An immersive decryption exploration and game-based learning system for cultural inheritance of opera helmet culture

Abstract

The application relates to the technical field of virtual reality application, and specifically discloses an immersive decryption exploration and gamified learning system for opera helmet culture inheritance. The system comprises a data processing layer, a front-end interaction layer and a functional module layer; the data processing layer establishes a knowledge graph database comprising a four-dimensional correlation network of shape-process-roles-patterns; the front-end interaction layer is constructed based on a three-dimensional rendering engine and a responsive layout engine; and the functional module layer comprises popular science education, immersive game, individualized customization and social sharing modules. The popular science education module provides a three-dimensional museum and process simulation; the immersive game module realizes gamified learning through plot driving and clue solving; the individualized customization module supports classic style replication and self-selected creation; and the social sharing module provides AR try-on and community interaction. The system solves the problems of fragmented knowledge dissemination and passive inheritance mode, and realizes the combination of teaching and entertainment and the active inheritance of culture.

Description

Technical Field

[0001] This invention belongs to the field of virtual reality application technology, specifically relating to a system for the inheritance of opera headdress culture based on immersive decryption exploration and gamified learning. Background Technology

[0002] As an important material carrier of traditional Chinese opera culture, opera headdresses are facing a historic turning point in the digital age. The craftsmanship of traditional opera headdresses embodies hundreds of years of artisan wisdom. From pattern making and shaping to applying powder and foil, from kingfisher feather inlay to final assembly, each step contains unique cultural codes and the essence of craftsmanship. However, current technological approaches in the field of digital cultural heritage preservation have not truly addressed the core needs of protecting this intangible cultural heritage.

[0003] Existing digital technologies often present helmet culture as static images or 3D models. This superficial approach to digital acquisition is limited by the two-dimensional display of a screen and the passive viewing posture of the user. Consequently, the user's understanding remains at the level of visual browsing, failing to delve into the internal structural logic and craftsmanship of the helmet. More importantly, traditional digital displays lack interactive mechanisms to transform knowledge into experience. Users cannot perceive the assembly relationships between different components through hands-on operation, nor can they appreciate the exquisite craftsmanship by simulating the production process.

[0004] This disconnect between knowledge transfer and experience directly creates a deep-seated dilemma in the effectiveness of cultural transmission. When users can only view images or 3D models of helmets from an outsider's perspective, their understanding of helmet culture remains at the level of "watching" rather than "participating," leading to difficulty in maintaining learning interest, deepening knowledge retention, and truly establishing cultural emotions. Ultimately, this creates an efficiency bottleneck in cultural transmission in the digital age that urgently needs to be overcome. Summary of the Invention

[0005] This application provides an immersive, gamified learning system for the inheritance of opera headdress culture, aiming to solve, or at least partially solve, the problems of fragmented knowledge dissemination, monotonous experience, and passive inheritance methods in the existing technology.

[0006] The first aspect of this application provides an immersive, decryption-based exploration and gamified learning system for the inheritance of opera headdress culture, including: The data processing layer is used to establish and maintain a knowledge graph database of helmet culture. The knowledge graph database contains helmet shape classification data, helmet production process data, correspondence data between roles and helmets, and symbolic meaning data of patterns. The data processing layer uses a knowledge graph construction engine to perform multi-dimensional correlation modeling on the data, forming a four-dimensional correlation network of shape-process-pattern-color, and provides knowledge query interface and knowledge recommendation interface to the outside world. The front-end interaction layer is used to present the user interface and collect user operation commands. The front-end interaction layer is built on a 3D rendering engine and a responsive layout engine, supports cross-platform operation and adapts to different display terminals. The functional module layer includes a science education module, an immersive game module, a personalized customization module, and a social sharing module; the functional module layer exchanges data bidirectionally with the data processing layer through a standard data interface to realize the collection, storage, and synchronization of user behavior data.

[0007] In one optional implementation, the science education module includes a 3D museum sub-module and a process simulation sub-module; The 3D Museum submodule is used to build a 3D model library of classic helmets through the 3D modeling unit, and present the 3D models to the user in a surround display manner through the rendering unit; the 3D Museum submodule further provides a model disassembly function, allowing users to perform layered disassembly operations on the target helmet model, and display the name, function label and cultural meaning of each disassembled part. The process simulation submodule is used to demonstrate the entire process of helmet making step by step through the step guidance unit, including the demonstration of the pattern making process, the powdering process, the foil application process, and the kingfisher feather inlay process. The process simulation submodule further provides interactive operation functions, allowing users to simulate key production steps by dragging and dropping, and the system feedback unit judges the accuracy of the user's operation in real time and provides correction prompts.

[0008] In one optional implementation, the immersive game module includes a plot-driven submodule and a clue-solving submodule; The story-driven submodule is used to create a virtual apprentice character when a user visits for the first time, and to set up multi-level progressive level tasks with a virtual stage as the background; each level task includes tasks such as helmet return, parts assembly, and character matching; users can only unlock subsequent level tasks after completing the current level task. The clue-solving submodule is used to randomly distribute interactive clue points in the virtual stage scene. When a user triggers a clue point, a knowledge question and answer associated with that clue point is triggered. Only after the user solves the puzzle correctly can the level progress be advanced. At the same time, the system updates the knowledge nodes involved in the puzzle-solving process to the user's personal learning profile.

[0009] In one optional implementation, the personalization module includes a classic style replication sub-module and a self-selected creation sub-module; The classic style replication submodule is used to load preset classic helmet style templates and provide users with main pattern replacement interface, secondary pattern replacement interface and color configuration interface; after the user adjusts the parameters through each interface, the 3D model generation unit generates the corresponding 3D preview model in real time. The self-selection creation submodule provides a component library selection interface, listing available helmet body components, visor components, helmet top components, and rear pocket components for users to freely combine. After the user completes the component combination, the combination rationality detection unit performs rule verification on the combination. When a combination that does not conform to the wearing rules is detected, the system automatically prompts the user and prohibits the generation of a preview model. When the combination passes the verification, the 3D model generation unit generates a unique 3D creation model and generates a digital certificate for the model.

