Dynamic response method and device for interactive object elements in interactive scene, equipment and medium

Abstract

The invention discloses a dynamic response method and device for interactive object elements in an interactive scene, equipment and a medium, and belongs to the technical field of Internet. The method comprises the following steps: collecting research data; analyzing the investigation data, and determining a scene type of an interaction scene needing to be generated; inputting the scene type into an AI model, and generating scene elements in the interaction scene through the AI model; applying the scene elements to an interaction platform for rendering to obtain an interaction scene; in the process of displaying the interaction scene, receiving an interaction operation sent by a user in the interaction scene; and identifying an interaction object element corresponding to the interaction operation, and generating a dynamic effect of the interaction object element in the interaction scene according to the interaction operation. According to the technical scheme, the interaction scene can be generated in a personalized mode according to the investigation and survey data, the corresponding dynamic effect is generated according to the interaction operation of the user, the content of the interaction scene is enriched, and the interactivity and immersion of the interaction scene can be improved.

Description

Technical Field

[0001] The present application belongs to the field of Internet technology, and specifically relates to a method, device, equipment and medium for dynamically responding to interactive object elements in an interactive scene. Background Art

[0002] With the development of science and technology, the application of augmented reality (AR) and virtual reality (VR) technologies is becoming more and more widespread. The interactive scenes created by these technologies can provide an immersive experience and significantly enhance the user's sense of participation and interactivity.

[0003] At present, the existing interactive scene creation methods still have some technical bottlenecks, such as low scene generation efficiency, insufficient interactivity, and lack of personalized experience. These problems are particularly prominent in large-scale game companies when various modules of the company are collaboratively developed.

[0004] Therefore, how to efficiently generate personalized interaction scenarios is a technical problem that needs to be urgently solved by technical personnel in this field. Summary of the invention

[0005] The embodiments of the present application provide a method, device, equipment and medium for dynamic response of interactive object elements in an interactive scene, with the purpose of generating an interactive scene based on personalized survey data, generating corresponding dynamic effects for the user's interactive operations, enriching the content of the interactive scene, and improving the interactivity and immersion of the interactive scene.

[0006] In a first aspect, this embodiment provides a method for dynamically responding to interactive object elements in an interactive scene, the method comprising:

[0007] Collecting survey data; wherein the survey data includes: at least one of user preference data, behavior data, environment data and historical data;

[0008] Analyze the survey data to determine the scene type of the interactive scene that needs to be generated;

[0009] Inputting the scene type into the AI ​​model, and generating scene elements in the interactive scene through the AI ​​model;

[0010] Applying the scene elements to the interactive platform for rendering to obtain an interactive scene;

[0011] In the process of displaying the interactive scene, receiving an interactive operation issued by a user in the interactive scene;

[0012] An interactive object element corresponding to the interactive operation is identified, and a dynamic effect of the interactive object element in the interactive scene is generated according to the interactive operation.

[0013] Furthermore, the scene elements in the interactive scene are generated by the AI ​​model, including:

[0014] Use TensorFlow and Keras to build an adversarial network, and generate scene elements in the interactive scene through the adversarial network;

[0015] and / or,

[0016] The existing scene element model is obtained through big data, and transfer learning is performed using PyTorch and Hugging FaceTransformers. The scene elements in the interactive scene are generated according to the existing scene element model.

[0017] Further, applying the scene elements to the interactive platform for rendering includes:

[0018] Use Unity 3D or Unreal Engine to render the scene elements in real time;

[0019] and / or,

[0020] Identify common elements among the scene elements, pre-render and cache them using Blender or Maya, and when the common elements are included in the user interface, load the pre-cached common elements that have been pre-rendered;

[0021] and / or,

[0022] Use AWS Gamelift or Google Cloud Gaming Solutions to render scene elements on cloud servers.

[0023] Further, receiving an interactive operation issued by the user in the interactive scenario includes:

[0024] Use Google Dialogflow or Amazon Lex to receive user voice commands as user interaction operations;

[0025] and / or,

[0026] Use Leap Motion or Microsoft Kinect to capture the user's gestures as user interaction operations;

[0027] and / or,

[0028] Use the Unity Touch API or ARKit / ARCore to obtain the user's touch operations on the mobile device as the user's interactive operations.

[0029] Furthermore, after the scene elements in the interactive scene are generated by the AI ​​model, the method further includes:

[0030] Using Firebase Realtime Database or AWS Lambda to collect user feedback information, and adjusting scene elements in the interactive scene according to the feedback information;

[0031] and / or,

[0032] Analyze the user's behavior data through Google BigQuery ML or Amazon Personalize, and adjust the scene elements in the interaction scene when the analysis results meet the preset conditions;

[0033] and / or,

[0034] When the user triggers a scene switch, an interactive scene after the switch is generated according to the scene element triggered by the user, and scene elements in the interactive scene after the switch are generated.

[0035] Furthermore, after applying the scene elements to the interactive platform for rendering to obtain the interactive scene, the method further includes:

[0036] Use Selenium or Appium to perform automated testing and obtain test results;

[0037] Optimizing the interaction scenario according to the test results;

[0038] and / or

[0039] Use New Relic or Dynatrace to monitor the performance indicators of the interaction scenario in real time to obtain monitoring data;

[0040] Optimizing the performance of the interaction scenario according to the monitoring data;

[0041] and / or,

[0042] Conduct user testing using UserTesting or Hotjar to collect user experience data;

[0043] The interaction scenario is optimized according to the experience data.

[0044] Furthermore, in the case where the survey data includes the environmental data, analyzing the survey data to determine the scene type of the interaction scene to be generated includes:

[0045] Extracting environmental data from the survey data, and obtaining weather data for the user's area based on the environmental data;

[0046] The weather data is analyzed, and when the weather data indicates a rainy day, it is determined that the scene type of the interactive scene to be generated is an indoor scene type.

[0047] In a second aspect, this embodiment provides a dynamic response device for interactive object elements in an interactive scene, the device comprising:

[0048] A survey data collection module, used to collect survey data; wherein the survey data includes: at least one of user preference data, behavior data, environment data and historical data;

[0049] A scenario type determination module, used to analyze the survey data and determine the scenario type of the interactive scenario to be generated;

[0050] A scene element generation module, used to input the scene type into the AI ​​model, and generate scene elements in the interactive scene through the AI ​​model;

[0051] An interactive scene acquisition module, used to apply the scene elements to the interactive platform for rendering to obtain an interactive scene;

[0052] An interactive operation receiving module, used to receive an interactive operation issued by a user in the interactive scene during the process of displaying the interactive scene;

[0053] The dynamic effect generation module is used to identify the interactive object element corresponding to the interactive operation and generate a dynamic effect of the interactive object element in the interactive scene according to the interactive operation.

