, etc., and use a graphics rendering engine and virtual reality technology to achieve a realistic visualization effect.

[0006] Multi-source data collection and integration: Collect data from various data sources such as traffic sensors, cameras, GPS devices, and mobile terminals, and perform integration and cleaning to form a unified data format and standard.

[0007] For example, a method for three-dimensional visualization of urban buildings disclosed in the invention patent with the publication number of CN113963113A includes: constructing a three-dimensional model of urban buildings; dividing the three-dimensional model, dividing the three-dimensional model of urban buildings, and classifying and dividing it into spatial models in different regions; performing overall visualization and regional visualization on the three-dimensional visualization of urban buildings, realizing data reading, and performing color rendering or texture mapping; integrating the spatial models after color rendering or texture mapping to form a complete three-dimensional visualization model of urban buildings.

[0008] For example, a method for efficient modeling and visualization of urban-level scenes based on NeRF disclosed in the invention patent with the publication number of CN118485784A includes: partitioning training data, and further includes the following steps: parallel training of sub-regions; generating a sparse octree and storing the node weight data of each node; performing interactive rendering.

[0009] However, in the process of implementing the technical solutions of the present invention in the embodiments of the present application, it is found that the above technologies have at least the following technical problems:

[0010] In the prior art, in the three-dimensional visual interaction of the urban scene, when the user interacts with the urban three-dimensional model, for example, day-night switching, detail magnification, and weather change, the buildings and plots in the urban three-dimensional model need to present more refined details in real time, and there is a problem of insufficient accuracy in real-time rendering of virtual reality three-dimension in complex virtual reality three-dimensional visual interactions. Summary of the Invention

[0011] By providing a method and system for three-dimensional visual interaction of a city based on virtual reality, the embodiments of the present application solve the problem of insufficient accuracy in real-time rendering of virtual reality three-dimension in complex virtual reality three-dimensional visual interactions in the prior art, and achieve the effects of accelerating the real-time rendering speed and increasing the frame rate.

[0012] The embodiments of the present application provide a method for three-dimensional visual interaction of a city based on virtual reality, including the following steps: dividing the urban three-dimensional model into multiple sub-regions, the user selects a sub-region, performs visual interaction on the model in the sub-region, and during the user's visual interaction process, the virtual reality computer performs real-time rendering on the sub-region and collects data related to virtual reality three-dimensional hardware load and data related to virtual reality three-dimensional software load; preprocessing the data related to virtual reality three-dimensional hardware load and the data related to virtual reality three-dimensional software load to obtain preprocessed data of virtual reality three-dimensional hardware load and preprocessed data of virtual reality three-dimensional software load; analyzing the preprocessed data of virtual reality three-dimensional hardware load to obtain a hardware load evaluation coefficient, analyzing the preprocessed data of virtual reality three-dimensional software load to obtain a software load evaluation coefficient, and comprehensively evaluating the hardware load evaluation coefficient and the software load evaluation coefficient to obtain a rendering load evaluation coefficient; comparing the hardware load evaluation coefficient, the software load evaluation coefficient, and the rendering load evaluation coefficient with the hardware load evaluation threshold, the software load evaluation threshold, and the rendering load evaluation threshold respectively for threshold comparison, and according to the threshold comparison result of the hardware load evaluation coefficient, executing a hardware load optimization scheme for the real-time rendering of the sub-region. If the hardware load evaluation coefficient is still greater than or equal to the hardware load evaluation threshold, executing a software load optimization scheme for the real-time rendering of the sub-region. According to the threshold comparison result of the software load evaluation coefficient, executing a rendering load optimization scheme for the real-time rendering of the sub-region. According to the threshold comparison result of the rendering load evaluation coefficient, executing a balanced rendering quality optimization scheme for the real-time rendering of the sub-region.

[0013] Further, the specific interaction process of performing visual interaction on the model in the sub-region is: obtaining the model in the sub-region through laser scanning, importing the model in the sub-region into the VR development engine, adding visual cues in the VR environment, and performing visual interaction on the model in the sub-region through handle buttons, gestures, and voice input. The visual interaction includes dragging and scaling, rotating to observe the internal structure, triggering an animation demonstration, day-night switching, and weather adjustment.

[0014] Further, the specific process of collecting data related to the virtual reality three-dimensional hardware load and data related to the virtual reality three-dimensional software load is as follows: Collect data related to the virtual reality three-dimensional hardware load and data related to the virtual reality three-dimensional software load through the built-in tools of the operating system and by using Unity's Profiler; The data related to the virtual reality three-dimensional hardware load includes the CPU core utilization rate of the VR computer, the GPU utilization rate of the VR computer, the percentage of video memory occupancy of the VR computer, and the multi-threaded scheduling efficiency of the VR computer; The data related to the virtual reality three-dimensional software load includes the number of polygons in the urban three-dimensional scene during each frame rendering, the number of dynamic objects in the urban three-dimensional scene during each frame rendering, the interaction latency from input to frame update during each frame rendering, and the data stream bandwidth during each frame rendering.

[0015] Further, the specific process of preprocessing the data related to the virtual reality three-dimensional hardware load and the data related to the virtual reality three-dimensional software load is as follows: Correlate the data related to the virtual reality three-dimensional hardware load and the data related to the virtual reality three-dimensional software load through timestamps, use the linear interpolation method to fill in the short-term missing data in the data related to the virtual reality three-dimensional hardware load and the data related to the virtual reality three-dimensional software load, perform time interval detection on the data related to the virtual reality three-dimensional hardware load and the data related to the virtual reality three-dimensional software load, mark and delete the long-term missing data, use a low-pass filter to smooth the data related to the virtual reality three-dimensional hardware load and the data related to the virtual reality three-dimensional software load, and use the Z-score normalization method to normalize the data related to the virtual reality three-dimensional hardware load and the data related to the virtual reality three-dimensional software load.

[0016] Further, the specific analysis process of analyzing the preprocessed data of the virtual reality three-dimensional hardware load is as follows: Obtain the weight factors of the CPU core utilization rate of the VR computer, the GPU utilization rate of the VR computer, the percentage of video memory occupancy of the VR computer, and the multi-threaded scheduling efficiency of the VR computer from the database, arrange the CPU core utilization rate of the VR computer, the GPU utilization rate of the VR computer, the percentage of video memory occupancy of the VR computer, and the multi-threaded scheduling efficiency of the VR computer in a time series, assign weights to the CPU core utilization rate of the VR computer, the GPU utilization rate of the VR computer, the percentage of video memory occupancy of the VR computer, and the multi-threaded scheduling efficiency of the VR computer, compare the standard values of the CPU core utilization rate of the VR computer, the GPU utilization rate of the VR computer, the percentage of video memory occupancy of the VR computer, and the multi-threaded scheduling efficiency of the VR computer with the average values of the CPU core utilization rate of the VR computer, the GPU utilization rate of the VR computer, the percentage of video memory occupancy of the VR computer, and the multi-threaded scheduling efficiency of the VR computer, and process to obtain the hardware load evaluation coefficient.