[0010] In one optional implementation, the social sharing module includes an augmented reality try-on sub-module, a peripheral customization sub-module, and a community interaction sub-module; The augmented reality try-on submodule is used to call the camera of the mobile device to obtain real-time images, overlay the 3D model of the helmet selected by the user onto the specified position of the camera image, generate an augmented reality try-on image, and support the user to take photos or record videos for saving. The peripheral customization submodule is used to receive customization orders submitted by users. The order parameters include 3D model specifications, peripheral product type parameters, and material parameters. The system generates a customized preview image based on the order parameters. After the user confirms the image, the order payment is completed and the system enters the production process. The community interaction submodule provides functions for displaying user profiles, showcasing personal works, and participating in social activities. The profile displays a list of completed levels, unlockable helmet types, learning time statistics, and achievement badge collection records. The community interaction submodule further provides entry points for periodic design competitions and knowledge quizzes, allowing users to submit entries or participate in quizzes and receive votes and comments from other users.

[0011] In one optional implementation, the construction process of the knowledge graph database includes: The raw data collection step is used to collect raw headgear data from sources such as interview records with intangible cultural heritage inheritors, archives of cultural relics, and classics on traditional opera costume techniques. The entity extraction step is used to extract helmet entities, component entities, process entities, character entities, and pattern entities from the original data, and assign a unique identifier to each entity; The relationship establishment step is used to analyze the semantic associations between entities, establish relationship edges between entities, and store them in the relational database. The knowledge reasoning step is used to perform transitive reasoning based on the established relation edges, generate implicit associations, and supplement the knowledge graph database.

[0012] In one optional implementation, the data processing layer further implements intelligent knowledge recommendation functionality through a knowledge recommendation engine; the knowledge recommendation engine obtains the user's recent browsing history, recently completed level records, and current learning progress, retrieves extended knowledge nodes related to the user's current knowledge points from the knowledge graph database through an association analysis algorithm, and pushes the retrieval results to the prompt area of ​​the front-end interaction layer.

[0013] In one optional implementation, the immersive game module is further configured with an achievement system; the achievement system records various achievement conditions achieved by the user during the learning process, including first completion of a level achievement, cumulative learning time achievement, and creation of works that have been liked by other users reaching a set threshold achievement; when a user's achievement condition is triggered, the system automatically unlocks the corresponding achievement badge and displays the badge in the honor display area of ​​the user's personal homepage.

[0014] In one optional implementation, the 3D model generation unit of the personalized customization module adopts a 3D model generation algorithm based on parametric modeling. The algorithm first calls the corresponding part model template according to the part type selected by the user, then maps the pattern to the specified area of ​​the part model according to the pattern parameters configured by the user, and finally applies a shader to perform color rendering according to the color parameters specified by the user to generate the final 3D creation model.

[0015] In one optional implementation, the system further includes an operations management backend module; the operations management backend module is used by administrators to incrementally update knowledge graph data, adjust game level configurations, perform statistical analysis of user data, and manage the uploading and delisting of community activities.

[0016] In the immersive exploration and gamified learning system for the inheritance of opera headdress culture provided in this application, the data processing layer provides structured and systematic knowledge support for the functional module layer by establishing a knowledge graph database containing a four-dimensional relational network of form, craftsmanship, pattern, and color. The front-end interaction layer, based on a 3D rendering engine and a responsive layout engine, achieves a cross-platform immersive user experience. The popular science education module in the functional module layer solves the technical problem of fragmented traditional knowledge dissemination. Through the model decomposition function of the 3D museum sub-module and the step-by-step demonstration function of the craft simulation sub-module, users can systematically and deeply understand the headdress culture. The immersive game module transforms knowledge learning into active exploration behavior through the task progression mechanism of the plot-driven sub-module and the puzzle-solving mechanism of the clue-solving sub-module, effectively overcoming the technical defects of passive inheritance methods. The personalized customization module provides users with a complete technical path from knowledge cognition to creative practice through the classic style replication sub-module and the self-selected creation sub-module. The social sharing module constructs a complete technical closed loop from individual learning to social dissemination through the augmented reality try-on sub-module, peripheral customization sub-module, and community interaction sub-module.

[0017] Compared with existing technologies, the advantages and positive effects of this invention are as follows: The knowledge graph-driven system architecture constructed by this invention is the first to digitally store and present opera headdress culture in the form of a structured knowledge network, breaking through the technical limitations of traditional static display or one-way dissemination; through the organic integration of popular science education modules and immersive game modules, it achieves the technical effect of "edutainment," ensuring both the systematicness and accuracy of knowledge transmission and enhancing users' initiative and interest in learning; through the technical linkage of personalized customization modules and social sharing modules, it forms a complete user journey from knowledge acquisition to creative practice and then to social dissemination, effectively improving user stickiness and community activity; through the combination of augmented reality try-on technology and peripheral customized services, it provides a feasible technical solution for the organic derivation and commercial monetization of traditional opera culture, laying an economic foundation for the sustainable development of intangible cultural heritage; through the dual drive of technological innovation and model innovation, this invention provides a complete, replicable, and scalable digital solution for the living inheritance of traditional Chinese opera headdress culture. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the overall technical solution architecture of the immersive decryption exploration and gamified learning system for the inheritance of opera headdress culture proposed in this invention. Figure 2 This is a schematic diagram of the core principle framework of the knowledge graph database based on a four-dimensional association network of form, process, pattern, and color in this invention; Figure 3This is a schematic diagram of the logical flow framework of the integration of the popular science education module and the immersive game module in this invention to achieve "edutainment"; Figure 4 This is a schematic diagram of the technical closed-loop framework formed by the linkage between the personalized customization module and the social sharing module in this invention. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] In the accompanying drawings, the size of constituent elements, the thickness of layers, or areas may sometimes be exaggerated for clarity. Therefore, any implementation of this disclosure is not necessarily limited to the dimensions shown in the drawings, and the shapes and sizes of the components in the drawings do not reflect true proportions. Furthermore, the drawings schematically illustrate ideal examples, and any implementation of this disclosure is not limited to the shapes or values ​​shown in the drawings.