[0054] In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the method described in the first aspect.

[0055] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented.

[0056] In a fifth aspect, an embodiment of the present application provides a chip, comprising a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the method described in the first aspect.

[0057] In an embodiment of the present application, survey data is collected; wherein the survey data includes: at least one of user preference data, behavior data, environmental data, and historical data; the survey data is analyzed to determine the scene type of the interactive scene that needs to be generated; the scene type is input into the AI ​​model, and the scene elements in the interactive scene are generated by the AI ​​model; the scene elements are applied to the interactive platform for rendering to obtain the interactive scene; in the process of displaying the interactive scene, the interactive operation issued by the user in the interactive scene is received; the interactive object element corresponding to the interactive operation is identified, and the dynamic effect of the interactive object element in the interactive scene is generated according to the interactive operation. Through the above-mentioned method of dynamic response of interactive object elements in an interactive scene, the interactive scene can be generated according to the survey data, and the corresponding dynamic effects can be generated for the user's interactive operation, enriching the content of the interactive scene, which is conducive to improving the interactivity and immersion of the interactive scene. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a flowchart of a dynamic response method of an interactive object element in an interactive scene provided in Example 1 of the present application;

[0059] Figure 2 This is a schematic diagram showing an interactive scene provided in Example 1 of the present application;

[0060] Figure 3 It is a flowchart of a dynamic response method of an interactive object element in an interactive scene provided in Embodiment 2 of the present application;

[0061] Figure 4 It is a flowchart of a dynamic response method of an interactive object element in an interactive scene provided in Embodiment 3 of the present application;

[0062] Figure 5 It is a flowchart of a method for dynamic response of interactive object elements in an interactive scene provided in Embodiment 4 of the present application;

[0063] Figure 6 It is a flowchart of a dynamic response method of an interactive object element in an interactive scene provided in Embodiment 5 of the present application;

[0064] Figure 7 It is a flowchart of a dynamic response method of an interactive object element in an interactive scene provided in Example 6 of the present application;

[0065] Figure 8 It is a structural schematic diagram of a dynamic response device of an interactive object element in an interactive scene provided in Embodiment 7 of the present application;

[0066] Fig. 9 It is a schematic diagram of the structure of the electronic device provided in Example 8 of the present application. DETAILED DESCRIPTION

[0067] In order to make the purpose, technical scheme and advantages of the present application clearer, the specific embodiments of the present application are further described in detail below in conjunction with the accompanying drawings. It is understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for the convenience of description, only the part related to the present application but not all the contents are shown in the accompanying drawings. Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow chart describes each operation (or step) as a sequential process, many of the operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of each operation can be rearranged. The process can be terminated when its operation is completed, but it can also have additional steps not included in the accompanying drawings. The process can correspond to a method, a function, a procedure, a subroutine, a subprogram, etc.

[0068] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

[0069] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0070] In conjunction with the accompanying drawings, the following describes in detail a method, device, equipment and medium for dynamically responding to interactive object elements in an interactive scene provided by an embodiment of the present application through specific embodiments and application scenarios.

[0071] Embodiment 1

[0072] Figure 1 It is a flowchart of a dynamic response method of an interactive object element in an interactive scene provided in Example 1 of the present application.

[0073] like Figure 1 As shown, the specific steps include:

[0074] S101, collecting research data; wherein the research data includes: at least one of user preference data, behavior data, environment data and historical data;

[0075] The application scenario of this solution can be a scenario in which AR scenes or VR scenes are intelligently generated based on survey data.

[0076] Based on the above scenario, it can be understood that the executor of this scenario can be an intelligent terminal used to analyze data and create interactive scenarios, such as a computer or software component that provides services in a network environment, etc., and no excessive limitations are made here.

[0077] User preference data may be user preferences and requirements for game scenes. For example, users hope to add more interactive elements such as more animals and collected resources to the forest adventure scene.

[0078] The behavior data may be the behavior data emitted by the user in an AR scene or a VR scene, such as walking across the grass, reaching out to grab an object, and pushing an object.

[0079] Environmental data may be geographic information and weather data of the user's area.

[0080] The historical data may be the historical user usage data recorded by the application that needs to create an interactive scenario.

[0081] The way to collect survey data is to conduct a questionnaire survey on users through survey platforms such as SurveyMonkey, analyze the survey results with Google Analytics, and then determine the user preference data. When the user runs the application, you can collect and analyze the user's behavior data by using Firebase Analytics (a data analysis tool designed specifically for mobile devices) or Mixpanel (a cloud data analysis tool). When the user logs in to the application, you can obtain the user's area based on the user's login device, and then use Google Earth Engine (a cloud platform for online visualization and analysis of satellite data) to obtain geographic information, and obtain real-time weather data through OpenWeatherMapAPI (a web service interface that provides global weather data). The application's historical records can be extracted and cleaned through BigQuery and Python Pandas to obtain historical data.

[0082] In addition, you can also use Tableau (a self-service analytics cloud platform) to visualize market data and obtain the current market trends of AR and / or VR games, obtain industry reports through Statista (a data statistics Internet company) to predict future trends, and use SEMrush (a comprehensive online marketing competitive intelligence platform) or App Annie (for data analysis in the mobile application and digital content era) to analyze user reviews and market strategies of competitors. As research data, there are no excessive restrictions here.

[0083] S102: Analyze the survey data to determine the scene type of the interactive scene to be generated;

[0084] Interaction scenarios can be specific situations or environments that occur when humans and computers interact or when users and systems, such as software applications, websites, mobile devices, and IoT devices, for example, AR scenarios and VR scenarios in game applications.

[0085] Scene type, which can be the theme of the interactive scene, for example, forest, beach, city, and countryside.

[0086] The scenario type of the interactive scenario to be generated may be determined by analyzing the survey data and counting the scenario type that is most popular with users as the scenario type of the interactive scenario to be generated.

[0087] S103, inputting the scene type into an AI model, and generating scene elements in an interactive scene through the AI ​​model;

[0088] AI models can refer to a system that can simulate human intelligent behavior through computer algorithms and data training. These models use machine learning, deep learning and other technologies to enable computers to complete complex tasks such as image recognition, speech recognition, natural language processing and machine translation.

[0089] Scene elements can be components of an interactive scene, such as trees, grass, and animals in a forest scene; vehicles, houses, and pedestrians in an urban scene.