[0017] Furthermore, the specific analysis process for analyzing the preprocessed data of virtual reality 3D software load is as follows: Obtain from the database the weight factors of the number of polygons in the urban 3D during each frame rendering, the weight factors of the number of dynamic objects in the urban 3D during each frame rendering, the weight factors of the interaction delay from input to frame update during each frame rendering, and the weight factors of the data stream bandwidth during each frame rendering. Arrange the number of polygons in the urban 3D during each frame rendering, the number of dynamic objects in the urban 3D during each frame rendering, the interaction delay from input to frame update during each frame rendering, and the data stream bandwidth during each frame rendering in a frame sequence. Assign weights to the number of polygons in the urban 3D during each frame rendering, the number of dynamic objects in the urban 3D during each frame rendering, the interaction delay from input to frame update during each frame rendering, and the data stream bandwidth during each frame rendering. Compare the standard values of the number of polygons in the urban 3D during each frame rendering, the number of dynamic objects in the urban 3D during each frame rendering, the interaction delay from input to frame update during each frame rendering, and the data stream bandwidth during each frame rendering with the average values of the number of polygons in the urban 3D during each frame rendering, the number of dynamic objects in the urban 3D during each frame rendering, the interaction delay from input to frame update during each frame rendering, and the data stream bandwidth during each frame rendering, and process to obtain the software load evaluation coefficient.

[0018] Furthermore, the specific analysis process for comprehensively evaluating the hardware load evaluation coefficient and the software load evaluation coefficient is as follows: Obtain from the database the weight factors of the hardware load evaluation coefficient and the weight factors of the software load evaluation coefficient. Assign weights to the hardware load evaluation coefficient and the software load evaluation coefficient. Combine the hardware load evaluation coefficient and the software load evaluation coefficient, and process to obtain the rendering load evaluation coefficient.

[0019] Further, the specific threshold comparison method for comparing the hardware load evaluation coefficient, software load evaluation coefficient, and rendering load evaluation coefficient with the hardware load evaluation threshold, software load evaluation threshold, and rendering load evaluation threshold respectively is as follows: Compare the hardware load evaluation coefficient with the hardware load evaluation threshold. If the hardware load evaluation coefficient is less than the hardware load evaluation threshold, directly perform real-time rendering on the sub-region. If the hardware load evaluation coefficient is greater than or equal to the hardware load evaluation threshold, execute the hardware load optimization plan for the real-time rendering of the sub-region. After executing the hardware load optimization plan, continue to compare the hardware load evaluation coefficient with the hardware load evaluation threshold. If the hardware load evaluation coefficient is still greater than or equal to the hardware load evaluation threshold, execute the software load optimization plan for the real-time rendering of the sub-region, and compare the software load evaluation coefficient with the software load evaluation threshold. If the software load evaluation coefficient is less than the software load evaluation threshold, perform real-time rendering on the sub-region. If the software load evaluation coefficient is greater than or equal to the software load evaluation threshold, execute the rendering load optimization plan for the real-time rendering of the sub-region, and compare the rendering load evaluation coefficient with the rendering load evaluation threshold. If the rendering load evaluation coefficient is less than the rendering load evaluation threshold, perform real-time rendering on the sub-region. If the rendering load evaluation coefficient is greater than or equal to the rendering load evaluation threshold, execute the balanced rendering quality optimization plan for the real-time rendering of the sub-region; The hardware load optimization plan includes dynamic resolution adjustment; The software load optimization plan includes interactive event priority scheduling and multi-thread parallel processing; The rendering load optimization plan includes frustum-based GPU culling technology.

[0020] Further, the specific process of the balanced rendering quality optimization plan is as follows: If, after executing the hardware load optimization plan, software load optimization plan, and rendering load optimization plan, the rendering load evaluation coefficient is still greater than or equal to the rendering load evaluation threshold, execute the balanced rendering quality optimization plan for the real-time rendering of the sub-region, including performing polygon merging on the real-time rendering of the sub-region, reducing the number of polygons and not rendering the polygons facing away from the camera. If the rendering load evaluation coefficient is less than the rendering load evaluation threshold, do not perform the balanced rendering quality optimization plan.

[0021] The embodiment of the present application provides a virtual reality-based urban three-dimensional visualization interaction system, which includes an interaction and data collection module, a data preprocessing module, a data analysis module, and an optimization module: Interaction and data collection module: used to divide the urban three-dimensional model into multiple sub-regions, the user selects a sub-region, performs visual interaction on the model in the sub-region, and during the user's visual interaction process, the virtual reality computer performs real-time rendering on the sub-region and collects data related to the virtual reality three-dimensional hardware load and data related to the virtual reality three-dimensional software load; Data preprocessing module: used to preprocess the data related to the virtual reality three-dimensional hardware load and the data related to the virtual reality three-dimensional software load to obtain preprocessed data of the virtual reality three-dimensional hardware load and preprocessed data of the virtual reality three-dimensional software load; Data analysis module: used to analyze the preprocessed data of the virtual reality three-dimensional hardware load to obtain a hardware load evaluation coefficient, analyze the preprocessed data of the virtual reality three-dimensional software load to obtain a software load evaluation coefficient, and comprehensively evaluate the hardware load evaluation coefficient and the software load evaluation coefficient to obtain a rendering load evaluation coefficient; Optimization module: used to compare the hardware load evaluation coefficient, the software load evaluation coefficient, and the rendering load evaluation coefficient with the hardware load evaluation threshold, the software load evaluation threshold, and the rendering load evaluation threshold respectively. According to the threshold comparison result of the hardware load evaluation coefficient, execute a hardware load optimization plan for the real-time rendering of the sub-region. If the hardware load evaluation coefficient is still greater than or equal to the hardware load evaluation threshold, execute a software load optimization plan for the real-time rendering of the sub-region. According to the threshold comparison result of the software load evaluation coefficient, execute a rendering load optimization plan for the real-time rendering of the sub-region. According to the threshold comparison result of the rendering load evaluation coefficient, execute a balanced rendering quality optimization plan for the real-time rendering of the sub-region.

[0022] One or more technical solutions provided in the embodiment of the present application have at least the following technical effects or advantages:

[0023] 1. By executing a balanced rendering quality optimization plan for the real-time rendering of the sub-region according to the threshold comparison result of the rendering load evaluation coefficient, the effects of accelerating the real-time rendering speed and increasing the frame rate are achieved, effectively solving the problem of insufficient accuracy of virtual reality three-dimensional real-time rendering during complex interactions in virtual reality three-dimensional visualization in the prior art.