[0021] Reference Figure 1 , Figure 1 This is a schematic diagram of the overall technical architecture of an immersive decryption exploration and gamified learning system for the inheritance of opera headdress culture proposed in one embodiment of this application. As shown in the figure, the system includes: a data processing layer, a front-end interaction layer, a functional module layer, and an operation management back-end module.

[0022] The data processing layer is used to establish and maintain a knowledge graph database of helmet culture. The knowledge graph database contains helmet shape classification data, helmet production process data, correspondence data between roles and helmets, and symbolic meaning data of patterns. The data processing layer uses a knowledge graph construction engine to perform multi-dimensional correlation modeling on the data, forming a four-dimensional correlation network of shape-process-pattern-color, and provides knowledge query interface and knowledge recommendation interface to the outside world.

[0023] In this embodiment, within the immersive exploration and gamified learning system for the inheritance of opera headdress culture, the data processing layer serves as the core data support unit, responsible for establishing and maintaining a knowledge graph database of headdress culture. Specifically, the data processing layer, through a knowledge graph construction engine, collects, cleans, labels, and structures raw headdress data from sources such as interview records with intangible cultural heritage inheritors, archived cultural relics, and classic texts on traditional opera costume techniques. This results in a complete knowledge graph database containing headdress shape classification data, headdress manufacturing process data, data on the correspondence between roles and headdresses, and data on the symbolic meaning of patterns. Furthermore, the data processing layer utilizes a multi-dimensional association modeling algorithm within the knowledge graph construction engine to establish semantic relationships between shape, craftsmanship, color, and pattern dimensions, forming a four-dimensional association network. This network provides unified data access services to upper-layer applications through knowledge query and recommendation interfaces.

[0024] The front-end interaction layer is used to present the user interface and collect user operation commands. The front-end interaction layer is built on a 3D rendering engine and a responsive layout engine, supports cross-platform operation and adapts to different display terminals.

[0025] In this embodiment, the front-end interaction layer is the interface layer for user interaction with the system, implemented using a dual-engine architecture based on a 3D rendering engine and a responsive layout engine. Specifically, the 3D rendering engine is built based on graphics rendering technologies such as WebGL or OpenGL, and is responsible for real-time rendering and presentation of 3D model data provided by the data processing layer, supporting 3D visualization effects such as lighting calculation, material mapping, and perspective switching. The responsive layout engine is responsible for adaptive layout adjustments based on the user's screen size, resolution, and interaction method, ensuring that the system provides the best user interaction experience on different display terminals such as desktop computers, tablets, and smartphones. The front-end interaction layer collects user operation commands such as clicks, drags, and swipes through an event listening mechanism, and sends these operation commands to the functional module layer for processing through a standard data interface.

[0026] The functional module layer includes a science education module, an immersive game module, a personalized customization module, and a social sharing module; the functional module layer exchanges data bidirectionally with the data processing layer through a standard data interface to realize the collection, storage, and synchronization of user behavior data.

[0027] In this embodiment, the functional module layer is a collection of functional units that implement the core business functions of the system. These modules are decoupled through standard data interfaces and exchange data with the knowledge graph database through a unified data access interface provided by the data processing layer. Specifically, the science education module provides users with science education and knowledge dissemination services related to opera headdress culture; the immersive game module guides users to actively explore and learn about headdress culture through gamification; the personalized customization module supports users in designing and creating personalized headdress styles; and the social sharing module supports users in sharing their learning outcomes and creative works within the system. User behavior data generated during the operation of each functional module is synchronized in real-time to the data processing layer for storage and analysis via standard data interfaces, providing data support for the knowledge recommendation engine and the operation management backend module.

[0028] In one embodiment, this application also provides an immersive decryption exploration and gamified learning system for the inheritance of opera headdress culture. In this system, the popular science education module includes a three-dimensional museum sub-module and a craft simulation sub-module. The 3D Museum submodule is used to build a 3D model library of classic helmets through the 3D modeling unit, and present the 3D models to the user in a surround display manner through the rendering unit; the 3D Museum submodule further provides a model disassembly function, allowing users to perform layered disassembly operations on the target helmet model, and display the name, function label and cultural meaning of each disassembled part. The process simulation submodule is used to demonstrate the entire process of helmet making step by step through the step guidance unit, including the demonstration of the mold making process, the powder application process, the foil application process, and the kingfisher feather inlay process; the process simulation submodule further provides interactive operation functions, allowing users to simulate key production steps by dragging and dropping, and the system feedback unit judges the accuracy of the user's operation in real time and provides correction prompts.

[0029] In this embodiment, the popular science education module is the core functional module of the system for disseminating knowledge about opera headdress culture to users. It mainly includes two sub-functional units: the 3D museum sub-module and the craft simulation sub-module.