[0090] The method for generating scene elements in interactive scenes can be to pre-acquire scene elements in different scene types, use scene elements as labels and scene types as variables, conduct supervised training, and then build an AI model that can generate scene elements that match the scene type, input the currently acquired scene type into the pre-built AI model, and the AI ​​model generates scene elements related to the input scene type based on the learned association between scene elements and scene types.

[0091] S104, applying the scene elements to the interactive platform for rendering to obtain an interactive scene;

[0092] The interactive platform may be an AR (Augmented Reality) platform or a VR (Virtual Reality) platform, etc., which can provide users with virtual interactive scenes and platforms for interacting with users.

[0093] Rendering can be the process of converting a 3D model or scene into a 2D image. Rendering can optimize the various materials and lighting in the scene elements, making the entire interactive scene more realistic.

[0094] The method of applying scene elements to the interactive platform for rendering is that after the scene elements are input into the interactive platform, the interactive platform selects appropriate materials for each scene element, such as metal, wood or plastic, and sets the material properties, such as color, glossiness and transparency. At the same time, add texture maps to the scene elements to simulate the surface texture of objects in reality. Then select a suitable light source for the interactive scene, such as a point light source, parallel light source or spotlight, and set the position, direction and intensity of the light source. Perform rendering settings as needed, including anti-aliasing coefficient, lighting mode and exposure method. Export the rendered image or video as an interactive scene.

[0095] For example, taking VR as an example, Figure 2 is a schematic diagram showing an interactive scene provided in Example 1 of the present application, such as Figure 2 As shown, scene elements such as houses, trees, and animals are rendered to form an interactive scene, which is then displayed through a VR game. Users can view the generated interactive scene through VR glasses. In the interactive scene, the scene elements have similar colors and textures to the corresponding objects in reality, and can interact with users to increase their sense of immersion.

[0096] S105. In the process of displaying the interactive scene, receiving an interactive operation issued by a user in the interactive scene;

[0097] Interaction operations can be interactions performed by users with scene elements in the interactive scene displayed while running the application, such as users hunting deer in the forest or touching flowers on the grass.

[0098] The method of receiving interactive operations issued by users can be that after the interactive platform renders the interactive scene, it is displayed to the user through an application. In the displayed interactive scene, the user can interact with the scene elements through gestures, voice and other operations, and the smart terminal captures the user's specific interactive operations and interactive objects.

[0099] S106: Identify the interactive object element corresponding to the interactive operation, and generate a dynamic effect of the interactive object element in the interactive scene according to the interactive operation.

[0100] An interactive object element may be an object that a user performs interactive operations on in an interactive scene. For example, in an interactive operation in which a user hunts animals in a forest, the hunted animals are interactive object elements; in an interactive operation in which a user touches a flower on a lawn, the flower is an interactive object element.

[0101] Dynamic effects can be dynamic responses of interactive object elements to user interactive operations based on actual conditions. For example, when a user shoots a deer in the forest, the deer will fall to the ground or run away in fright; when a user touches a flower on the grass, the flower will shake slightly as the user touches it.

[0102] The interactive object element corresponding to the interactive operation may be identified by identifying scene elements around the body part of the user performing the interactive operation and using the scene elements as the interactive object elements. For example, if the user's interactive operation is walking on the grass, the grass stepped on by the user and the grass touched by the user's trouser legs are the interactive object elements.

[0103] The method of generating the dynamic effect of the interactive object element in the interactive scene according to the interactive operation can be to determine the dynamic effect of the interactive operation on the interactive object element in the interactive scene by the reaction caused by the user's interactive operation in the actual situation. For example, in the actual situation, if waving to drive away birds will cause the flock of birds to fly away, then if the user's interactive operation is to wave to drive away the sparrow resting on the hat, the dynamic effect generated by the sparrow in the interactive scene is to avoid the user and fly away from the user's hat.

[0104] Based on the above solution, optionally, when the survey data includes the environment data, analyzing the survey data to determine the scene type of the interaction scene to be generated includes:

[0105] Extracting environmental data from the survey data, and obtaining weather data for the user's area based on the environmental data;

[0106] The weather data is analyzed, and when the weather data indicates a rainy day, it is determined that the scene type of the interactive scene to be generated is an indoor scene type.

[0107] The weather data of the area where the user is located may be obtained by identifying the obtained environmental data and extracting the weather data therein.

[0108] Determining that the scene type of the interactive scene to be generated is an indoor scene type can be that when the acquired weather data shows that the user's area is rainy, it is predicted that the user will prefer indoor interactive scenes, such as indoor scene types such as houses and shopping malls. Therefore, indoor scene types can be generated for users to choose, so as to achieve accurate push based on user preferences.

[0109] The benefit of this arrangement is that it can predict the user's preference for the scene type of the interactive scene based on the weather data in the user's area, which is conducive to pushing scene types that are more in line with the user's preferences and increasing the attractiveness to the user.

[0110] In an embodiment of the present application, survey data is collected; wherein the survey data includes: at least one of user preference data, behavior data, environmental data, and historical data; the survey data is analyzed to determine the scene type of the interactive scene that needs to be generated; the scene type is input into the AI ​​model, and the scene elements in the interactive scene are generated by the AI ​​model; the scene elements are applied to the interactive platform for rendering to obtain the interactive scene; in the process of displaying the interactive scene, the interactive operation issued by the user in the interactive scene is received; the interactive object element corresponding to the interactive operation is identified, and the dynamic effect of the interactive object element in the interactive scene is generated according to the interactive operation. Through the above-mentioned method of dynamic response of interactive object elements in an interactive scene, the interactive scene can be generated according to the survey data, and the corresponding dynamic effects can be generated for the user's interactive operation, enriching the content of the interactive scene, which is conducive to improving the interactivity and immersion of the interactive scene.

[0111] Embodiment 2

[0112] Figure 3 This is a flow chart of a dynamic response method of interactive object elements in an interactive scene provided in Example 2 of the present application. This solution makes a better improvement on the above-mentioned embodiment, and the specific improvement is: generating scene elements in the interactive scene through the AI ​​model, including: using TensorFlow and Keras to build an adversarial network, and generating scene elements in the interactive scene through the adversarial network; and / or, obtaining an existing scene element model through big data, using PyTorch and Hugging Face Transformers for transfer learning, and generating scene elements in the interactive scene according to the existing scene element model.