[0024] 2. By dividing the urban three-dimensional model into multiple sub-regions and the user selects a sub-region, thereby performing visual interaction on the model in the sub-region, the effect of improving the visual interaction efficiency is achieved, effectively solving the problem of insufficient visual interaction efficiency in the prior art.

[0025] 3. By preprocessing the data related to the virtual reality three-dimensional hardware load and the data related to the virtual reality three-dimensional software load, the preprocessed data of the virtual reality three-dimensional hardware load and the preprocessed data of the virtual reality three-dimensional software load are obtained, thereby achieving the effect of improving the data quality and effectively solving the problem of insufficient data quality in the prior art. Description of the Drawings

[0026] Figure 1 Flowchart of the method for urban three-dimensional visualization interaction based on virtual reality provided by the embodiment of the present application;

[0027] Figure 2 Schematic diagram of the hardware load evaluation coefficient of the method for urban three-dimensional visualization interaction based on virtual reality provided by the embodiment of the present application;

[0028] Figure 3 Schematic diagram of the structure of the urban three-dimensional visualization interaction system based on virtual reality provided by the embodiment of the present application. Detailed Embodiments

[0029] The embodiment of the present application provides a method and a system for urban three-dimensional visualization interaction based on virtual reality, which solve the problem of insufficient accuracy of real-time rendering of virtual reality three-dimensional in complex virtual reality three-dimensional visualization interactions in the prior art. By comparing the threshold of the rendering load evaluation coefficient, a balanced rendering quality optimization scheme is executed for the real-time rendering of sub-regions, thereby achieving the effects of accelerating the real-time rendering speed and increasing the frame rate.

[0030] The technical solution in the embodiment of the present application for solving the problem of insufficient accuracy of real-time rendering of virtual reality three-dimensional in complex virtual reality three-dimensional visualization interactions is as follows:

[0031] By dividing the urban three-dimensional model into multiple sub-regions, collecting the data related to the virtual reality three-dimensional hardware load and the data related to the virtual reality three-dimensional software load during the visualization interaction process, analyzing the preprocessed data of the virtual reality three-dimensional hardware load to obtain the hardware load evaluation coefficient, analyzing the preprocessed data of the virtual reality three-dimensional software load to obtain the software load evaluation coefficient, and comprehensively evaluating the hardware load evaluation coefficient and the software load evaluation coefficient to obtain the rendering load evaluation coefficient, the effects of accelerating the real-time rendering speed and increasing the frame rate are achieved.

[0032] To better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the drawings in the specification and specific embodiments.

[0033] As Figure 1As shown in the figure, it is a flowchart of a virtual reality-based urban three-dimensional visualization interaction method provided by an embodiment of the present application. This method is applied to a virtual reality-based urban three-dimensional visualization interaction system, and the method includes the following steps: Divide the urban three-dimensional model into multiple sub-regions, the user selects a sub-region, and performs visual interaction on the model in the sub-region. During the visual interaction process of the user, the virtual reality computer performs real-time rendering on the sub-region and collects data related to virtual reality three-dimensional hardware load and data related to virtual reality three-dimensional software load; preprocess the data related to virtual reality three-dimensional hardware load and data related to virtual reality three-dimensional software load to obtain preprocessed data of virtual reality three-dimensional hardware load and preprocessed data of virtual reality three-dimensional software load; analyze the preprocessed data of virtual reality three-dimensional hardware load to obtain a hardware load evaluation coefficient, analyze the preprocessed data of virtual reality three-dimensional software load to obtain a software load evaluation coefficient, and comprehensively evaluate the hardware load evaluation coefficient and the software load evaluation coefficient to obtain a rendering load evaluation coefficient; compare the hardware load evaluation coefficient, the software load evaluation coefficient, and the rendering load evaluation coefficient with the hardware load evaluation threshold, the software load evaluation threshold, and the rendering load evaluation threshold respectively for threshold comparison. According to the threshold comparison result of the hardware load evaluation coefficient, execute a hardware load optimization plan for the real-time rendering of the sub-region. If the hardware load evaluation coefficient is still greater than or equal to the hardware load evaluation threshold, execute a software load optimization plan for the real-time rendering of the sub-region. According to the threshold comparison result of the software load evaluation coefficient, execute a rendering load optimization plan for the real-time rendering of the sub-region. According to the threshold comparison result of the rendering load evaluation coefficient, execute a balanced rendering quality optimization plan for the real-time rendering of the sub-region.

[0034] Further, the specific interaction process of performing visual interaction on the model in the sub-region is as follows: Obtain the model in the sub-region through laser scanning, import the model in the sub-region into the VR development engine, add visual cues in the VR environment, and perform visual interaction on the model in the sub-region through handle buttons, gestures, and voice input. The visual interaction includes dragging and scaling, rotating to observe the internal structure, triggering animation demonstrations, day-night switching, and weather adjustment.

[0035] In this embodiment, laser scanning technology is used to scan an existing urban park to obtain accurate three-dimensional data of a specific building in the park, such as a pavilion. The three-dimensional model of the scanned building is imported into a VR development engine, such as Unity or Unreal Engine. In the VR environment, visual cues are added to the building, such as highlighting the area to be renovated or marking different functional areas with different colors. Users can use the buttons on the VR controller to drag and scale the building model to observe the model from different angles and distances. Users can use gesture control, such as making a fist and spreading the palm, to rotate the building model to observe its internal structure. When the user wants to view the renovated effect, an animation can be triggered by a specific controller button, such as simulating the opening of the pavilion roof or the dynamic effect of a sculpture. Users can input commands by voice, such as "switch to night", to observe the visual effect of the building under different lighting conditions. Similarly, users can adjust the weather in the VR environment by voice commands, such as simulating rain or sunny days, to evaluate the impact of weather on the park usage experience.

[0036] Further, the specific process of collecting data related to the virtual reality three-dimensional hardware load and data related to the virtual reality three-dimensional software load is as follows: Data related to the virtual reality three-dimensional hardware load and data related to the virtual reality three-dimensional software load are collected through the built-in tools of the operating system and the Profiler of Unity; Data related to the virtual reality three-dimensional hardware load includes the CPU core utilization rate of the VR computer, the GPU utilization rate of the VR computer, the percentage of video memory occupancy of the VR computer, and the multi-threaded scheduling efficiency of the VR computer; Data related to the virtual reality three-dimensional software load includes the number of polygons in the urban three-dimensional model during each frame rendering, the number of dynamic objects in the urban three-dimensional model during each frame rendering, the interaction delay from input to frame update during each frame rendering, and the data stream bandwidth during each frame rendering.

[0037] In this embodiment, the CPU core utilization rate of the VR computer, the GPU utilization rate of the VR computer, the percentage of video memory occupancy, the multi-threaded scheduling efficiency, as well as the number of polygons in the urban three-dimensional model, the number of dynamic objects, the interaction delay from input to frame update, and the data stream bandwidth during each frame rendering can be obtained through real-time monitoring and performance analysis tools. These tools include the task manager and performance monitor built into the operating system, as well as the performance analyzers provided by professional VR development engines (such as Unity or Unreal Engine).

