Dong minority culture content information generation method and device

Abstract

The invention belongs to the technical field of information, and discloses a Dong minority culture content information generation method and device, and the method comprises the steps: obtaining the position information and sight line direction information of tourist virtual reality equipment; according to the position information, various culture elements corresponding to the Dong minority culture virtual reality scene are loaded; according to the sight direction information and the distribution positions of the loaded various culture elements, determining the culture elements in the sight area of the tourist, and recording the culture elements as display culture elements; determining the fineness level of each display culture element according to the preset priority and distribution position of each display culture element; according to the determined fineness level, generating virtual reality content corresponding to each display culture element; transmitting the generated virtual reality content to a tourist virtual reality device; therefore, smooth Dong minority culture virtual reality experience with rich culture details can be realized under the conditions of limited network bandwidth and limited computing resources.

Description

Technical Field

[0001] The present application relates to the field of information technology, and more specifically, to a method and device for generating Dong ethnic cultural content information. Background Art

[0002] To enhance visitors' cultural experiences, some Dong village scenic spots are introducing virtual reality (VR) technology, hoping to showcase the unique charm of Dong culture through immersive experiences. However, these scenic spots generally face the challenges of weak network infrastructure and limited wireless network bandwidth. When multiple visitors simultaneously wear VR devices and navigate the scenic area, the VR system must dynamically load culturally relevant VR content, such as distinctive architecture, festivals, and traditional crafts, based on their real-time location information. To address bandwidth limitations and reduce data transmission latency, scenic spots often deploy edge computing servers (edge computing devices) to generate and distribute VR content. While edge computing alleviates network transmission pressure to some extent, it still faces significant computational pressure from multiple concurrent visitors and the high computing resource demands of the VR content itself. This is especially true when high-precision representation of Dong cultural details is required to ensure cultural authenticity and immersion. Traditional VR content generation methods often suffer from excessive data volume, leading to VR experience lag and poor smoothness.

[0003] Therefore, in application scenarios such as Dong village scenic spots where the network environment is limited and multiple mobile tourists need to be served simultaneously, how to design an efficient edge computing VR content generation method to ensure that every tourist can obtain a smooth, location-related and culturally rich VR experience under limited bandwidth and computing resources has become a key technical problem that needs to be solved urgently.

[0004] In view of the above problems, the existing technology is in urgent need of improvement. Summary of the Invention

[0005] The purpose of this application is to provide a method and device for generating Dong ethnic cultural content information, which can achieve a smooth and culturally rich Dong ethnic cultural virtual reality experience under the conditions of limited network bandwidth and limited computing resources.

[0006] In a first aspect, the present application provides a method for generating Dong ethnic cultural content information, which is applied to edge computing devices in Dong village scenic areas to generate Dong ethnic cultural virtual reality content for tourists. The method includes: A1. Obtain the location and sight direction of the visitor's virtual reality device; A2. Load various cultural elements corresponding to the Dong ethnic culture virtual reality scene based on the location information; A3. Determine the cultural elements within the tourist's line of sight area based on the line of sight direction information and the distribution locations of various loaded cultural elements, and denote them as displayed cultural elements; A4. Determine the fineness level of each displayed cultural element based on the preset priority level and distribution location of each displayed cultural element; A5. Generate virtual reality content corresponding to each displayed cultural element according to the determined fineness level; A6. Transmit the generated virtual reality content to the tourist's virtual reality device.

[0007] Furthermore, this application also proposes that step A2 includes: A201. Screen out the set of cultural elements related to the location information from the virtual reality content library according to the location information; A202. Sort each cultural element in the set of cultural elements based on the superiority parameter of each cultural element. The higher the superiority, the higher the ranking; the superiority parameters include historical access frequency, expert score, and Dong ethnic culture representativeness score; A203. Load a number of the top-ranked cultural elements according to the sorting result and the remaining storage space of the edge computing device.