[0113] like Figure 3 As shown, specifically including the following:

[0114] S301, collecting research data; wherein the research data includes: at least one of user preference data, behavior data, environment data and historical data;

[0115] S302: Analyze the survey data to determine the scene type of the interactive scene to be generated;

[0116] S303, using TensorFlow and Keras to build an adversarial network, and generating scene elements in the interactive scene through the adversarial network;

[0117] and / or,

[0118] Obtain an existing scene element model through big data, use PyTorch and Hugging FaceTransformers for transfer learning, and generate scene elements in the interactive scene based on the existing scene element model;

[0119] TensorFlow is an open source machine learning framework developed by the Google Brain team, dedicated to automatic differentiation of data flow graphs and deep neural network calculations. TensorFlow is cross-platform and flexible to use, and is widely used to build, train, and deploy machine learning models.

[0120] Keras is a high-level neural network interface consisting of configurable and composable building blocks that provides a clear way to define and train deep learning models.

[0121] Adversarial networks can be a deep learning model consisting of two key components: the generator and the discriminator. Adversarial networks implement generative models through adversarial training of two networks. The generator tries to generate samples as realistic as possible to fool the discriminator, while the discriminator strives to improve its recognition ability, thereby driving the generator to continuously improve the generated samples.

[0122] The way to build an adversarial network is to use TensorFlow and Keras to build a generator and a discriminator, where the generator is used to generate scene elements according to the scene type and send the generated scene elements to the discriminator. The discriminator is used to determine whether the scene elements generated by the generator are real or model-generated based on a pre-input discrimination mechanism. When the discriminator believes that the current scene element is generated by the model, the generator optimizes the current scene element and sends the optimized scene element to the discriminator again for judgment until the discriminator believes that the scene element is real. The construction of the adversarial network is completed.

[0123] The method of generating scene elements in the interactive scene is to input the scene type into the generator of a pre-built adversarial network, generate scene elements and send them to the discriminator. When the discriminator determines that the scene element is real, the adversarial network outputs realistic scene elements.

[0124] PyTorch is an open source deep learning framework for machine learning and deep learning. It mainly implements automatic differentiation functions and introduces dynamic computational graphs to make model building more flexible.

[0125] Hugging Face Transformers is an open source Python library that provides state-of-the-art pre-trained models for various tasks such as natural language processing, computer vision, and audio. The core module of Transformer is to capture the dependencies between sequences through the self-attention mechanism.

[0126] The existing scene element model may be obtained by searching for scene elements that match the scene type through big data, and downloading the search results as the existing scene element model.

[0127] The method of generating scene elements in interactive scenes according to the existing scene element model is to use PyTorch and Hugging Face Transformers to build a learning model after obtaining the scene element model, and input the scene element model as an example into the pre-built learning model, so that the learning model can learn the characteristics of the scene element model, and then generate similar scene elements, and fine-tune the generated scene elements according to the requirements of the interactive scene to generate scene elements that are more consistent with the scene type.

[0128] S304, applying the scene elements to the interactive platform for rendering to obtain an interactive scene;

[0129] S305: receiving an interactive operation issued by a user in the interactive scene during displaying the interactive scene;

[0130] S306: Identify the interactive object element corresponding to the interactive operation, and generate a dynamic effect of the interactive object element in the interactive scene according to the interactive operation.

[0131] The advantage of this arrangement of the present invention is that scene elements can be generated through adversarial networks and / or transfer learning, making the scene elements more realistic, thereby enhancing the picture quality of subsequent interactive scenes and improving the user experience.

[0132] Embodiment 3

[0133] Figure 4It is a flow chart of a dynamic response method of interactive object elements in an interactive scene provided in Example 3 of the present application. This solution makes a better improvement on the above-mentioned embodiment, and the specific improvement is: applying the scene elements to the interactive platform for rendering, including: using Unity 4D or Unreal Engine to render the scene elements in real time; and / or, identifying common elements in the scene elements, pre-rendering and caching them using Blender or Maya, and when the common elements are included in the user interface, loading the pre-cached common elements that have been pre-rendered; and / or, using AWS Gamelift or Google Cloud Gaming Solutions to render the scene elements on a cloud server.

[0134] like Figure 4 As shown, specifically including the following:

[0135] S401, collecting research data; wherein the research data includes: at least one of user preference data, behavior data, environment data and historical data;

[0136] S402: Analyze the survey data to determine the scene type of the interactive scene to be generated;

[0137] S403, inputting the scene type into an AI model, and generating scene elements in an interactive scene through the AI ​​model;

[0138] S404, using Unity 4D or Unreal Engine to render the scene elements in real time to obtain an interactive scene;

[0139] and / or,

[0140] Identify common elements in the scene elements, pre-render and cache them using Blender or Maya, and when the common elements are included in the user interface, load the pre-cached common elements that have been pre-rendered to obtain an interactive scene;

[0141] and / or,

[0142] Use AWS Gamelift or Google Cloud Gaming Solutions to render scene elements on a cloud server to get an interactive scene;

[0143] Unity 4D is a cross-platform game development engine that allows developers to create 2D and 4D video games, simulation training, real-time 4D animation, virtual reality (VR) and augmented reality (AR) experiences, etc. Unity 4D is known for its ease of use, flexibility, and wide support for multiple platforms.

[0144] Unreal Engine, which can be Unreal Engine, can produce beautiful graphics suitable for video games, movies and other interactive applications.

[0145] The method of real-time rendering of scene elements can be that when the user runs the application, the application displays the interactive scene. During the display process, as the user moves in the interactive scene and interacts, the screen is calculated and displayed simultaneously, so that the user can get instant feedback and experience in the virtual environment.

[0146] Common elements can be element units that appear frequently in interactive scenes, such as trees in a forest, buildings in a city, etc.

[0147] Blender is an open source 3D graphics software that provides a series of animation short film production solutions from modeling, animation, materials, rendering, to audio processing and video editing.

[0148] Maya is a 3D computer graphics software that integrates the most advanced animation and digital effects technologies of Alias ​​and Wavefront, provides a wealth of modeling tools, and supports multiple renderers.

[0149] The method of identifying common elements among scene elements may be to count the number of occurrences of each scene element in the interactive scene, and when the number of occurrences is greater than a preset threshold, the corresponding scene element is regarded as a common element.

[0150] The method of pre-rendering and caching commonly used elements can be to pre-generate static content of commonly used elements and temporarily store the static content to a specified location. When it is necessary to generate an interactive scene containing common elements, there is no need to re-render. The processed static content can be directly read from the cache location for further calculation and rendering, thereby obtaining the dynamic content of the commonly used elements.

[0151] AWS Gamelift is a dedicated game server hosting solution that can deploy, operate, and scale cloud servers for multiplayer games.

[0152] Google Cloud Gaming Solutions is a series of comprehensive solutions provided by Google Cloud for game developers, designed to help developers build, deploy and manage high-performance, scalable gaming applications.