[0038] The CPU core utilization rate of a VR computer refers to the degree of usage of each core of the computer's central processing unit (CPU) when a virtual reality application is running, usually expressed as a percentage. It can be obtained through the task manager built into the operating system (such as the Task Manager in Windows or the Activity Monitor in macOS) or third-party performance monitoring tools (such as CPU-Z, HWMonitor).

[0039] The GPU utilization rate of a VR computer refers to the degree of busyness of the graphics processing unit (GPU) when performing graphics rendering and other computing tasks, expressed as a percentage. Tools provided by GPU manufacturers can be used (such as the performance monitors in NVIDIA's GPU Control Panel and GeForce Experience, or the performance monitors in AMD's Radeon Settings) to monitor the GPU utilization rate.

[0040] The percentage of VRAM occupied by a VR computer refers to the degree to which the VRAM (video memory) of the GPU is used by the currently running application, also expressed as a percentage. The usage of VRAM can be viewed through tools provided by GPU manufacturers or third-party monitoring software.

[0041] The multi-threaded scheduling efficiency of a VR computer refers to the ability of the operating system to effectively allocate and schedule multiple threads to run on multiple CPU cores. Usually, professional performance analysis tools (such as Intel VTune Amplifier, AMD uProf) are required to evaluate it.

[0042] The number of polygons in the 3D city during each frame rendering refers to the total number of polygons (usually triangles) contained in the 3D city model during each frame rendering process. It can be obtained through the statistical functions provided by 3D engines or rendering APIs (such as OpenGL, DirectX).

[0043] The number of dynamic objects in the 3D city during each frame rendering refers to the number of objects that change dynamically in the 3D city scene in each frame, such as moving vehicles, pedestrians, or other animated elements. The dynamic objects can be counted programmatically in the rendering loop.

[0044] The interaction delay from input to frame update during each frame rendering refers to the time delay from user input (such as mouse clicks, keyboard key presses, or VR controller actions) to the corresponding frame update being displayed on the screen. The time difference between input and rendering update can be measured through high-performance timing tools (such as QueryPerformanceCounter in Windows).

[0045] The data stream bandwidth in each frame rendering refers to the data transfer from memory to the GPU video memory during each frame rendering process. GPU performance analysis tools can be used to monitor the data transfer bandwidth.

[0046] Furthermore, the specific process of preprocessing the data related to virtual reality three-dimensional hardware load and the data related to virtual reality three-dimensional software load is as follows: associate the data related to virtual reality three-dimensional hardware load and the data related to virtual reality three-dimensional software load through timestamps, use the linear interpolation method to complete the short-term missing data in the data related to virtual reality three-dimensional hardware load and the data related to virtual reality three-dimensional software load, detect the time intervals of the data related to virtual reality three-dimensional hardware load and the data related to virtual reality three-dimensional software load, mark and delete the long-term missing data, use a low-pass filter to smooth the data related to virtual reality three-dimensional hardware load and the data related to virtual reality three-dimensional software load, and use the Z-score normalization method to normalize the data related to virtual reality three-dimensional hardware load and the data related to virtual reality three-dimensional software load.

[0047] In this embodiment, for example, at a specific time point t1, the CPU core utilization rate is 60%, and at the same time, the number of polygons in the city three-dimensional model during each frame rendering is 1000. If it is found that the CPU core utilization rate data at time point t2 is missing. Using the linear interpolation method, based on the CPU core utilization rate data at time points t1 and t3 (assuming 60% and 70% respectively), estimate the CPU core utilization rate at time point t2. If it is found that the GPU utilization rate data is completely missing from time point t4 to t6, it is determined that the missing data at this time is long-term missing. Mark this time period and exclude it from the analysis to avoid interfering with the overall performance evaluation. To reduce the noise in the data, use a low-pass filter to smooth the CPU and GPU utilization rate data to obtain a more stable data curve for easy analysis. For example, if the average value of the video memory occupancy is 50% and the standard deviation is 10%, then the data point with a video memory occupancy of 60% at time point t7 will be converted to a Z-score of 1, indicating that it is 1 standard deviation higher than the average value.

[0048] Further, the specific analysis process of preprocessing data on the hardware load of virtual reality three - dimension is as follows: Obtain the weight factors of the CPU core utilization rate of the VR computer, the weight factor of the GPU utilization rate of the VR computer, the weight factor of the video memory occupancy percentage of the VR computer, and the weight factor of the multi - thread scheduling efficiency of the VR computer from the database. Arrange the CPU core utilization rate of the VR computer, the GPU utilization rate of the VR computer, the video memory occupancy percentage of the VR computer, and the multi - thread scheduling efficiency of the VR computer in a time series. Assign weights to the CPU core utilization rate of the VR computer, the GPU utilization rate of the VR computer, the video memory occupancy percentage of the VR computer, and the multi - thread scheduling efficiency of the VR computer. Compare the standard values of the CPU core utilization rate of the VR computer, the GPU utilization rate of the VR computer, the video memory occupancy percentage of the VR computer, and the multi - thread scheduling efficiency of the VR computer with the average values of the CPU core utilization rate of the VR computer, the GPU utilization rate of the VR computer, the video memory occupancy percentage of the VR computer, and the multi - thread scheduling efficiency of the VR computer, and process to obtain the hardware load evaluation coefficient.

[0049] In this embodiment, the specific method for obtaining the hardware load evaluation coefficient is as follows:

[0050]

[0051] In the formula, HLA represents the hardware load evaluation coefficient, which is used to evaluate the hardware load during rendering. Set several time monitoring points, S0 = 1, 2, 3,..., a, where a represents the total number of time monitoring points. represents the CPU core utilization rate of the VR computer at the S0 - th time monitoring point, CPU_CU0 represents the CPU core utilization rate of the standard VR computer, and α represents the weight factor of the CPU core utilization rate of the VR computer. represents the GPU utilization rate of the VR computer at the S0 - th time monitoring point, β represents the weight factor of the GPU utilization rate of the VR computer, and GPU_U0 represents the GPU utilization rate of the standard VR computer. represents the video memory occupancy percentage of the VR computer at the S0 - th time monitoring point, γ represents the weight factor of the video memory occupancy percentage of the VR computer, and GPU_MUP0 represents the video memory occupancy percentage of the standard VR computer. represents the multi - thread scheduling efficiency of the VR computer at the S0 - th time monitoring point, δ represents the weight factor of the multi - thread scheduling efficiency of the VR computer, and MSE0 represents the multi - thread scheduling efficiency of the standard VR computer.