[0008] Furthermore, this application also proposes that step A202 includes: B1. Calculate the comprehensive superiority score of each cultural element in the set of cultural elements through a weighted algorithm according to the superiority parameter; B2. Sort each cultural element in the set of cultural elements in descending order according to the comprehensive superiority score.

[0009] Furthermore, this application also proposes that after step B1 and before step B2, the following step is also included: B3. Obtain the portrait data of the tourist to estimate the personalized preference score of each cultural element in the set of cultural elements for the tourist; B4. Modify the comprehensive superiority score of each cultural element in the set of cultural elements according to the personalized preference score.

[0010] Furthermore, this application also proposes that step A3 includes: A301. Construct a frustum according to the line of sight direction information and the preset field of view angle parameter; A302. Traverse each loaded cultural element, and judge whether each cultural element meets the geometric constraint conditions of the frustum range according to the distribution location of each cultural element, and determine the cultural elements that meet the geometric constraint conditions of the frustum range as displayed cultural elements.

[0011] Furthermore, this application also proposes that step A302 includes: Construct a spatial index structure that includes the distribution positions of the loaded cultural elements; Based on the spatial index structure, using the vertex coordinates of the viewing frustum and the bounding box information of each cultural element, filter out a set of candidate cultural elements that may intersect with the viewing frustum; Traverse each cultural element in the set of candidate cultural elements, and according to the distribution position of each cultural element, determine whether each cultural element meets the geometric constraint conditions of the viewing frustum range, and determine the cultural elements that meet the geometric constraint conditions of the viewing frustum range as displayed cultural elements.

[0012] Furthermore, the present application also proposes that step A4 includes: A401. According to the distribution positions of the displayed cultural elements, calculate the distances between the displayed cultural elements and the tourist's virtual reality device; A402. Determine the distance level according to the distance; A403. According to the preset priorities and distance levels of the displayed cultural elements, determine the initial fineness levels of the displayed cultural elements; A404. Obtain the moving speed of the tourist's virtual reality device to correct the initial fineness levels of the displayed cultural elements and obtain the final fineness levels.

[0013] Furthermore, the present application also proposes that step A404 includes: Obtain the moving speed of the tourist's virtual reality device; Judge whether the moving speed is greater than the preset speed threshold; If the moving speed is greater than the preset speed threshold, calculate the fineness attenuation coefficient according to the moving speed and the distance level, and reduce the initial fineness level according to the fineness attenuation coefficient to obtain the final fineness level; the greater the moving speed and the higher the distance level, the greater the fineness attenuation coefficient; If the moving speed is not greater than the preset speed threshold, use the initial fineness level as the final fineness level.

[0014] Furthermore, the present application also proposes that step A5 includes: A501. According to the determined fineness level, select the cultural element model corresponding to the fineness level from the preset cultural element model library; A502. According to the selected cultural element model, select the texture map corresponding to the fineness level from the preset texture library, and map the texture map onto the cultural element model to generate cultural element visual resources with the corresponding fineness level; A503. Integrate the generated cultural element visual resources in spatial positions to construct virtual reality scene content that matches the current line-of-sight area.

[0015] Second aspect, the present application also proposes a Dong ethnic culture content information generation device, which is applied to edge computing devices in Dong ethnic villages to generate virtual reality content of Dong ethnic culture for tourists. The device includes: A position and line-of-sight acquisition module, configured to acquire the position information and line-of-sight direction information of the tourist's virtual reality device; A scene loading module, configured to load various cultural elements corresponding to the virtual reality scene of Dong ethnic culture according to the position information; A display element determination module, configured to determine the cultural elements within the tourist's line-of-sight area according to the line-of-sight direction information and the distribution positions of the loaded various cultural elements, and record them as display cultural elements; A fineness determination module, configured to determine the fineness levels of the respective display cultural elements according to the preset priorities and distribution positions of the respective display cultural elements; A content generation module, configured to generate virtual reality content corresponding to the respective display cultural elements according to the determined fineness levels; A content transmission module, configured to transmit the generated virtual reality content to the tourist's virtual reality device.