[0030] The implementation process of the 3D Museum submodule is as follows: First, the 3D modeling unit performs 3D scanning or manual modeling of classic opera helmets to build a 3D model library of classic helmets. Then, the rendering unit presents the 3D models from the library to the user in a surround display manner. Users can control the camera's rotation angle by dragging with the mouse or swiping on the touchscreen, achieving 360-degree observation without blind spots. The 3D Museum submodule further provides a model disassembly function. After the user clicks on the target helmet model, the system will automatically enter disassembly mode, displaying the helmet's layered structure. Each disassembled component includes, but is not limited to, the helmet body, brim, top, faceplate, and back pocket. After disassembly, each component simultaneously displays its name, function description, and cultural significance. For example, for the Seven Stars forehead project, the disassembled pom-pom component is labeled "pom-pom," its function description is "a decorative component located on the upper part of the forehead and sides, used to display the character's status and personality," and its cultural significance is "seven evenly arranged colored pom-poms symbolize the Big Dipper, with the largest one in the center representing Kui Xing, signifying both wisdom and courage."

[0031] The process simulation submodule is implemented as follows: The step guidance unit pre-records or animates the entire process flow of helmet making, including four main processes: pattern making, powder application, foil application, and kingfisher feather inlay. Each process contains several sub-steps, such as the yarn-insertion process, which includes sub-steps such as glue preparation, cutting and positioning, soaking and hammering. The process simulation submodule further provides interactive operation functions, allowing users to simulate the execution of key production steps through drag-and-drop operations. For example, when a user drags a virtual paintbrush to paint the body, the system uses a step judgment algorithm to analyze in real time whether the user's operation trajectory and operation force conform to the standard process flow. If it is determined to be unqualified, the system feedback unit will provide specific correction prompts, such as "Please keep the horizontal direction of the paint evenly applied" or "The coating thickness is insufficient, please increase the number of coats."

[0032] In one embodiment, this application also provides an immersive puzzle-solving and gamified learning system for the inheritance of opera headdress culture. In this system, the immersive game module includes a plot-driven sub-module and a clue-solving sub-module. The story-driven submodule is used to create a virtual apprentice character when a user visits for the first time, and to set up multi-level progressive level tasks with a virtual stage as the background; each level task includes tasks such as helmet return task, component assembly task, and character matching task; users can only unlock subsequent level tasks after completing the current level task. The clue-solving submodule is used to randomly distribute interactive clue points in the virtual stage scene. When a user triggers a clue point, a knowledge puzzle associated with that clue point is triggered. Only after the user correctly solves the puzzle can the level progress be advanced. At the same time, the system updates the knowledge nodes involved in the puzzle-solving process to the user's personal learning profile.

[0033] In this embodiment, the immersive game module is the core functional module that guides users to actively explore and learn about helmet culture through gamification design. It mainly includes two sub-functional units: the plot-driven sub-module and the clue-solving sub-module.

[0034] The implementation process of the plot-driven submodule is as follows: When a user visits the system for the first time, they create a virtual apprentice character through a character creation wizard, including selecting the virtual apprentice's gender, appearance, initial equipment, and other attributes. After the virtual apprentice character is created, the system automatically enters the main game interface with a virtual stage as the background and sets up several levels of level tasks according to the principle of progressive difficulty. The types of level tasks include: the first type is the helmet placement task, which requires the user to select the correct helmet from several options based on the given theatrical character name and place it in its correct position; the second type is the component assembly task, which requires the user to select each component correctly based on text and graphic prompts; the third type is the character matching task, which requires the user to determine the theatrical character category corresponding to the given helmet sample. Each level task contains several independent task items, and the user must complete all task items in the current level to unlock the next level task.

[0035] The implementation process of the clue-solving submodule is as follows: During the game's progression, the system randomly distributes several interactive clue points in the virtual stage scene. These clue points are presented in various forms, including glowing icons and special textured areas. When the user's virtual apprentice character touches a clue point, the system triggers a knowledge-based question or pattern puzzle related to that clue point. For knowledge-based question-and-answer type clue points, the system randomly selects knowledge-based questions related to the current level from the knowledge graph database, such as "Which of the following helmets is suitable for the role of Bai Suzhen in the Peking Opera 'The Legend of the White Snake'?" If the user selects the correct answer, the puzzle is solved successfully. For component assembly type clue points, the system breaks down a complete helmet into its components and arranges them randomly. The user drags and drops the components to their correct positions to assemble them. After the user solves the puzzle correctly, the system calculates and awards reward points based on the level's progress, and simultaneously updates the knowledge nodes involved in the puzzle-solving process to the user's personal learning profile, forming a learning history record.

[0036] In one embodiment, this application also provides an immersive decryption exploration and gamified learning system for the inheritance of opera headdress culture. In this system, the personalized customization module includes a classic style replication sub-module and a self-selected creation sub-module. The classic style replication submodule is used to load preset classic helmet style templates and provide users with main pattern replacement interface, secondary pattern replacement interface and color configuration interface; after the user adjusts the parameters through each interface, the 3D model generation unit generates the corresponding 3D preview model in real time. The self-selection creation submodule provides a component library selection interface, listing available helmet body components, visor components, helmet top components, and back pocket components for users to freely combine. After the user completes the component combination, the combination rationality detection unit performs rule verification on the combination. When a combination that does not comply with the wearing rules is detected, the system automatically prompts the user and prohibits the generation of a preview model. When the combination passes the verification, the 3D model generation unit generates a unique 3D creation model and generates a digital certificate for the model.

[0037] In this embodiment, the personalized customization module is the core functional module that supports users in designing and creating personalized helmet styles. It mainly includes two sub-functional units: the classic style replication sub-module and the self-selection creation sub-module.