[0052] When the CPU core utilization rate of the VR computer is too high, it will cause the GPU of the VR computer to have a decreased utilization rate due to waiting for data. Efficient scheduling can evenly distribute tasks to CPU cores (such as separating the UI thread, physical thread, and rendering instruction submission thread), avoid overloading a single core, improve CPU utilization while reducing GPU waiting time. A too high percentage of video memory occupancy (such as a complex city model exceeding the video memory capacity) will trigger memory-video memory data exchange (swap), significantly increasing latency and causing the GPU utilization rate to decrease due to waiting for data.

[0053] When the system is running, obtain the mapping table of weight factors through the database, and quickly extract the corresponding weight factors according to the CPU core utilization rate of the current VR computer, the GPU utilization rate of the VR computer, the percentage of video memory occupancy of the VR computer, and the multi-threaded scheduling efficiency of the VR computer, such as the weight factor of the CPU core utilization rate of the VR computer, the weight factor of the GPU utilization rate of the VR computer, the weight factor of the percentage of video memory occupancy of the VR computer, and the weight factor of the multi-threaded scheduling efficiency of the VR computer. This mapping table defines a clear set of association rules, which converts the specific values of the CPU core utilization rate of the VR computer, the GPU utilization rate of the VR computer, the percentage of video memory occupancy of the VR computer, and the multi-threaded scheduling efficiency of the VR computer into their corresponding weight factors. Under this mechanism, whether it is to achieve an exact one-to-one match or a one-to-many relationship where multiple parameters converge into a single weight, the dynamic acquisition of weight factors can be effectively achieved.

[0054] In a specific embodiment, an example of the hardware load evaluation coefficient data is as follows in the table.

[0055] Table 1 Example Table of Hardware Load Evaluation Coefficient Data

[0056]

[0057] When the weight factors of the CPU core utilization rate of the VR computer, the GPU utilization rate of the VR computer, the percentage of video memory occupancy of the VR computer, and the multi-threaded scheduling efficiency of the VR computer are 0.2, 0.3, 0.25, and 0.25 respectively, the standard values of the CPU core utilization rate of the VR computer, the GPU utilization rate of the VR computer, the percentage of video memory occupancy of the VR computer, and the multi-threaded scheduling efficiency of the VR computer are 55%, 50%, 65%, and 80% respectively. Through Figure 2 and the data in Table 1, it can be seen that when the CPU core utilization rate of the VR computer, the GPU utilization rate of the VR computer, and the percentage of video memory occupancy of the VR computer remain fixed, the greater the multi-threaded scheduling efficiency of the VR computer, the smaller the hardware load evaluation coefficient.

[0058] Further, the specific analysis process of analyzing the preprocessed data of virtual reality three-dimensional software load is as follows: Obtain the weight factors of the number of polygons in the urban three-dimensional model during each frame rendering, the weight factors of the number of dynamic objects in the urban three-dimensional model during each frame rendering, the weight factors of the interaction delay from input to frame update during each frame rendering, and the weight factors of the data stream bandwidth during each frame rendering from the database. Arrange the number of polygons in the urban three-dimensional model during each frame rendering, the number of dynamic objects in the urban three-dimensional model during each frame rendering, the interaction delay from input to frame update during each frame rendering, and the data stream bandwidth during each frame rendering in the frame sequence. Assign weights to the number of polygons in the urban three-dimensional model during each frame rendering, the number of dynamic objects in the urban three-dimensional model during each frame rendering, the interaction delay from input to frame update during each frame rendering, and the data stream bandwidth during each frame rendering. Compare the standard values of the number of polygons in the urban three-dimensional model during each frame rendering, the number of dynamic objects in the urban three-dimensional model during each frame rendering, the interaction delay from input to frame update during each frame rendering, and the data stream bandwidth during each frame rendering with the average values of the number of polygons in the urban three-dimensional model during each frame rendering, the number of dynamic objects in the urban three-dimensional model during each frame rendering, the interaction delay from input to frame update during each frame rendering, and the data stream bandwidth during each frame rendering, and process to obtain the software load evaluation coefficient.

[0059] In this embodiment, the specific method for obtaining the software load evaluation coefficient is as follows:

[0060]

[0061] In the formula, SLA represents the software load evaluation coefficient, which is used to evaluate the software load during rendering. Set several frame monitoring points, R0 = 1, 2, 3,..., b, where b represents the total number of frame monitoring points. represents the number of polygons in the urban three-dimensional model during each frame rendering at the R0th frame monitoring point, 3D_NOP0 represents the standard number of polygons in the urban three-dimensional model during each frame rendering, and θ represents the weight factor of the number of polygons in the urban three-dimensional model during each frame rendering. represents the number of dynamic objects in the urban three-dimensional model during each frame rendering at the R0th frame monitoring point, μ represents the weight factor of the number of dynamic objects in the urban three-dimensional model during each frame rendering, and 3D_NOD0 represents the standard number of dynamic objects in the urban three-dimensional model during each frame rendering. represents the interaction delay from input to frame update during each frame rendering at the R0th frame monitoring point, ρ represents the weight factor of the interaction delay from input to frame update during each frame rendering, and 3D_FUL0 represents the standard interaction delay from input to frame update during each frame rendering. represents the data stream bandwidth during each frame rendering at the R0th frame monitoring point, σ represents the weight factor of the data stream bandwidth during each frame rendering, and DSB0 represents the standard data stream bandwidth during each frame rendering.

[0062] The number of polygons directly affects the rendering burden on the GPU. The more polygons need to be processed per frame, the greater the pressure on vertex shading, rasterization, and pixel filling of the GPU, which may lead to a decrease in the frame rate. High-precision models (with a large number of polygons) require greater storage and transmission bandwidth. If the model data needs to be dynamically loaded or streamed from the server (such as cloud rendering), high-polygon models will occupy more data stream bandwidth. Dynamic objects (such as vehicles and pedestrians) need to update their states (position, animation, physical simulation) every frame, which increases the logical computing burden on the CPU. If the CPU processing time is too long, it may delay the start time of GPU rendering, resulting in an increase in interaction latency.

[0063] When the system is running, obtain the mapping table of weight factors through the database, and quickly extract the corresponding weight factors according to the number of polygons in the urban three-dimensional model per frame during rendering, the number of dynamic objects in the urban three-dimensional model per frame during rendering, the interaction latency from input to frame update during each frame of rendering, and the data stream bandwidth during each frame of rendering. For example, the weight factor for the number of polygons in the urban three-dimensional model per frame during rendering, the weight factor for the number of dynamic objects in the urban three-dimensional model per frame during rendering, the weight factor for the interaction latency from input to frame update during each frame of rendering, and the weight factor for the data stream bandwidth during each frame of rendering. This mapping table defines a clear set of association rules, which converts the specific values of the number of polygons in the urban three-dimensional model per frame during rendering, the number of dynamic objects in the urban three-dimensional model per frame during rendering, the interaction latency from input to frame update during each frame of rendering, and the data stream bandwidth during each frame of rendering into their corresponding weight factors. Under this mechanism, whether it is to achieve an exact one-to-one match or a one-to-many relationship where multiple parameters converge into a single weight, the dynamic acquisition of weight factors can be effectively achieved.