[0016] Advantageous effects: A method and device for generating Dong ethnic culture content information provided by the present application determine the cultural elements within the tourist's line-of-sight area, determine the fineness levels according to the priorities and distribution positions, and generate virtual reality content as needed, solving the problems of limited network bandwidth and computing resources, and having the advantages of realizing a smooth and culturally detailed virtual reality experience of Dong ethnic culture under the conditions of limited network bandwidth and limited computing resources. Description of the Drawings

[0017] Figure 1 It is a flowchart of the method for generating Dong ethnic culture content information provided by an embodiment of the present application.

[0018] Figure 2 It is a structural schematic diagram of the device for generating Dong ethnic culture content information provided by an embodiment of the present application.

[0019] Reference numeral description: 1. Position and line-of-sight acquisition module; 2. Scene loading module; 3. Display element determination module; 4. Fineness determination module; 5. Content generation module; 6. Content transmission module. Specific Embodiments

[0020] The technical solutions in the present application will be clearly and completely described below with reference to the accompanying drawings in the present application. Apparently, the described embodiments are only some of the embodiments of the present application, rather than all embodiments. The components of the present application usually described and illustrated in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but merely represents the selected embodiments of the present application. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative efforts fall within the scope of protection of the present application.

[0021] It should be noted that: Similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present application, terms such as "first", "second", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0022] Referring to Figure 1 , the present application proposes a method for generating Dong ethnic culture content information, which is applied to an edge computing device in a Dong ethnic village scenic area to generate virtual reality content of Dong ethnic culture for tourists. The method includes: A1. Obtain the location information and line-of-sight direction information of the tourist's virtual reality device; A2. According to the location information, load various cultural elements of the corresponding virtual reality scene of Dong ethnic culture; A3. Determine the cultural elements within the tourist's line-of-sight area according to the line-of-sight direction information and the distribution positions of the loaded various cultural elements, and record them as displayed cultural elements; A4. Determine the fineness level of each displayed cultural element according to the preset priority and distribution position of each displayed cultural element; A5. Generate virtual reality content corresponding to each displayed cultural element according to the determined fineness level; A6. Transmit the generated virtual reality content to the tourist's virtual reality device.

[0023] Among them, in step A1, the location information of the tourist's virtual reality device is obtained through a positioning module, such as GPS positioning (for example, the tourist's virtual reality device integrates a GPS module to receive satellite signals in real time and calculates the current longitude and latitude coordinates of the device) or base station positioning (for example, the tourist's virtual reality device communicates with the base station through a mobile communication network, and the base station estimates the location of the device based on information such as signal strength and arrival time). The line-of-sight direction information is captured by sensors built into the virtual reality device, such as a gyroscope (for example, the gyroscope can measure the rotational angular velocity of the virtual reality device, and the attitude information of the device is obtained through integration to determine the line-of-sight direction) or a camera (for example, by capturing the eye movement and head movement of the tourist and analyzing the image information to infer the tourist's line-of-sight direction).

[0024] Among them, in step A2, various cultural elements corresponding to the Dong ethnic culture virtual reality scene are pre-stored in the virtual reality content library of the edge computing device or the cloud server. The cultural elements include Dongzhai building models, ethnic clothing models, cultural performance videos, etc. The cultural elements have an association relationship with the location information. For example, the drum tower model is associated with the location coordinates where the drum tower is located. This association relationship can be pre-recorded to form a query table, and the corresponding cultural elements can be queried according to the location information of the tourist's virtual reality device.

[0025] Among them, in step A3, the line-of-sight area is represented by a frustum model. The frustum is determined by the line-of-sight direction information and a preset field-of-view angle parameter. It is judged whether the cultural element is located within the frustum by comparing the spatial position of the cultural element (i.e., the distribution position, and the distribution positions of each cultural element are preset in advance) and the geometric range of the frustum.