[0038] The implementation process of the classic style replication submodule is as follows: The system pre-sets several classic helmet style templates, such as the Overlord Helmet, Phoenix Crown, and Commander Helmet. Each template defines the basic component composition, main pattern area, secondary pattern area, and default color configuration. After the user selects a classic style template, the system loads the 3D model data of the template and provides several optional main pattern patterns for the user to choose and replace through the main pattern replacement interface, several optional secondary pattern patterns for the user to choose and replace through the secondary pattern replacement interface, and optional color schemes for the user to choose and adjust through the color configuration interface. After the user completes the parameter adjustment of each interface, the 3D model generation unit generates the corresponding 3D preview model in real time according to the parameters configured by the user. The user can rotate, scale, and interact with the generated 3D model in the preview interface.

[0039] The implementation process of the self-selection creation submodule is as follows: The system provides a component library selection interface, listing available helmet body components (e.g., flat helmets, pointed helmets, round helmets, etc.), bridle components (e.g., wide bridles, narrow bridles, wavy bridles, etc.), helmet top components (e.g., pagoda-shaped, flame-shaped, pom-pom-shaped, etc.), and back pocket components (e.g., square, round, draped, etc.) for users to freely choose and combine. After the user selects specific components from each component category, a complete component combination scheme is formed. The combination rationality detection unit performs wearing rule verification on the combination. The verification rules include: component size matching rules (checking whether the interface sizes of each component are compatible), component style consistency rules (checking whether the style elements of each component are coordinated), and role applicability rules (checking whether the combination conforms to the wearing specifications of a specific role). If a combination item that does not conform to the wearing rules is detected, the system automatically pops up a prompt message to inform the user of the specific rule conflict and prohibits the generation of a preview model. Only when the combination passes all rule verifications will the 3D model generation unit generate an exclusive 3D creation model, and at the same time, generate a unique digital certificate for the model based on blockchain and other technologies for ownership confirmation and traceability.

[0040] In one embodiment, this application also provides an immersive decryption exploration and gamified learning system for the inheritance of opera headdress culture. In this system, the social sharing module includes an augmented reality try-on sub-module, a peripheral customization sub-module, and a community interaction sub-module. The augmented reality try-on submodule is used to call the camera of the mobile device to obtain real-time images, overlay the 3D model of the helmet selected by the user onto the specified position of the camera image, generate an augmented reality try-on image, and support the user to take photos or record videos for saving. The peripheral customization submodule is used to receive customization orders submitted by users. The order parameters include 3D model specifications, peripheral product type parameters, and material parameters. The system generates a customized preview image based on the order parameters. After the user confirms the image, the order payment is completed and the system enters the production process. The community interaction submodule provides functions for displaying user profiles, showcasing personal works, and participating in social activities. The profile displays a list of completed levels, unlockable helmet types, learning time statistics, and achievement badge collection records. The community interaction submodule further provides entry points for periodic design competitions and knowledge quizzes, allowing users to submit entries or participate in quizzes and receive votes and comments from other users.

[0041] In this embodiment, the social sharing module is the core functional module that supports users in social interaction and content dissemination. It mainly includes three sub-functional units: augmented reality try-on sub-module, peripheral customization sub-module, and community interaction sub-module.

[0042] The implementation process of the augmented reality try-on submodule is as follows: When a user accesses the system through a mobile device, the augmented reality try-on submodule calls the mobile device's camera to capture real-time footage; the user selects the helmet style they wish to try on from the helmet model list provided by the system, and the system overlays the selected helmet 3D model onto the designated position in the camera image, i.e., the area above the user's face, using an augmented reality rendering engine; the wearing position of the helmet model is determined through facial recognition algorithms or manual markers to ensure a realistic and natural visual effect; the user can take photos or record videos in the augmented reality try-on interface and share the generated images or videos to social media platforms.

[0043] The implementation process of the peripheral customization sub-module is as follows: When a user expresses a desire to customize a helmet model, they can submit a customization order through the peripheral customization sub-module. The order parameters include: 3D model specifications (e.g., model accuracy level, file format requirements), peripheral product type parameters (e.g., keychains, refrigerator magnets, bookmarks, T-shirts, etc.), and material parameters (e.g., metal, plastic, paper, cotton, linen, etc.). The system generates a customized preview image based on the order parameters submitted by the user, showcasing the actual appearance and size of the peripheral product. After the user confirms the preview and completes online payment, the order enters the production process, and the system sends the 3D model data and related parameters to the production management system for manufacturing.

[0044] The implementation process of the community interaction submodule is as follows: The system generates a personal homepage for each registered user, displaying content including a list of completed levels (recording the levels the user has completed in the immersive game module), unlockable helmet types (recording the helmet types that the user can unlock at their current level), learning time statistics (statistics on the user's cumulative learning time in the system), and achievement badge collection records (a list of badges obtained in the achievement system). The community interaction submodule regularly holds design competitions, where users can submit their own helmet designs for evaluation, and other users can vote and comment on the entries. Simultaneously, the community interaction submodule regularly holds knowledge quizzes, where users can participate after logging in. The system calculates scores based on the accuracy of answers and publishes rankings after the event.

[0045] In one embodiment, this application also provides an immersive decryption exploration and gamified learning system for the inheritance of opera headdress culture. In this system, the construction process of the knowledge graph database includes: The raw data collection step is used to collect raw headgear data from sources such as interview records with intangible cultural heritage inheritors, archives of cultural relics, and classics on traditional opera costume techniques. The entity extraction step is used to extract helmet entities, component entities, process entities, character entities, and pattern entities from the original data, and assign a unique identifier to each entity; The relationship establishment step is used to analyze the semantic associations between entities, establish relationship edges between entities, and store them in the relational database. The knowledge reasoning step is used to perform transitive reasoning based on the established relation edges, generate implicit associations, and supplement the knowledge graph database.