[0064] Furthermore, the specific analysis process for comprehensively evaluating the hardware load evaluation coefficient and the software load evaluation coefficient is as follows: Obtain the weight factor of the hardware load evaluation coefficient and the weight factor of the software load evaluation coefficient from the database, assign weights to the hardware load evaluation coefficient and the software load evaluation coefficient, combine the hardware load evaluation coefficient and the software load evaluation coefficient, and process to obtain the rendering load evaluation coefficient.

[0065] In this embodiment, the specific method for obtaining the rendering load evaluation coefficient is as follows:

[0066]

[0067] In the formula, RLEF represents the rendering load evaluation coefficient, which is used to evaluate the impact of hardware load and software load on the rendering load. HLA represents the hardware load evaluation coefficient, represents the weight factor of the hardware load evaluation coefficient, SLA represents the software load evaluation coefficient, and ω represents the weight factor of the software load evaluation coefficient.

[0068] When the system is running, obtain the mapping table of weight factors through the database, and quickly extract the corresponding weight factors according to the current hardware load evaluation coefficient and software load evaluation coefficient, such as the weight factor of the hardware load evaluation coefficient and the weight factor of the software load evaluation coefficient. This mapping table defines a clear set of association rules that convert the hardware load evaluation coefficient and the software load evaluation coefficient into their corresponding weight factors. Under this mechanism, whether it is to achieve an exact one-to-one match or a one-to-many relationship where multiple parameters converge into a single weight, the dynamic acquisition of weight factors can be effectively achieved.

[0069] Furthermore, the specific threshold comparison method for comparing the hardware load evaluation coefficient, software load evaluation coefficient, and rendering load evaluation coefficient with the hardware load evaluation threshold, software load evaluation threshold, and rendering load evaluation threshold respectively is as follows: Compare the hardware load evaluation coefficient with the hardware load evaluation threshold. If the hardware load evaluation coefficient is less than the hardware load evaluation threshold, directly perform real-time rendering on the sub-region. If the hardware load evaluation coefficient is greater than or equal to the hardware load evaluation threshold, execute the hardware load optimization plan for the real-time rendering of the sub-region. After executing the hardware load optimization plan, continue to compare the hardware load evaluation coefficient with the hardware load evaluation threshold. If the hardware load evaluation coefficient is still greater than or equal to the hardware load evaluation threshold, execute the software load optimization plan for the real-time rendering of the sub-region, and compare the software load evaluation coefficient with the software load evaluation threshold. If the software load evaluation coefficient is less than the software load evaluation threshold, perform real-time rendering on the sub-region. If the software load evaluation coefficient is greater than or equal to the software load evaluation threshold, execute the rendering load optimization plan for the real-time rendering of the sub-region, and compare the rendering load evaluation coefficient with the rendering load evaluation threshold. If the rendering load evaluation coefficient is less than the rendering load evaluation threshold, perform real-time rendering on the sub-region. If the rendering load evaluation coefficient is greater than or equal to the rendering load evaluation threshold, execute the balanced rendering quality optimization plan for the real-time rendering of the sub-region; the hardware load optimization plan includes dynamic resolution adjustment; the software load optimization plan includes interactive event priority scheduling and multi-thread parallel processing; the rendering load optimization plan includes frustum-based GPU culling technology.

[0070] In this embodiment, the hardware load is evaluated to obtain a hardware load evaluation coefficient, and a hardware load evaluation threshold is obtained from the database. If the hardware load evaluation coefficient is less than the hardware load evaluation threshold, real-time rendering of the sub-region is directly performed. If the hardware load evaluation coefficient is greater than or equal to the hardware load evaluation threshold, a hardware load optimization scheme is executed for the real-time rendering of the sub-region. The computer automatically reduces the resolution according to a preset multiple. If the hardware load evaluation coefficient is still greater than or equal to the hardware load evaluation threshold at this time, the computer performs interactive event priority scheduling and multi-thread parallelization processing on the system. The software load is evaluated to obtain a software load evaluation coefficient. If the software load evaluation coefficient is less than the software load evaluation threshold, real-time rendering of the sub-region is performed. If the software load evaluation coefficient is greater than or equal to the software load evaluation threshold, the computer performs a frustum-based GPU culling technique on the system. The rendering load is evaluated to obtain a rendering load evaluation coefficient. If the rendering load evaluation coefficient is less than the rendering load evaluation threshold, real-time rendering of the sub-region is performed. If the rendering load evaluation coefficient is greater than or equal to the rendering load evaluation threshold, a balanced rendering quality optimization scheme is executed for the real-time rendering of the sub-region.

[0071] In a specific embodiment, the system loads the sub-region of the intersection (building models, vehicles, pedestrians, dynamic lights), with an initial resolution of 1080P. The hardware load optimization scheme is that the computer automatically reduces the resolution according to a preset multiple. For example, the resolution is reduced from 1080P to 720P. The software load optimization scheme is to pause non-critical background data loading tasks and allocate shadow calculations to dedicated calculation threads. The rendering load optimization scheme is to cull 30% of the building backs and underground pipe network models outside the field of view through the frustum, reducing the draw calls to 8,500 times and the number of triangles to 5.6 million.

[0072] Furthermore, the specific process of the balanced rendering quality optimization scheme is as follows: If, after executing the hardware load optimization scheme, the software load optimization scheme, and the rendering load optimization scheme, the rendering load evaluation coefficient is still greater than or equal to the rendering load evaluation threshold, a balanced rendering quality optimization scheme is executed for the real-time rendering of the sub-region, including performing polygon merging on the real-time rendering of the sub-region, reducing the number of polygons and not rendering the polygons facing away from the camera. If the rendering load evaluation coefficient is less than the rendering load evaluation threshold, the balanced rendering quality optimization scheme is no longer performed.

[0073] In this embodiment, real-time rendering is performed on the model within the sub-region. After the hardware load optimization scheme, software load optimization scheme, and rendering load optimization scheme, the rendering load evaluation coefficient is still greater than or equal to the rendering load evaluation threshold. By using the buffer method, the glass curtain wall meshes of adjacent office buildings within the sub-region are merged from 20,000 polygons to 8,000. The specific steps of the buffer method are to generate a buffer for the polygons (the buffer distance is set to 0) to replace the traditional Union operation, and merge a large number of polygons. Rendering of structures such as air conditioners and pipes on the back of the building facing away from the user's view point is stopped, reducing 1,200 invisible polygons, and immediately stop the degradation optimization, retaining the current rendering quality (the merged building model still shows a complete appearance, but the details on the back are no longer updated).