[0153] The way to render scene elements on the cloud server is to distribute the scene elements that need to be rendered in the interactive scene to the cloud server through AWS Gamelift or Google Cloud Gaming Solutions to perform the rendering task. After the cloud server completes the rendering, it is sent to the user end for display, thereby reducing the load on the user end and improving the rendering efficiency of the interactive scene.

[0154] S405: receiving an interactive operation issued by a user in the interactive scene during displaying the interactive scene;

[0155] S406: Identify the interactive object element corresponding to the interactive operation, and generate a dynamic effect of the interactive object element in the interactive scene according to the interactive operation.

[0156] The benefit of this setting is that the interactive scene can be rendered through real-time rendering, pre-rendering and cloud rendering, thereby improving rendering efficiency and frame rate, increasing the fluency of the application and improving the user experience.

[0157] Embodiment 4

[0158] Figure 5 This is a flowchart of a dynamic response method for interactive object elements in an interactive scene provided by Example 4 of the present application. This solution makes a better improvement on the above-mentioned embodiment, and the specific improvement is: receiving the interactive operation issued by the user in the interactive scene, including: using Google Dialogflow or Amazon Lex to receive the user's voice command as the user's interactive operation; and / or, using Leap Motion or Microsoft Kinect to capture the user's gesture action as the user's interactive operation; and / or, using Unity Touch API or ARKit / ARCore to obtain the user's touch operation in the mobile device as the user's interactive operation.

[0159] like Figure 5 As shown, specifically including the following:

[0160] S501, collecting research data; wherein the research data includes: at least one of user preference data, behavior data, environment data and historical data;

[0161] S502: Analyze the survey data to determine the scene type of the interactive scene to be generated;

[0162] S503: input the scene type into an AI model, and generate scene elements in an interactive scene through the AI ​​model;

[0163] S504, applying the scene elements to the interactive platform for rendering to obtain an interactive scene;

[0164] S505, using Google Dialogflow or Amazon Lex to receive the user's voice command as the user's interactive operation;

[0165] and / or,

[0166] Use Leap Motion or Microsoft Kinect to capture the user's gestures as user interaction operations;

[0167] and / or,

[0168] Use Unity Touch API or ARKit / ARCore to obtain the user's touch operation on the mobile device as the user's interactive operation;

[0169] Google Dialogflow is a natural language understanding platform that allows developers to easily integrate conversational user interfaces into various applications. By providing powerful natural language processing capabilities, users can interact with applications in a natural and fluent way.

[0170] Amazon Lex is a fully managed AI service with advanced natural language models designed for designing, building, testing, and deploying voice and text conversational interfaces in your applications.

[0171] Receiving user voice commands as a user interaction operation can be done by using Google Dialogflow or Amazon Lex to develop voice recognition and natural language processing interfaces for applications, so that the application can receive the user's voice while displaying the interactive scene, and generate corresponding voice commands based on the user's voice, so that the scene elements in the interactive scene generate corresponding dynamic effects. For example, if the user issues the command "pick the fruit from the tree" in the interactive scene, the character controlled by the user will appear to pick the fruit from the tree, and the corresponding fruit tree and fruit will produce dynamic effects of shaking and moving respectively.

[0172] Leap Motion is an advanced somatosensory interaction device that uses optical gesture tracking technology to detect and track users' hands, fingers, and finger-like tools.

[0173] Microsoft Kinect is a computer hardware device that has highly accurate motion tracking capabilities, can recognize user gestures, movements, and postures, and convert this information into digital signals to enable interaction with the computer.

[0174] Capturing the user's gestures as a way of user interaction can be to predict the gestures that the user may make in advance and set corresponding interaction instructions for the predicted gestures. For example, the gesture of holding up the gun barrel is set as the interaction instruction for opening the field of view of the sniper rifle scope, etc. When the user runs the application, LeapMotion or Microsoft Kinect is used to capture the user's gestures, and the captured gestures are compared with the predicted gestures. When the comparison is consistent, an interaction instruction associated with the current gesture is generated.

[0175] Unity Touch API is a set of APIs provided by the Unity engine for processing touch input. It allows developers to implement various touch interaction functions in Unity projects, such as clicking, sliding, and zooming.

[0176] ARKit / ARCore are two popular augmented reality technology platforms that provide developers with a simple and efficient way to build augmented reality applications that enable users to interact with virtual objects in the real world.

[0177] The user's touch operation in the mobile device is obtained as a user's interactive operation. When the user uses the mobile device to control the character in the interactive scene, the user's operation on the touch screen of the mobile device can be recorded through the Unity Touch API or ARKit / ARCore, and the corresponding interactive operation instructions can be obtained. For example, the user slides his finger in different directions on the touch screen of the mobile device, and then the character in the interactive scene can be controlled to move in different directions in the current scene.

[0178] S506: Identify the interactive object element corresponding to the interactive operation, and generate a dynamic effect of the interactive object element in the interactive scene according to the interactive operation.

[0179] The advantage of this setting is that the interaction function between the user and the interactive scene can be realized through voice, gestures, touch, etc., which enhances the interactivity and participation of the user in the interactive scene and attracts the user's interest in the interactive scene.

[0180] Embodiment 5

[0181] Figure 6It is a flow chart of a dynamic response method of interactive object elements in an interactive scene provided in Example 5 of the present application. This solution makes a better improvement on the above-mentioned embodiment, and the specific improvement is: after the scene elements in the interactive scene are generated by the AI ​​model, the method also includes: using Firebase Realtime Database or AWSLambda to collect user feedback information, and adjusting the scene elements in the interactive scene according to the feedback information; and / or, analyzing the user's behavior data through Google BigQuery ML or Amazon Personalize, and adjusting the scene elements in the interactive scene when the analysis results meet the preset conditions; and / or, when the user triggers a scene switch, generating the switched interactive scene according to the scene elements triggered by the user, and generating the scene elements in the switched interactive scene.

[0182] like Figure 6 As shown, specifically including the following:

[0183] S601, collecting research data; wherein the research data includes: at least one of user preference data, behavior data, environment data and historical data;

[0184] S602: Analyze the survey data to determine the scene type of the interactive scene to be generated;

[0185] S603: input the scene type into an AI model, and generate scene elements in an interactive scene through the AI ​​model;

[0186] S604, using Firebase Realtime Database or AWS Lambda to collect user feedback information, and adjusting scene elements in the interactive scene according to the feedback information;

[0187] and / or,

[0188] Analyze the user's behavior data through Google BigQuery ML or Amazon Personalize, and adjust the scene elements in the interaction scene when the analysis results meet the preset conditions;

[0189] and / or,

[0190] When the user triggers a scene switch, the interactive scene after the switch is generated according to the scene element triggered by the user, and the scene elements in the interactive scene after the switch are generated;

[0191] Firebase Realtime Database is a NoSQL database hosted in the cloud that allows developers to store and synchronize user data in real time.