[0046] In this embodiment, the construction of the knowledge graph database is one of the core functions of the data processing layer, and it is completed using a multi-stage pipeline approach. Specifically: In the raw data acquisition step, the system collects raw headdress data from multiple sources using a data acquisition engine. These sources include: oral records of headdress-making techniques from intangible cultural heritage inheritors via video interviews; images and descriptions of headdress artifacts extracted from museum archives using image recognition technology; and textual records of process procedures and standards extracted from traditional opera costume technique classics using text parsing technology. The collected raw data undergoes preprocessing operations such as cleaning, noise reduction, and standardization before being stored in the raw data storage area.

[0047] In the entity extraction step, the system automatically extracts various entities from the raw data using a named entity recognition algorithm, including: helmet entities (such as "Overlord Helmet", "Phoenix Crown", etc.), component entities (such as "Helmet Body", "Helmet Brim", "Helmet Top", etc.), craft entities (such as "Bullet Pattern", "Powdered Surface", "Foil Applying", etc.), role entities (such as "Sheng Jiao", "Dan Jiao", "Jing Jiao", etc.), and pattern entities (such as "Cloud Pattern", "Phoenix Pattern", "Peony Pattern", etc.). Each extracted entity is automatically assigned a unique identifier ID by the system for subsequent association calculations.

[0048] In the relationship establishment step, the system analyzes the semantic associations between entities using semantic analysis algorithms, establishes relationship edges between entities, and stores them in the relational database. The types of relationships between entities include: subordinate relationships (e.g., "pom-pom belongs to the general's helmet"), process relationships (e.g., "after applying red clay, powder is applied"), correspondence relationships (e.g., "the general's helmet corresponds to a female role"), and symbolic relationships (e.g., "dragon patterns symbolize power," etc.). Each relationship edge records the source entity ID, target entity ID, relationship type, and confidence score.

[0049] In the knowledge reasoning step, the system performs transitive reasoning based on established relational edges, generating implicit associations and supplementing the knowledge graph database. For example, given that "A belongs to B" and "B corresponds to C," the system can reason to the conclusion that "A corresponds to C." Similarly, given that "Process A must be performed before Process B," the system can generate implicit process sequence constraints. The relationships generated through reasoning are also stored in the relational database, continuously enriching the coverage of the knowledge graph.

[0050] In one embodiment, this application also provides an immersive decryption exploration and gamified learning system for the inheritance of opera headdress culture. In this system, the data processing layer also implements intelligent knowledge recommendation function through a knowledge recommendation engine. The knowledge recommendation engine obtains the user's recent browsing history, recently completed level records, and current learning progress, retrieves extended knowledge nodes related to the user's current knowledge points from the knowledge graph database through an association analysis algorithm, and pushes the retrieval results to the prompt area of ​​the front-end interaction layer.

[0051] In this embodiment, the knowledge recommendation engine is an intelligent knowledge recommendation function module provided by the data processing layer. The implementation process is as follows: The knowledge recommendation engine continuously collects and updates the user's recent browsing records (including viewed helmet model pages, process teaching videos, etc.), recently completed level records (level numbers and task types passed), and current learning progress (current level and learning chapter) through user behavior logs; the knowledge recommendation engine analyzes the degree of association between the user's current knowledge point and other knowledge nodes in the knowledge graph database through association analysis algorithms, and the retrieval algorithm comprehensively considers the semantic distance, co-occurrence frequency, and user interest matching degree between knowledge nodes, and selects extended knowledge nodes that are highly related to the user's current knowledge point from the knowledge graph database; after the retrieval results are sorted according to the relevance score, they are pushed to the user through the prompt area of ​​the front-end interaction layer (such as pop-up recommendations, banner recommendations, etc.) to guide the user to the next step of learning exploration.

[0052] In one embodiment, this application also provides an immersive puzzle-solving and gamified learning system for the inheritance of opera headdress culture. In this system, the immersive game module is also equipped with an achievement system. The achievement system records various achievement conditions achieved by the user during the learning process, including first completion of a level achievement, cumulative learning time achievement, and achievement of having one's work liked by other users reaching a set threshold achievement. When a user's achievement condition is triggered, the system automatically unlocks the corresponding achievement badge and displays the badge in the honor display area of ​​the user's personal homepage.

[0053] In this embodiment, the achievement system is a functional subsystem within the immersive game module used to motivate users to continue learning. The implementation process is as follows: The system predefines several achievement condition types, including: first-time level completion achievement (triggered when a user completes any level for the first time), cumulative learning time achievement (triggered when a user's cumulative learning time reaches set thresholds such as 1 hour, 5 hours, and 10 hours), and achievement for having their work liked (triggered when a user's personalized creation receives 10, 50, or 100 likes from other users, etc.). When any of a user's achievement conditions is triggered, the system automatically unlocks the corresponding achievement badge, simultaneously triggering a badge animation display effect to enhance the user's sense of accomplishment. The unlocked badge is automatically added to the user's personal homepage's honor display area for other users to browse and like.

[0054] In one embodiment, this application also provides an immersive decryption exploration and gamified learning system for the inheritance of opera headdress culture. In this system, the three-dimensional model generation unit of the personalized customization module adopts a three-dimensional model generation algorithm based on parametric modeling. The algorithm first calls the corresponding part model template according to the part type selected by the user, then maps the pattern to the specified area of ​​the part model according to the pattern parameters configured by the user, and finally applies a shader to perform color rendering according to the color parameters specified by the user to generate the final three-dimensional creative model.