[0074] As Figure 3 shown, it is a schematic structural diagram of a virtual reality-based urban three-dimensional visualization interaction system provided by an embodiment of the present application. The virtual reality-based urban three-dimensional visualization interaction system provided by an embodiment of the present application includes: an interaction and data collection module, a data preprocessing module, a data analysis module, and an optimization module: Interaction and data collection module: used to divide the urban three-dimensional model into multiple sub-regions, the user selects a sub-region, and performs visual interaction on the model in the sub-region. During the user's visual interaction process, the virtual reality computer performs real-time rendering on the sub-region and collects virtual reality three-dimensional hardware load-related data and virtual reality three-dimensional software load-related data; Data preprocessing module: used to preprocess the virtual reality three-dimensional hardware load-related data and virtual reality three-dimensional software load-related data to obtain virtual reality three-dimensional hardware load preprocessing data and virtual reality three-dimensional software load preprocessing data; Data analysis module: used to analyze the virtual reality three-dimensional hardware load preprocessing data to obtain a hardware load evaluation coefficient, analyze the virtual reality three-dimensional software load preprocessing data to obtain a software load evaluation coefficient, and comprehensively evaluate the hardware load evaluation coefficient and the software load evaluation coefficient to obtain a rendering load evaluation coefficient; Optimization module: used to compare the hardware load evaluation coefficient, software load evaluation coefficient, and rendering load evaluation coefficient with the hardware load evaluation threshold, software load evaluation threshold, and rendering load evaluation threshold respectively. According to the threshold comparison result of the hardware load evaluation coefficient, execute the hardware load optimization scheme for the real-time rendering of the sub-region. If the hardware load evaluation coefficient is still greater than or equal to the hardware load evaluation threshold, execute the software load optimization scheme for the real-time rendering of the sub-region. According to the threshold comparison result of the software load evaluation coefficient, execute the rendering load optimization scheme for the real-time rendering of the sub-region. According to the threshold comparison result of the rendering load evaluation coefficient, execute the balanced rendering quality optimization scheme for the real-time rendering of the sub-region.

[0075] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0076] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices produce means for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or combinations of blocks.

[0077] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufactured article including instruction means that implement the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or combinations of blocks.

[0078] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are performed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or combinations of blocks.

[0079] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications once they know the basic creative concepts. Therefore, the appended claims are intended to be construed to include the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0080] Obviously, those skilled in the art can make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A three-dimensional urban visualization interactive method based on virtual reality, characterized in that: The following steps are involved: The city 3D model is divided into multiple sub-areas. The user selects a sub-area and performs visual interaction on the model in the sub-area. During the user's visual interaction, the virtual reality computer renders the sub-area in real time and collects virtual reality 3D hardware load-related data and virtual reality 3D software load-related data. Preprocessing virtual reality three-dimensional hardware load related data and virtual reality three-dimensional software load related data to obtain virtual reality three-dimensional hardware load preprocessing data and virtual reality three-dimensional software load preprocessing data; Analyze virtual reality 3D hardware load preprocessing data to obtain hardware load evaluation coefficients, analyze virtual reality 3D software load preprocessing data to obtain software load evaluation coefficients, and conduct comprehensive evaluation on the hardware load evaluation coefficients and software load evaluation coefficients to obtain rendering load evaluation coefficients; The hardware load assessment coefficient, software load assessment coefficient and rendering load assessment coefficient are respectively compared with the hardware load assessment threshold, software load assessment threshold and rendering load assessment threshold; based on the threshold comparison result of the hardware load assessment coefficient, a hardware load optimization scheme is executed for the real-time rendering of the sub-area; if the hardware load assessment coefficient is still greater than or equal to the hardware load assessment threshold, a software load optimization scheme is executed for the real-time rendering of the sub-area; based on the threshold comparison result of the software load assessment coefficient, a rendering load optimization scheme is executed for the real-time rendering of the sub-area; based on the threshold comparison result of the rendering load assessment coefficient, a balanced rendering quality optimization scheme is executed for the real-time rendering of the sub-area.

2. The method for interactive three-dimensional visualization of a city based on virtual reality according to claim 1, characterized in that: The specific interactive process of visually interacting with the models in the sub-areas is as follows: The model in the sub-area is acquired through laser scanning, imported into the VR development engine, visual cues are added in the VR environment, and the model in the sub-area is visually interacted with through handle buttons, gestures, and voice input. The visual interaction includes dragging and zooming, rotating to observe the internal structure, triggering animation demonstrations, day and night switching, and weather adjustment.

3. The method for interactive three-dimensional visualization of a city based on virtual reality according to claim 1, characterized in that: The specific process of collecting the virtual reality 3D hardware load related data and the virtual reality 3D software load related data is as follows: Collect VR 3D hardware load-related data and VR 3D software load-related data through the operating system's built-in tools and Unity's Profiler; The data related to the virtual reality 3D hardware load includes the CPU core utilization of the VR computer, the GPU utilization of the VR computer, the percentage of video memory usage of the VR computer, and the multi-threaded scheduling efficiency of the VR computer; The data related to the virtual reality 3D software load include the number of polygons in the 3D city when rendering each frame, the number of 3D dynamic objects in the city when rendering each frame, the interactive delay from input to screen update in each frame rendering, and the data stream bandwidth in each frame rendering.

4. The method for interactive three-dimensional visualization of a city based on virtual reality according to claim 1, characterized in that: The specific process of preprocessing the virtual reality 3D hardware load related data and the virtual reality 3D software load related data is as follows: The virtual reality 3D hardware load related data and the virtual reality 3D software load related data are associated through timestamps, and the short-term missing data in the virtual reality 3D hardware load related data and the virtual reality 3D software load related data are supplemented by linear interpolation method. The time interval of the virtual reality 3D hardware load related data and the virtual reality 3D software load related data is detected, and the long-term missing data is marked and deleted. The virtual reality 3D hardware load related data and the virtual reality 3D software load related data are smoothed by a low-pass filter, and the virtual reality 3D hardware load related data and the virtual reality 3D software load related data are normalized by using the Z-score normalization method.

5. The method for interactive three-dimensional visualization of a city based on virtual reality according to claim 1, characterized in that: The specific analysis process of analyzing the virtual reality 3D hardware load preprocessing data is as follows: The weight factor of the CPU core utilization rate of the VR computer, the weight factor of the GPU utilization rate of the VR computer, the weight factor of the video memory occupancy percentage of the VR computer, and the weight factor of the multi-thread scheduling efficiency of the VR computer are obtained from the database, the CPU core utilization rate of the VR computer, the GPU utilization rate of the VR computer, the video memory occupancy percentage of the VR computer, and the multi-thread scheduling efficiency of the VR computer are arranged in time series, weights are assigned to the CPU core utilization rate of the VR computer, the GPU utilization rate of the VR computer, the video memory occupancy percentage of the VR computer, and the multi-thread scheduling efficiency of the VR computer, and the standard values ​​of the CPU core utilization rate of the VR computer, the GPU utilization rate of the VR computer, the video memory occupancy percentage of the VR computer, and the multi-thread scheduling efficiency of the VR computer are compared with the average values ​​of the CPU core utilization rate of the VR computer, the GPU utilization rate of the VR computer, the video memory occupancy percentage of the VR computer, and the multi-thread scheduling efficiency of the VR computer, and the hardware load evaluation coefficient is obtained through processing.