[0026] Among them, in step A4, the preset priority is set artificially according to the importance of the cultural elements. For example, the priority of the drum tower is higher than that of ordinary folk houses. The fineness level is divided into multiple levels, such as high fineness, medium fineness, and low fineness. The distance level is divided according to a distance threshold, such as close distance, medium distance, and long distance. The fineness level and the distance level can also be represented by level values.

[0027] Among them, in step A5, the virtual reality content generation process includes model selection, texture loading, and rendering. The higher the fineness level, the more polygon faces the selected model has and the higher the resolution of the texture map.

[0028] Among them, in step A6, the generated virtual reality content is transmitted to the tourist's virtual reality device for display through a wireless network transmission protocol, such as Wi-Fi or 5G, etc. Thus, it realizes the efficient generation of Dong ethnic culture virtual reality content for the tourist's line-of-sight area under the condition of limited resources of the edge computing device.

[0029] Specifically, for the method provided in this application, first, the location information of the tourist's virtual reality device is utilized to load Dong ethnic culture elements related to the tourist's current location from the virtual reality content library, thereby ensuring the location relevance of the virtual reality content. Then, in combination with the tourist's line-of-sight direction information, through frustum culling technology, the cultural elements within the tourist's field of view are accurately screened out as the displayed cultural elements, reducing the rendering of unnecessary cultural elements and lowering the computational burden. Further, this application also considers the preset priority and distribution location of the displayed cultural elements, divides the displayed cultural elements into levels of detail, assigns a high level of detail to the cultural elements that are close to the tourist or have a high priority, and vice versa, achieving the control of the level of detail of the virtual reality content. Finally, according to the determined level of detail, virtual reality content with the corresponding level of detail is adaptively generated and transmitted to the tourist's virtual reality device, ensuring that under limited computational and network resources, a smooth and culturally detailed virtual reality experience is provided to the tourist. Through the above steps, the method provided in this application realizes the improvement of the virtual reality content generation efficiency and user experience in an edge computing environment, and solves the technical problem of efficiently generating virtual reality content of Dong ethnic culture when the resources of edge computing devices are limited.

[0030] In some specific embodiments, the tourist is near the drum tower in the Dong ethnic village scenic area and wears a virtual reality helmet. The edge computing device first obtains the tourist's longitude and latitude coordinates through the GPS module and obtains the tourist's line-of-sight direction through the gyroscope sensor of the helmet. The edge computing device loads the 3D model data and texture data of cultural elements such as the drum tower, Dong ethnic village buildings, and wind-rain bridges from the pre-stored virtual reality content library according to the longitude and latitude coordinates. Then, the edge computing device constructs a frustum according to the line-of-sight direction and a preset 60-degree field of view angle, and uses a spatial index structure to quickly screen out the drum tower and some building models within the frustum as the displayed cultural elements. For the drum tower, which is a high-priority cultural element and is relatively close to the tourist, it is determined to be at a high level of detail. The edge computing device selects a high-polygon drum tower model and a high-resolution texture map to generate the virtual reality content of the drum tower; for the buildings in the distance, which are determined to be at a low level of detail, the edge computing device selects a low-polygon building model and a low-resolution texture map to generate the virtual reality content of the buildings. Finally, the generated virtual reality content is encoded and transmitted to the tourist's virtual reality helmet through the Wi-Fi network for immersive display.

[0031] In some embodiments, step A2 includes: A201. According to the location information, screen out the set of cultural elements related to the location information from the virtual reality content library; A202. Sort each cultural element in the set of cultural elements based on the superiority parameters of each cultural element. The higher the superiority, the more forward the ranking. The superiority parameters include historical access frequency, expert score, and the representative score of Dong culture; A203. Load a number of the cultural elements ranked at the top according to the sorting result and the remaining storage space of the edge computing device.

[0032] Among them, in step A201, the location information is used as a condition for screening the set of cultural elements from the virtual reality content library. The virtual reality content library has pre-stored cultural element information related to different locations. The specific screening process is as follows: After the edge computing device receives the location information of the tourist's virtual reality device, it queries the virtual reality content library, retrieves the cultural elements associated with the location information, and forms a set of cultural elements with the retrieved cultural elements.