[0055] In this embodiment, the 3D model generation algorithm of the personalized customization module is the core algorithm for realizing personalized creation by users, and it is implemented based on parametric modeling technology. Specifically: after receiving the component combination scheme submitted by the user, the 3D model generation algorithm first calls the pre-stored corresponding component model templates according to the component types selected by the user (e.g., helmet body type A, helmet brim type B, helmet top type C, and rear hood type D). Each component model template defines the geometric mesh data, UV coordinate mapping, and material parameters of the component. Second, according to the primary and secondary pattern parameters configured by the user, the selected pattern is mapped to a specified area on the surface of the component model through a texture mapping algorithm. The mapping position, size, and rotation angle of the pattern are dynamically adjusted according to the user parameters. Finally, according to the color parameters specified by the user, a shader is applied for color rendering. The color parameters include primary color, specular color, shadow color, and ambient light reflectance. The shader calculates the final lighting rendering effect based on these parameters to generate a realistic 3D creation model.

[0056] In one embodiment, this application also provides an immersive decryption exploration and gamified learning system for the inheritance of opera headdress culture. In this system, the system also includes an operation management backend module; the operation management backend module is used for administrators to incrementally update knowledge graph data, configure and adjust game levels, perform statistical analysis of user data, and manage the uploading and delisting of community activities.

[0057] In this embodiment, the operations management backend module is a web-based management interface that provides management functions for system operators. The implementation process is as follows: The knowledge graph management function allows operators to incrementally update the knowledge graph database, including adding helmet entities, updating process parameters, and correcting relational edges; the game level management function allows operators to configure and adjust the difficulty parameters, task content, and reward mechanism of game levels, including adding levels, modifying level order, and adjusting level completion conditions; the user data statistical analysis function provides multi-dimensional data statistical reports, including user activity statistics, learning time distribution statistics, and usage rate statistics of each functional module, to help operators understand the system's operational status; the community activity management function allows operators to manage the listing and delisting of design competitions and knowledge quizzes within the community, including activities going online, adjusting activity parameters, and taking activities offline.

[0058] In one embodiment, combined with Figure 2 , Figure 3 and Figure 4 The technical solution of this application will be further described. Figure 2 This is a schematic diagram illustrating the core principle framework of the knowledge graph database based on a four-dimensional association network of form, process, pattern, and color in this invention. (For example...) Figure 2 As shown, the knowledge graph database contains four major data types: helmet shape classification, helmet manufacturing process, correspondence between opera characters and helmets, and symbolic meaning of patterns. These four data types are modeled in multiple dimensions through a knowledge graph construction engine to form a four-dimensional association network of shape, craftsmanship, pattern, and color. The knowledge recommendation engine realizes intelligent knowledge recommendation function based on this four-dimensional association network.

[0059] Figure 3 This is a schematic diagram of the logical flow framework for the "edutainment" approach achieved by integrating the science education module and the immersive game module in this invention. For example... Figure 3 As shown, after entering the system, users can choose to enter the science education module or the immersive game module. In the science education module, users can gain intuitive knowledge through the 3D museum sub-module and engage in hands-on practice through the craft simulation sub-module. In the immersive game module, users can learn systematically through the task progression mechanism of the story-driven sub-module and consolidate their knowledge through the puzzle-solving mechanism of the clue-solving sub-module. The two modules are connected through a knowledge graph database, and learning outcomes are mutually transferred and verified, forming a complete learning loop that combines education and entertainment.

[0060] Figure 4 This is a schematic diagram of the technical closed-loop framework formed by the linkage between the personalized customization module and the social sharing module in this invention. For example... Figure 4As shown, users can create helmet designs through the personalized customization module, and the results can be exported as 3D model files. Users can also enjoy immersive displays through the augmented reality try-on function of the social sharing module, transform designs into physical products through the peripheral customization function, and spread them on social media through the community interaction function. Product order data and social interaction data are sent back to the data processing layer for analysis and processing, forming a complete business loop from creative design to social dissemination.

[0061] The immersive exploration and gamified learning system for the inheritance of opera headdress culture proposed in this application has the following significant advantages: 1. Structured Knowledge Network Support: A knowledge graph database containing a four-dimensional network of form, craftsmanship, pattern, and color is established through the data processing layer. For the first time, the culture of opera headdresses is digitally stored and presented in the form of a structured knowledge network, breaking through the technical limitations of traditional static display or one-way dissemination.

[0062] 2. Learning experience that combines education with entertainment: By organically integrating science education modules with immersive game modules, knowledge learning is transformed into an immersive and gamified active exploration behavior, which not only ensures the systematic and accurate transmission of knowledge, but also enhances the user's initiative and interest in learning.

[0063] 3. Complete User Journey Design: Through the technical linkage between the personalized customization module and the social sharing module, a complete user journey is formed from knowledge acquisition to creative practice and then to social dissemination, which effectively improves user stickiness and community activity.

[0064] 4. Feasibility of Commercialization: By combining augmented reality try-on technology with peripheral customized services, a feasible technical solution is provided for the organic derivation and commercialization of traditional opera culture, laying an economic foundation for the sustainable development of intangible cultural heritage.

[0065] In summary, the immersive exploration and gamified learning system for the inheritance of opera headdress culture proposed in this application successfully solves key technical problems in the inheritance of traditional opera culture, such as fragmented knowledge dissemination, monotonous experience forms, and passive inheritance methods. Through knowledge graph-driven system architecture design, immersive gamified learning mechanism, and the creation of a complete business closed loop, it provides a complete, replicable, and scalable digital solution for the living inheritance of traditional Chinese opera headdress culture.

[0066] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0067] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus, or computer program products. Therefore, embodiments of this application can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of this application can take the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0068] This application describes embodiments with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0069] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0070] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0071] Although preferred embodiments of the present application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present application.

[0072] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.

