High-precision Scene Cloud Rendering Optimization Method Based on Digital Twin

Abstract

The present invention discloses a high-precision scene cloud rendering optimization method based on digital twins, which relates to the technical field of cloud rendering. In the present invention, the rendering request end requests the cloud to render the high-precision scene rendering file pre-uploaded by it, and the rendering display unit displays the rendering result data. At the same time, it monitors the click operations in the high-precision scene of the authorized user in real time, and preferentially matches and displays the attribute display information in the local display file to the authorized user for matching. In this way, the interaction operations with the cloud can be effectively reduced, and the interaction overhead is reduced; the attribute display information included in the local display file of the present invention is based on the data capacity size and display times of the attribute display information. In this way, some frequently interacted attribute display information is stored locally for quick display and viewing, effectively reducing the amount of information transmitted and optimizing the timely display of some data.

Description

Technical Field

[0001] The present invention relates to the technical field of cloud rendering, and specifically relates to an optimization method for high-precision scene cloud rendering based on digital twins. Background Technique

[0002] With the rapid development of information technology, digital twin technology has been widely applied in many fields, providing strong support for the accurate mapping and interaction between the physical world and the digital world. In the application of digital twins, cloud rendering of high-precision scenes is a key link; in today's digital age, the demand for high-precision scenes is increasing. For example, in urban planning, it is necessary to accurately present details such as buildings, roads, and infrastructure in the city; in the field of industrial manufacturing, the virtual display of complex mechanical equipment and production lines requires high realism; in the protection of cultural heritage, the digital reproduction of historical buildings and sites requires accurate restoration of every detail;

[0003] Currently, users will upload high-precision scene rendering files to the cloud in advance and utilize the rich computing resources in the cloud to achieve efficient rendering processing, ultimately achieving the purpose of online viewing. This measure not only ensures a high level and high efficiency of the rendering effect but also effectively reduces the pressure on local storage resources;

[0004] However, when users expect to interact with the rendered data, the frequent cloud interaction requirements undoubtedly increase the complexity of network communication, which may in turn affect the overall user experience;

[0005] For example, when a user wants to understand the relevant information of several models in the scene by clicking, they need to click on the model to view the information type they need; for such data, if all are processed by the cloud, the amount of information transmitted needs to be increased, which is bound to be unfavorable for the timely display of data.

[0006] To solve the above problems, the present invention proposes a solution. Summary of the Invention

[0007] The purpose of the present invention is to provide an optimization method for high-precision scene cloud rendering based on digital twins to solve the problems raised in the above background technique;

[0008] The purpose of the present invention can be achieved through the following technical solutions:

[0009] An optimization method for high-precision scene cloud rendering based on digital twins includes the following steps:

[0010] Step 1: The rendering display unit displays the rendering scene to authorized users and monitors the click operations of authorized users in the rendering scene in real time;

[0011] Step 2: When an authorized user clicks on a certain area in the rendered scene, obtain the image data of the frame corresponding to the clicked area, and obtain the position of the area in the image data, and generate a click event of the authorized user based on it;

[0012] Step 3: After the click event of the authorized user, preferentially match the attribute display information contained in the local display file. If it exists, display the matched attribute display information to the authorized user for viewing. Otherwise, transmit the click event to the rendering display unit, and the rendering display unit matches the consistent attribute display information and displays the attribute display information to the authorized user for viewing.

[0013] Further, before completing Step 1, the following steps need to be carried out:

[0014] SS1: After the authorized user inputs a cloud rendering instruction, the rendering request unit transmits the cloud rendering instruction to the cloud rendering unit;

[0015] SS2: After the cloud rendering unit receives the cloud rendering instruction, it performs cloud rendering on the high-precision scene rendering file pre-stored therein to obtain rendering result data;

[0016] SS3: After the rendering display unit receives the rendering result data, it generates a rendering scene based on it and displays it to the authorized user for viewing.

[0017] The high-precision scene rendering file contains scene description data, model data, material and texture data, environmental parameter data, and subjective parameter data.

[0018] Further, the scene description data contains the basic layout of the scene, the position, shape, and size of the objects; the model data includes specific 3D model files, including the models of specific objects and the entire scene in the scene.

[0019] Advantages of the present invention:

[0020] In the present invention, the rendering request end requests the cloud to render the pre-uploaded high-precision scene rendering file, the rendering display unit displays the rendering result data, and at the same time, it monitors the click operations of the authorized user in the high-precision scene in real time, preferentially matches the attribute display information in the local display file and displays it to the authorized user for matching. In this way, the interaction operations with the cloud can be effectively reduced, and the interaction overhead is reduced;

[0021] The attribute display information contained in the local display file of the present invention is based on the data capacity size and display times of the attribute display information. In this way, some frequently interacted attribute display information is stored locally for quick display and viewing, effectively reducing the amount of transmitted information and optimizing the timely display of some data. Brief Description of the Drawings

[0022] The present invention will be further described below in conjunction with the accompanying drawings.