6. The method for interactive three-dimensional visualization of a city based on virtual reality according to claim 1, characterized in that: The specific analysis process of analyzing the virtual reality three-dimensional software load preprocessing data is as follows: The weight factor of the number of polygons in the three-dimensional city when rendering each frame, the weight factor of the number of dynamic objects in the three-dimensional city when rendering each frame, the weight factor of the interactive delay from input to screen update in each frame rendering, and the weight factor of the data stream bandwidth in each frame rendering are obtained from the database, the number of polygons in the three-dimensional city when rendering each frame, the number of dynamic objects in the three-dimensional city when rendering each frame, the interactive delay from input to screen update in each frame rendering, and the data stream bandwidth in each frame rendering are arranged in frame sequence, and weights are assigned to the number of polygons in the three-dimensional city when rendering each frame, the number of dynamic objects in the three-dimensional city when rendering each frame, the interactive delay from input to screen update in each frame rendering, and the data stream bandwidth in each frame rendering. The standard values ​​of the number of polygons in the three-dimensional city when rendering each frame, the number of dynamic objects in the three-dimensional city when rendering each frame, the interactive delay from input to screen update in each frame rendering, and the data stream bandwidth in each frame rendering are compared with the average values ​​of the number of polygons in the three-dimensional city when rendering each frame, the number of dynamic objects in the three-dimensional city when rendering each frame, the interactive delay from input to screen update in each frame rendering, and the data stream bandwidth in each frame rendering, and the software load evaluation coefficient is obtained by processing.

7. The method for interactive three-dimensional visualization of a city based on virtual reality according to claim 1, characterized in that: The specific analysis process of comprehensively evaluating the hardware load evaluation coefficient and the software load evaluation coefficient is as follows: The weight factor of the hardware load assessment coefficient and the weight factor of the software load assessment coefficient are obtained from the database, weights are assigned to the hardware load assessment coefficient and the software load assessment coefficient, the hardware load assessment coefficient and the software load assessment coefficient are combined, and processed to obtain the rendering load assessment coefficient.

8. The method for interactive three-dimensional visualization of a city based on virtual reality according to claim 1, characterized in that: The specific threshold comparison method for comparing the hardware load evaluation coefficient, the software load evaluation coefficient and the rendering load evaluation coefficient with the hardware load evaluation threshold, the software load evaluation threshold and the rendering load evaluation threshold, respectively, is: Compare the hardware load assessment coefficient with the hardware load assessment threshold; if the hardware load assessment coefficient is less than the hardware load assessment threshold, directly perform real-time rendering on the sub-area; if the hardware load assessment coefficient is greater than or equal to the hardware load assessment threshold, execute the hardware load optimization plan for the real-time rendering of the sub-area; after executing the hardware load optimization plan, continue to compare the hardware load assessment coefficient with the hardware load assessment threshold; if the hardware load assessment coefficient is still greater than or equal to the hardware load assessment threshold, execute the software load optimization plan for the real-time rendering of the sub-area, compare the software load assessment coefficient with the software load assessment threshold; if the software load assessment coefficient is less than the software load assessment threshold, perform real-time rendering on the sub-area; if the software load assessment coefficient is greater than or equal to the software load assessment threshold, execute the rendering load optimization plan for the real-time rendering of the sub-area, compare the rendering load assessment coefficient with the rendering load assessment threshold; if the rendering load assessment coefficient is less than the rendering load assessment threshold, perform real-time rendering on the sub-area; if the rendering load assessment coefficient is greater than or equal to the rendering load assessment threshold, execute the balanced rendering quality optimization plan for the real-time rendering of the sub-area; Hardware load optimization solutions include dynamic resolution adjustment; Software load optimization solutions include interactive event priority scheduling and multi-threaded parallel processing; Rendering load optimization solutions include frustum-based GPU culling technology.

9. The method for interactive three-dimensional visualization of a city based on virtual reality according to claim 1, characterized in that: The specific process of the balanced rendering quality optimization solution is as follows: If after executing the hardware load optimization plan, the software load optimization plan and the rendering load optimization plan, if the rendering load evaluation coefficient is still greater than or equal to the rendering load evaluation threshold, the balanced rendering quality optimization plan is executed for the real-time rendering of the sub-area, including performing polygon merging on the real-time rendering of the sub-area, reducing the number of polygons and not rendering the polygons facing away from the camera. If the rendering load evaluation coefficient is less than the rendering load evaluation threshold, the balanced rendering quality optimization plan is no longer executed.

10. The city three-dimensional visualization interactive system based on virtual reality is characterized by: Including interaction and data collection module, data preprocessing module, data analysis module and optimization module: Interaction and data collection module: used to divide the city 3D model into multiple sub-areas. The user selects a sub-area and performs visual interaction on the model in the sub-area. During the user's visual interaction, the virtual reality computer renders the sub-area in real time and collects virtual reality 3D hardware load-related data and virtual reality 3D software load-related data; Data preprocessing module: used for preprocessing virtual reality 3D hardware load related data and virtual reality 3D software load related data to obtain virtual reality 3D hardware load preprocessing data and virtual reality 3D software load preprocessing data; Data analysis module: used to analyze virtual reality 3D hardware load preprocessing data to obtain hardware load evaluation coefficients, analyze virtual reality 3D software load preprocessing data to obtain software load evaluation coefficients, and conduct comprehensive evaluation of hardware load evaluation coefficients and software load evaluation coefficients to obtain rendering load evaluation coefficients; Optimization module: used to perform threshold comparison between the hardware load assessment coefficient, the software load assessment coefficient and the rendering load assessment coefficient and the hardware load assessment threshold, the software load assessment threshold and the rendering load assessment threshold respectively; based on the threshold comparison result of the hardware load assessment coefficient, a hardware load optimization plan is executed for the real-time rendering of the sub-area; if the hardware load assessment coefficient is still greater than or equal to the hardware load assessment threshold, a software load optimization plan is executed for the real-time rendering of the sub-area; based on the threshold comparison result of the software load assessment coefficient, a rendering load optimization plan is executed for the real-time rendering of the sub-area; based on the threshold comparison result of the rendering load assessment coefficient, a balanced rendering quality optimization plan is executed for the real-time rendering of the sub-area.

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