[0073] The above provides a detailed description of an immersive decryption exploration and gamified learning system for the inheritance of opera headdress culture provided in this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. An immersive, puzzle-solving, and gamified learning system for the inheritance of opera headdress culture, characterized in that: include: The data processing layer is used to establish and maintain a knowledge graph database of helmet culture. The knowledge graph database contains helmet shape classification data, helmet production process data, correspondence data between roles and helmets, and symbolic meaning data of patterns. The data processing layer uses a knowledge graph construction engine to perform multi-dimensional correlation modeling on the data, forming a four-dimensional correlation network of shape-process-pattern-color, and provides knowledge query interface and knowledge recommendation interface to the outside world. The front-end interaction layer is used to present the user interface and collect user operation commands. The front-end interaction layer is built on a 3D rendering engine and a responsive layout engine, supports cross-platform operation and adapts to different display terminals. The functional module layer includes a science education module, an immersive game module, a personalized customization module, and a social sharing module; The functional module layer exchanges data bidirectionally with the data processing layer through a standard data interface to realize the collection, storage and synchronization of user behavior data.

2. The system according to claim 1, characterized in that, The science education module includes: The 3D Museum submodule is used to build a 3D model library of classic helmets through the 3D modeling unit, and present the 3D models to the user in a surround display manner through the rendering unit; the 3D Museum submodule further provides a model disassembly function, allowing users to perform layered disassembly operations on the target helmet model, and display the name, function label and cultural meaning of each disassembled part. The process simulation submodule is used to demonstrate the entire process of helmet making step by step through the step guidance unit, including the demonstration of the pattern making process, the powdering process, the foil application process, and the kingfisher feather inlay process. The process simulation submodule further provides interactive operation functions, allowing users to simulate key production steps by dragging and dropping, and the system feedback unit judges the accuracy of the user's operation in real time and provides correction prompts.

3. The system according to claim 1, characterized in that, The immersive gaming module includes: The story-driven submodule is used to create a virtual apprentice character when a user visits for the first time, and to set up multi-level progressive level tasks with a virtual stage as the background. Each level task includes tasks such as helmet return, parts assembly, and character matching. Users can only unlock subsequent level tasks after completing the current level task. The Clue Puzzle Submodule is used to randomly distribute interactive clue points in the virtual stage scene. When a user triggers a clue point, it triggers a knowledge question and answer associated with that clue point. Only after the user solves the puzzle correctly can he / she advance the level. At the same time, the system updates the knowledge nodes involved in the puzzle-solving process to the user's personal learning profile.

4. The system according to claim 1, characterized in that, The personalized customization module includes: The classic style replication submodule is used to load preset classic helmet style templates and provides users with main pattern replacement interface, secondary pattern replacement interface and color configuration interface; after users adjust the parameters through each interface, the 3D model generation unit generates the corresponding 3D preview model in real time. The self-selection creation submodule provides a component library selection interface, listing available helmet body components, visor components, helmet top components, and back flap components for users to freely combine. After the user completes the component combination, the combination rationality detection unit performs rule verification on the combination. When a combination is detected that does not comply with the wearing rules, the system automatically prompts the user and prohibits the generation of a preview model. When the combination passes the verification, the 3D model generation unit generates a unique 3D creation model and generates a digital certificate for the model.

5. The system according to claim 1, characterized in that, The social sharing module includes: The augmented reality try-on submodule is used to call the camera of the mobile device to obtain real-time images, overlay the 3D model of the helmet selected by the user onto the specified position of the camera image, generate an augmented reality try-on image, and support the user to take photos or record videos for saving. The peripheral customization submodule is used to receive customized orders submitted by users. The order parameters include 3D model specifications, peripheral product type parameters, and material parameters. The system generates a customized preview image based on the order parameters. After the user confirms the image, the order payment is completed and the system enters the production process. The community interaction submodule provides users with functions such as displaying their personal homepage, showcasing their personal works, and participating in social activities. The personal homepage displays a list of completed levels, unlockable helmet types, learning time statistics, and achievement badge collection records.

6. The system according to claim 1, characterized in that, The construction process of the knowledge graph database includes: The original data collection step is used to collect original helmet data from sources such as interview records of intangible cultural heritage inheritors, archives of cultural relics, and classics on traditional opera costume techniques. The entity extraction step is used to extract helmet entities, component entities, process entities, character entities, and pattern entities from the original data, and assign a unique identifier to each entity; The relationship establishment step is used to analyze the semantic associations between entities, establish relationship edges between entities, and store them in the relational database. The knowledge reasoning step is used to perform transitive reasoning based on the established relation edges, generate implicit associations, and supplement the knowledge graph database.

7. The system according to claim 1, characterized in that, The data processing layer also implements intelligent knowledge recommendation function through a knowledge recommendation engine; the knowledge recommendation engine obtains the user's recent browsing history, recently completed level history and current learning progress, retrieves extended knowledge nodes related to the user's current knowledge points from the knowledge graph database through the association analysis algorithm, and pushes the retrieval results to the prompt area of ​​the front-end interaction layer.

8. The system according to claim 3, characterized in that, The immersive game module is also equipped with an achievement system; the achievement system records various achievement conditions achieved by users during the learning process, including first completion of a level achievement, cumulative learning time achievement, and creation of works that have been liked by other users reaching a set threshold achievement; when a user's achievement condition is triggered, the system automatically unlocks the corresponding achievement badge and displays the badge in the honor display area of ​​the user's personal homepage.

9. The system according to claim 4, characterized in that, The 3D model generation unit adopts a 3D model generation algorithm based on parametric modeling. The algorithm first calls the corresponding part model template according to the part type selected by the user, then maps the pattern to the specified area of ​​the part model according to the pattern parameters configured by the user, and finally applies shaders to perform color rendering according to the color parameters specified by the user to generate the final 3D creation model.

10. The system according to claim 1, characterized in that, It also includes an operations management backend module; the operations management backend module is used by administrators to incrementally update knowledge graph data, adjust the configuration of game levels, perform statistical analysis of user data, and manage the uploading and delisting of community activities.

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