[0023] Figure 1 It is a flowchart of the method of the present invention. Detailed Embodiments

[0024] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts shall fall within the protection scope of the present invention.

[0025] As Figure 1 shown, a high-precision scene cloud rendering optimization method based on digital twin, which is executed by a high-precision scene cloud rendering optimization system based on digital twin. The system includes a cloud rendering terminal and a rendering user terminal;

[0026] The rendering request terminal is used to authorize users to perform rendering with the help of the cloud; the rendering request terminal includes a rendering request unit and a rendering display unit;

[0027] The cloud rendering terminal is used to perform cloud rendering on the high-precision scene rendering files uploaded by authorized users. The cloud rendering terminal includes a cloud rendering unit, an interaction analysis unit, and a rendering optimization unit;

[0028] After the authorized user inputs a cloud rendering instruction, the rendering request unit transmits the cloud rendering instruction to the cloud rendering terminal. After receiving the transmitted cloud rendering instruction, the cloud rendering terminal transmits it to the cloud rendering unit;

[0029] The cloud rendering unit includes high-precision scene rendering files pre-stored by authorized users. The high-precision scene rendering files include scene description data, model data, material and texture data, environmental parameter data, and subjective parameter data;

[0030] Among them, the scene description data includes the basic layout of the scene, the position, shape, and size of objects; the model data includes specific 3D model files, including the models of specific objects and the entire scene within the scene; the material and texture data includes the material attributes of the surface appearance of objects within the scene, including but not limited to color, glossiness, roughness, and texture images, and the texture images include but not limited to wood grain, brick texture, etc.;

[0031] The environmental parameter data includes data on environmental factors such as lighting conditions, weather conditions, time, etc.; the subjective parameter data includes specific requirements of the user for rendering quality, resolution, frame rate, etc. For example, the user specifies to observe the scene from a certain angle and requires rendering at 4K resolution.

[0032] After receiving the transmitted cloud rendering instruction, the cloud rendering unit performs cloud rendering on the high-precision scene rendering file of the corresponding authorized user to obtain rendering result data. The rendering result data contains a number of frame image data and an interactive capture script. The number of frame image data is used to generate a high-quality rendered scene for the authorized user to view.

[0033] The interactive capture script is used to identify the click action of the authorized user in the image data and locate the click area.

[0034] The cloud rendering unit transmits the rendering result data to the rendering display unit. The rendering display unit receives it and generates a high-quality rendered scene based on the number of frame image data carried therein for the authorized user to view. At the same time, the interactive capture script is started to monitor the click operation of the user in the rendered scene in real time.

[0035] When the authorized user clicks on a certain area in the rendered scene, a frame of image data corresponding to the area when it is clicked is obtained, and the position of the area in the image data is obtained. According to the frame image data and the position of the area in the image data, a single click event of the authorized user is generated, and the single click event of the authorized user is transmitted to the cloud rendering unit.

[0036] After receiving the transmitted single click event of the authorized user, the cloud rendering unit matches the corresponding attribute display information according to the image data carried therein and the position of the area in the image data, and transmits the attribute display information as the feedback information of the click event to the rendering display unit.

[0037] After receiving the feedback information of the click event, the rendering display unit displays it for the authorized user to view.

[0038] The interactive analysis unit analyzes all click events of the authorized user. The analysis steps are as follows:

[0039] S11: Obtain the feedback information of all past click events of the authorized user, and select a type of attribute display information from it as the data to be analyzed.

[0040] S12: Obtain the click weight A1 of the data to be analyzed. The calculation formula of the click weight is A1 = B1 / C1, where B1 refers to the total number of times the data to be analyzed is displayed as feedback information in all past click events, and C1 refers to the total number of all past click events;

[0041] S13: Use the formula E1 = A1×ɑ1 + D1×ɑ2 to calculate and obtain the reserved evaluation amount E1 of the data to be analyzed, where ɑ1 and ɑ2 are the preset first and second adjustment ratios respectively, and D1 is the preset data capacity size of the data to be analyzed;

[0042] S14: Sequentially select the attribute display information included in the feedback information of the authorized user in all past click events as the data to be analyzed according to S13, and sequentially calculate and obtain the reserved evaluation amounts of all attribute display information;