[0192] AWS Lambda, a serverless computing service, allows users to run code without managing servers, automatically scales applications, and allocates precise computing execution capacity to code executed by each trigger.

[0193] The method of adjusting the scene elements in the interactive scene can be to use Firebase Realtime Database or AWS Lambda to collect user feedback information in the process of displaying the interactive scene to the user, for example, to collect the user's comments such as "resources are too hard to find" and "interactions are too little" in the interactive scene, or to receive the text content entered by the user in the feedback information input box. And adjust the content and difficulty of the game scene in real time according to the feedback information, for example, if the user feedback is that the resources are too hard to find, then increase the number of resources in the interactive scene, or place the resources in the interactive scene in a position that is easy to find; if the user feedback is that the interaction is too little, then increase the number of animal species and tasks in the interactive scene.

[0194] Google BigQuery ML, an integrated part of the Google Cloud BigQuery data warehouse, provides the ability to train machine learning models and make predictions directly inside the data warehouse.

[0195] Amazon Personalize is a fully managed machine learning service that uses your data to generate personalized product and content recommendations for you.

[0196] The preset condition may be a pre-set condition used to determine whether the scene elements need to be adjusted based on the difficulty of the user completing the task in the interactive scene.

[0197] The scene elements in the interactive scene can be adjusted by obtaining the time it takes for the user to complete the task in the interactive scene, the exploration habits and other behavioral data, analyzing the user's behavioral data through Google BigQuery ML or Amazon Personalize, obtaining the analysis results, and comparing the analysis results with the preset conditions. When the analysis results meet the requirements of the preset conditions, the scene elements in the interactive scene are adjusted accordingly. For example, when the time it takes for the user to complete the task is greater than 6 minutes, it is judged that the current task is more difficult for the user, and the difficulty coefficient of the user's subsequent tasks is reduced accordingly; or, when the number of times the user chooses to explore exceeds 3 times, it is judged that the user prefers to explore, and the subsequent exploration routes are added.

[0198] Scene switching may be switching of the interactive scene in which the user is located. For example, when entering a cabin in the forest, the interactive scene switches from the forest to the cabin.

[0199] The method of generating the interactive scene after switching and the scene elements in the interactive scene after switching can be to obtain the scene elements triggered by the user. For example, if the user pushes open the door of the wooden house, the scene element triggered by the user is the wooden house door; if the user enters the cave, the scene element triggered by the user is the cave. The scene type to which the scene element belongs is analyzed, and the interactive scene and scene elements that match the scene type are dynamically generated through tools such as OpenAI API (a series of interfaces developed by OpenAI that allow developers to easily call the large model basic capabilities provided by OpenAI in applications. These APIs cover a variety of functions, including text generation, reasoning, etc.) or GPT-4o (which has the function of accepting any combination of text, audio and images as input, and generating corresponding text, audio and image output, as well as real-time reasoning on audio, vision and text).

[0200] S605, applying the scene elements to the interactive platform for rendering to obtain an interactive scene;

[0201] S606: receiving an interactive operation issued by a user in the interactive scene during displaying the interactive scene;

[0202] S607: Identify the interactive object element corresponding to the interactive operation, and generate a dynamic effect of the interactive object element in the interactive scene according to the interactive operation.

[0203] The advantage of this setting of the scheme is that the scene elements in the interactive scene can be dynamically adjusted according to the user's feedback information, behavior data and the scene elements triggered by the user, thereby making the display of the interactive scene smoother and improving the user experience.

[0204] Embodiment 6

[0205] Figure 7 This is a flow chart of a method for dynamically responding to interactive object elements in an interactive scene provided by Example 6 of the present application. This solution makes a better improvement on the above-mentioned embodiment, and the specific improvement is: after applying the scene element to the interactive platform for rendering and obtaining the interactive scene, the method further includes:

[0206] Use Selenium or Appium to perform automated testing to obtain test results; optimize the interaction scenario based on the test results; and / or use New Relic or Dynatrace to monitor the performance indicators of the interaction scenario in real time to obtain monitoring data; optimize the performance of the interaction scenario based on the monitoring data; and / or use UserTesting or Hotjar to perform user testing to collect user experience data; optimize the interaction scenario based on the experience data.

[0207] like Figure 7 As shown, specifically including the following:

[0208] S701, collecting research data; wherein the research data includes: at least one of user preference data, behavior data, environment data and historical data;

[0209] S702: Analyze the survey data to determine the scene type of the interactive scene to be generated;

[0210] S703: input the scene type into an AI model, and generate scene elements in an interactive scene through the AI ​​model;

[0211] S704, applying the scene elements to the interactive platform for rendering to obtain an interactive scene;

[0212] S705. Use Selenium or Appium to perform automated testing and obtain test results;

[0213] Optimizing the interaction scenario according to the test results;

[0214] and / or

[0215] Use New Relic or Dynatrace to monitor the performance indicators of the interaction scenario in real time to obtain monitoring data;

[0216] Optimizing the performance of the interaction scenario according to the monitoring data;

[0217] and / or,

[0218] Conduct user testing using UserTesting or Hotjar to collect user experience data;

[0219] Optimizing the interaction scenario according to the experience data;

[0220] Selenium is a tool for automated testing of web applications, which allows testers to write test scripts to simulate user operations in a browser to verify the functionality and performance of web applications.

[0221] Appium is an open source test automation framework that uses the WebDriver protocol to drive iOS, Android, and Windows applications, making automated testing more efficient and flexible.

[0222] The way to conduct automated testing is to use tools such as Selenium or Appium to run the code of the interactive scene after generating the interactive scene, use various possible user operations and scenarios, and record the loading speed of the interactive scene, the quality and smoothness of the interactive scene, and the reflection effect of each user operation as the test results.

[0223] The method for optimizing the interaction scene is to analyze the test results. When there are problems such as unsmooth loading of the interaction scene, poor image quality, or poor response to user operations in the test results, the corresponding code position is located, and the problems in the test results are improved by modifying the parameter values ​​in the code.

[0224] New Relic is a company that focuses on providing solutions such as application performance management (APM), infrastructure monitoring, and digital experience monitoring, and is committed to helping enterprises monitor and optimize the performance of their software stacks.

[0225] Dynatrace is a company that provides a digital intelligence platform, focusing on providing comprehensive monitoring, analysis and optimization solutions for complex enterprise IT environments.

[0226] The performance indicators of interactive scenarios can be monitored in real time by using New Relic or Dynatrace to monitor the application running process and calculate the performance indicators during the running process, such as the frame rate of the interactive screen, loading time, and memory usage of the application, and use the values ​​of each performance indicator in the calculation results as monitoring data.

[0227] The performance of the interactive scenario can be optimized by obtaining the values ​​of each performance indicator in the monitoring data, and judging whether there are performance indicators in the monitoring data that do not meet the standards based on the requirements for the performance indicators of the interactive scenario. If so, the code is located and repaired to improve the unqualified performance indicators of the interactive scenario.

[0228] UserTesting is a world-leading online user research and testing platform that provides companies with valuable opportunities to gain in-depth understanding of user behavior and obtain user feedback.

[0229] Hotjar is a powerful website behavior analysis tool that provides an all-in-one solution for collecting various information from website information and optimizing it accordingly.

[0230] The user experience data can be collected by issuing experience tests to users who have used the interactive scenarios through UserTesting or Hotjar, and collecting the user's answers to the experience tests as experience data.

[0231] The interaction scenario may be optimized by collecting statistics on the experience data and improving the issues with the most feedback. For example, if the design of some interactive interfaces reported by users in the experience data is not intuitive enough, the user experience may be improved by adjusting the interface layout and interaction logic.

[0232] S706: receiving an interactive operation issued by a user in the interactive scene during displaying the interactive scene;

[0233] S707: Identify the interactive object element corresponding to the interactive operation, and generate a dynamic effect of the interactive object element in the interactive scene according to the interactive operation.

[0234] The benefit of this solution is that it can comprehensively detect problems in interactive scenarios through automatic testing, performance indicator monitoring, and user experience feedback, and make active and effective improvements to the problems, thereby optimizing the interactive scenarios and better meeting user expectations.

[0235] Based on the above solution, optionally, after optimizing the interaction scenario, the method further includes:

[0236] Use AWS Elastic Beanstalk or Google App Engine to deploy the optimized interaction scenarios in the cloud;

[0237] and / or,

[0238] Use Docker to package application services and deploy them to the Kubernetes cluster to perform containerized deployment of optimized interaction scenarios.

[0239] and / or,

[0240] Use Jenkins or GitLab CI / CD to build test and deployment pipelines to continuously integrate and deploy optimized interaction scenarios.

[0241] AWS Elastic Beanstalk is a service designed to simplify the process of deploying, running, and managing scalable web applications on AWS.

[0242] Google App Engine, also known as Google Application Engine, is a cloud computing platform for developing and hosting web applications, using data centers managed by Google to provide services.

[0243] The optimized interactive scene can be deployed in the cloud by using AWS Elastic Beanstalk or Google App Engine to deploy the application containing the optimized interactive scene on a cloud server, so that users can access and use the interactive scene through the Internet.

[0244] Docker is an open source application container engine that allows developers to package their applications and dependent packages into a portable container and then publish it to any popular Linux machine, and can also achieve virtualization.

[0245] Kubernetes is an open source container orchestration system for automating the deployment, scaling, and management of containerized applications.

[0246] The optimized interactive scene can be deployed in a containerized manner by isolating the application in which the interactive scene is located from its operating environment to form an independent, portable, and standardized software package. This software package is called a container, which contains all necessary components such as the application code, runtime environment, library files, and configuration files. Through containerized deployment, applications can be run quickly and consistently on different hardware, operating systems, and environments.

[0247] Jenkins is an open source automation server tool that is mainly used to build, test and deploy software projects. As a core tool for continuous integration and continuous delivery, it plays an important role in the software development process.

[0248] GitLab CI / CD is a powerful feature provided by the GitLab platform, which aims to improve the efficiency of the development team and the quality of software releases by automating the build, test, and deployment processes.

[0249] The way to continuously integrate and continuously deploy the optimized interaction scenarios is that developers can frequently merge the code changes of the interaction scenarios into the main branch or shared code repository, and verify these changes through automated build and test processes. Going further on the basis of continuous integration, the code built and tested through continuous integration will be automatically deployed to the production environment or other operating environment. This means that every time the code changes, as long as it passes the automated test, the application where the interaction scenario is located will be automatically released to users.

[0250] The benefit of this solution is that it can achieve multi-platform release of interactive scenarios through cloud deployment, containerized deployment, and continuous deployment, and maintain the stability and availability of the application after it is launched, thereby improving the user experience.

[0251] Embodiment 7

[0252] Figure 8 It is a structural diagram of a dynamic response device for interactive object elements in an interactive scene provided in Example 7 of the present application.

[0253] like Figure 8 As shown, specifically including the following:

[0254] The survey data collection module 801 is used to collect survey data; wherein the survey data includes: at least one of user preference data, behavior data, environment data and historical data;

[0255] A scenario type determination module 802 is used to analyze the survey data and determine the scenario type of the interactive scenario to be generated;

[0256] A scene element generation module 803, used to input the scene type into the AI ​​model, and generate scene elements in the interactive scene through the AI ​​model;

[0257] An interactive scene acquisition module 804 is used to apply the scene elements to the interactive platform for rendering to obtain an interactive scene;

[0258] An interactive operation receiving module 805 is used to receive an interactive operation issued by a user in the interactive scene during the process of displaying the interactive scene;

[0259] The dynamic effect generation module 806 is used to identify the interactive object element corresponding to the interactive operation, and generate a dynamic effect of the interactive object element in the interactive scene according to the interactive operation.

[0260] In an embodiment of the present application, a survey data collection module is used to collect survey data; wherein the survey data includes: at least one of user preference data, behavior data, environmental data and historical data; a scene type determination module is used to analyze the survey data and determine the scene type of the interactive scene to be generated; a scene element generation module is used to input the scene type into the AI ​​model and generate scene elements in the interactive scene through the AI ​​model; an interactive scene acquisition module is used to apply the scene elements to the interactive platform for rendering to obtain an interactive scene; an interactive operation receiving module is used to receive the interactive operation issued by the user in the interactive scene during the display of the interactive scene; a dynamic effect generation module is used to identify the interactive object element corresponding to the interactive operation, and generate the dynamic effect of the interactive object element in the interactive scene according to the interactive operation. Through the above-mentioned method of dynamic response of interactive object elements in an interactive scene, an interactive scene can be generated according to the survey data, and corresponding dynamic effects can be generated for the user's interactive operation, enriching the content of the interactive scene, which is conducive to improving the interactivity and immersion of the interactive scene.