[0043] Transmit the reserved evaluation amounts of the attribute display information included in the feedback information of the authorized user in all past click events to the rendering optimization unit;

[0044] The rendering optimization unit, in the order from largest to smallest of the reserved evaluation amounts, takes the attribute display information corresponding to all reserved evaluation amounts with values greater than or equal to P1 as the local display file and transmits it to the rendering display unit for pre-storage, where P1 is the preset selected evaluation threshold;

[0045] When the authorized user clicks on a certain area in the rendering scene next time, preferentially match the attribute display information included in the local display file. If it cannot be found, then generate the click event of the click according to it and transmit the click event to the cloud rendering unit;

[0046] In the description of the specification, the descriptions referring to terms such as "one embodiment", "example", "specific example", etc. mean that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0047] The above content is only an example and illustration of the present invention. Those skilled in the art of the present technology make various modifications or supplements to the described specific embodiments or use similar ways to replace them. As long as they do not deviate from the invention or exceed the scope defined by the claims of the present invention, they should all belong to the protection scope of the present invention.

[0048] The above has described in detail an embodiment of the present invention, but the content described above is only a preferred embodiment of the present invention and cannot be considered as limiting the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the application of the present invention should still fall within the scope covered by the patent of the present invention.

Claims

1. A high-precision scene cloud rendering optimization method based on digital twins, characterized in that, It includes the following steps: Step 1: The rendering display unit displays the rendering scene to the authorized user and monitors the click operations of the authorized user in the rendering scene in real time; Step 2: When the authorized user clicks on a certain area in the rendering scene, obtain the image data of a frame corresponding to the area when it is clicked, and obtain the position of the area in the image data, and generate a click event of the authorized user based on it; Step 3: According to the click event of the authorized user, preferentially match the attribute display information contained in the local display file. If it exists, display the matched attribute display information to the authorized user for viewing. Otherwise, transmit the click event to the rendering display unit, and the rendering display unit matches the consistent attribute display information and displays the attribute display information to the authorized user for viewing; The generation steps of the local display file are as follows: S11: Obtain the feedback information of all past click events of the authorized user, and select a kind of attribute display information from them as the data to be analyzed; S12: Obtain the click weight A1 of the data to be analyzed. The calculation formula of the click weight is A1 = B1 / C1, where B1 refers to the total number of times the data to be analyzed is displayed as feedback information in all past click events, and C1 refers to the total number of past click events; S13: Use the formula E1 = A1×ɑ1 + D1×ɑ2 to calculate and obtain the reserved evaluation amount E1 of the data to be analyzed, where ɑ1 and ɑ2 are the preset first and second adjustment ratios respectively, and D1 is the preset data capacity size of the data to be analyzed; S14: Select the attribute display information included in the feedback information of all past click events of the authorized user as the data to be analyzed in sequence according to S13, and calculate and obtain the reserved evaluation amounts of all attribute display information in sequence; The reserved evaluation amounts of the attribute display information included in the feedback information of all past click events of the authorized user; The rendering display unit takes the attribute display information corresponding to all reserved evaluation amounts with values greater than or equal to P1 as the local display file in the order from largest to smallest reserved evaluation amount, where P1 is the preset selected evaluation threshold.

2. The high-precision scene cloud rendering optimization method based on digital twin according to claim 1, wherein Before completing Step 1, the following steps are also required: SS1: After the authorized user inputs the cloud rendering instruction, the rendering request unit transmits the cloud rendering instruction to the cloud rendering unit; SS2: After the cloud rendering unit receives the cloud rendering instruction, it performs cloud rendering on the high-precision scene rendering file pre-stored in it to obtain the rendering result data; SS3: After the rendering display unit receives the rendering result data, it generates a rendering scene based on it and displays it to the authorized user for viewing.

3. The high-precision scenario cloud rendering optimization method based on digital twin according to claim 1, wherein The high-precision scene rendering file contains scene description data, model data, material and texture data, environmental parameter data, and subjective parameter data.

4. The high-precision scenario cloud rendering optimization method based on digital twin according to claim 3, wherein The scene description data contains the basic layout of the scene, the position, shape, and size of the objects; the model data includes specific 3D model files, including the models of specific objects and the entire scene in the scene.

5. The high-precision scenario cloud rendering optimization method based on digital twin according to claim 2, wherein The rendering result data also contains an interactive capture script, which is used to identify the click action of the authorized user in the image data and locate the click area of the user.

6. The method for optimizing high-precision scenario cloud rendering based on digital twin according to claim 5, wherein, The rendering display unit generates a high-rendering scene based on the rendering result data for authorized users to view, and at the same time starts the interactive capture script to monitor the user's click operations in the rendering scene in real time.

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