[0261] In an embodiment of the present application, a dynamic response device of an interactive object element in an interactive scene can be a device, or a component, integrated circuit, or chip in a terminal. The device can be a mobile electronic device or a non-mobile electronic device. Exemplarily, the mobile electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, a wearable device, an ultra-mobile personal computer (UMPC), a netbook, or a personal digital assistant (PDA), etc., and the non-mobile electronic device can be a server, a network attached storage (NAS), a personal computer (PC), a television (TV), a teller machine or a self-service machine, etc., which is not specifically limited in the embodiment of the present application.

[0262] In an embodiment of the present application, a device for dynamically responding to an interactive object element in an interactive scene may be a device having an operating system. The operating system may be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0263] The device for dynamic response of interactive object elements in an interactive scene provided in an embodiment of the present application can implement the various processes implemented in the above-mentioned method embodiments. To avoid repetition, they will not be described here.

[0264] Embodiment 8

[0265] like Fig. 9 As shown, an embodiment of the present application also provides an electronic device 900, including a processor 901, a memory 902, and a program or instruction stored in the memory 902 and executable on the processor 901. When the program or instruction is executed by the processor 901, each process of an embodiment of a method for dynamic response of interactive object elements in the above-mentioned interactive scene is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described here.

[0266] It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0267] Embodiment 9

[0268] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, each process of an embodiment of a method for dynamic response of an interactive object element in the above-mentioned interactive scene is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0269] The processor is a processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0270] Embodiment 10

[0271] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the method embodiment of the dynamic response of interactive object elements in the above-mentioned interactive scene, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0272] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0273] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0274] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0275] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

[0276] The above are only preferred embodiments of the present application and the technical principles used. The present application is not limited to the specific embodiments described herein, and various obvious changes, readjustments and substitutions that can be made by those skilled in the art will not deviate from the scope of protection of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the claims.

Claims

1. A dynamic response method for interactive object elements in an interactive scene, characterized in that: The method comprises: Collecting survey data; wherein the survey data includes: at least one of user preference data, behavior data, environment data and historical data; Analyze the survey data to determine the scene type of the interactive scene that needs to be generated; Inputting the scene type into the AI ​​model, and generating scene elements in the interactive scene through the AI ​​model; Applying the scene elements to the interactive platform for rendering to obtain an interactive scene; In the process of displaying the interactive scene, receiving an interactive operation issued by a user in the interactive scene; An interactive object element corresponding to the interactive operation is identified, and a dynamic effect of the interactive object element in the interactive scene is generated according to the interactive operation.

2. The dynamic response method of interactive object elements in an interactive scene according to claim 1, characterized in that: The scene elements in the interactive scene are generated by the AI ​​model, including: Use TensorFlow and Keras to build an adversarial network, and generate scene elements in the interactive scene through the adversarial network; and / or, The existing scene element model is obtained through big data, and transfer learning is performed using PyTorch and Hugging Face Transformers. The scene elements in the interactive scene are generated according to the existing scene element model.

3. The dynamic response method of interactive object elements in an interactive scene according to claim 1, characterized in that: Applying the scene elements to the interactive platform for rendering includes: Using Unity 3D or Unreal Engine to render the scene elements in real time; and / or, Identify common elements among the scene elements, pre-render and cache them using Blender or Maya, and when the common elements are included in the user interface, load the pre-cached common elements that have been pre-rendered; and / or, Use AWS Gamelift or Google Cloud Gaming Solutions to render scene elements on cloud servers.

4. The dynamic response method of interactive object elements in an interactive scene according to claim 1, characterized in that: Receiving an interactive operation issued by a user in the interactive scenario, including: Use Google Dialogflow or Amazon Lex to receive user voice commands as user interaction operations; and / or, Use Leap Motion or Microsoft Kinect to capture the user's gestures as user interaction operations; and / or, Use the Unity Touch API or ARKit / ARCore to obtain the user's touch operations on the mobile device as the user's interactive operations.

5. The method for dynamic response of interactive object elements in an interactive scene according to claim 1, characterized in that: After generating scene elements in the interactive scene by using the AI ​​model, the method further includes: Using Firebase Realtime Database or AWS Lambda to collect user feedback information, and adjusting scene elements in the interactive scene according to the feedback information; and / or, Analyze the user's behavior data through Google BigQuery ML or Amazon Personalize, and adjust the scene elements in the interaction scene when the analysis results meet the preset conditions; and / or, When the user triggers a scene switch, an interactive scene after the switch is generated according to the scene element triggered by the user, and scene elements in the interactive scene after the switch are generated.

6. The method for dynamic response of interactive object elements in an interactive scene according to claim 1, characterized in that: After applying the scene elements to the interactive platform for rendering to obtain the interactive scene, the method further includes: Use Selenium or Appium to perform automated testing and obtain test results; Optimizing the interaction scenario according to the test results; and / or Use New Relic or Dynatrace to monitor the performance indicators of the interaction scenario in real time to obtain monitoring data; Optimizing the performance of the interaction scenario according to the monitoring data; and / or, Conduct user testing using UserTesting or Hotjar to collect user experience data; The interaction scenario is optimized according to the experience data.

7. The method for dynamic response of interactive object elements in an interactive scene according to claim 1, characterized in that: In the case where the survey data includes the environment data, analyzing the survey data to determine the scene type of the interaction scene to be generated includes: Extracting environmental data from the survey data, and obtaining weather data for the user's area based on the environmental data; The weather data is analyzed, and when the weather data indicates a rainy day, it is determined that the scene type of the interactive scene to be generated is an indoor scene type.

8. A dynamic response device for interactive object elements in an interactive scene, characterized in that: The device comprises: A survey data collection module, used to collect survey data; wherein the survey data includes: at least one of user preference data, behavior data, environment data and historical data; A scenario type determination module, used to analyze the survey data and determine the scenario type of the interactive scenario to be generated; A scene element generation module, used to input the scene type into the AI ​​model, and generate scene elements in the interactive scene through the AI ​​model; An interactive scene acquisition module, used to apply the scene elements to the interactive platform for rendering to obtain an interactive scene; An interactive operation receiving module, used to receive an interactive operation issued by a user in the interactive scene during the process of displaying the interactive scene; The dynamic effect generation module is used to identify the interactive object element corresponding to the interactive operation and generate a dynamic effect of the interactive object element in the interactive scene according to the interactive operation.

9. An electronic device, characterized in that: It includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of a method for dynamic response of interactive object elements in an interactive scene as described in any one of claims 1 to 7.

10. A readable storage medium, characterized in that: The readable storage medium stores a program or instruction, and when the program or instruction is executed by the processor, the steps of a method for dynamic response of an interactive object element in an interactive scene as described in any one of claims 1-7 are implemented.

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