[0033] Among them, in step A202, the superiority parameters of each cultural element are used for sorting. The superiority parameters include historical access frequency, expert score, and the representative score of Dong culture. The historical access frequency reflects the popularity of the cultural element among tourists; the expert score reflects the value of the cultural element in the professional field; the representative score of Dong culture indicates the degree to which the cultural element represents Dong culture (a panel of experts, such as folklorists, historians, cultural scholars, etc. in the field of Dong culture, can be formed to evaluate and score the representativeness of each cultural element. The evaluation criteria can include the historical status, inheritance degree, recognition, and influence of the cultural element in Dong culture. The panel of experts gives a representative score to each cultural element according to the evaluation criteria). These parameters can be preset and stored in the cultural element information. When sorting, a weighted summation method can be used to calculate the comprehensive superiority value according to the weights of each superiority parameter, and the set of cultural elements is sorted based on the comprehensive superiority value. The higher the superiority value, the more forward the ranking.

[0034] Among them, in step A203, the number of cultural elements loaded is limited by the remaining storage space of the edge computing device. After the edge computing device finishes sorting the cultural elements, it obtains the information of its remaining storage space. Then, according to the size of the remaining storage space, a part of the cultural elements ranked at the top is selected from the sorting result for loading. The number of loaded elements needs to ensure that it does not exceed the storage capacity of the edge computing device. Thus, in the case of limited edge computing resources, cultural elements with high superiority are preferentially loaded to ensure the key cultural content of the virtual reality experience.

[0035] Specifically, this solution provides a method for optimizing the cultural element loading process in an edge computing environment. In a virtual reality tour application for a Dong village scenic area, when a visitor moves to a specific location, the edge computing device first uses the visitor's location information to filter cultural elements relevant to that location from a pre-built library of Dong ethnic culture virtual reality content. For example, if the visitor is near a drum tower, the selected cultural element set might include a drum tower architectural model, an introduction to the drum tower culture, and scenes of festivals and celebrations related to the drum tower. The superiority of each cultural element in the selected set is then evaluated. Evaluation criteria might include: the drum tower has a higher historical visit frequency than ordinary residential buildings; experts rate the drum tower higher than ordinary trees; and the drum tower, as a landmark of the Dong village, is more culturally representative than ordinary stone tablets. Based on these superiority parameters, a weighted algorithm is used to calculate the overall superiority score of each cultural element and rank them from high to low. Assume that the top three cultural elements in the ranking are: a 3D drum tower model (with the highest overall score), a video introducing the drum tower culture, and a VR scene of a drum tower festival and celebration. Finally, the edge computing device detects that there's only enough storage space to load two cultural elements. Based on the sorting results, it loads the first and second ranked cultural elements: the Drum Tower 3D model and the video introducing Drum Tower culture. This prioritizes loading the core cultural element of the Drum Tower, even with limited storage space, ensuring that visitors experience the most important cultural content first, even with limited resources.

[0036] In some specific embodiments, the virtual reality content library can adopt a distributed storage structure, with a portion stored on a cloud server and a portion stored locally on the edge computing device. In step A201, the edge computing device first queries the local content library. If the local content library does not contain a cultural element that fully matches the location information, it further sends a request to the cloud server to obtain a more comprehensive set of cultural elements. In step A202, the weighting of the superiority parameters can be adjusted according to the actual application scenario. For example, during peak tourist seasons such as holidays, the weighting of historical visit frequency can be appropriately increased to prioritize the loading of cultural elements that are more popular with tourists. During cultural promotional activities, the weighting of the representativeness score of Dong ethnic culture can be increased to highlight the unique characteristics of Dong culture. In step A203, the edge computing device can monitor the remaining storage space in real time and dynamically adjust the number of cultural elements loaded based on changes in storage space. As a preferred embodiment, a storage space threshold can be preset. When the remaining storage space is below this threshold, only a portion of the key cultural elements will be loaded, even if the number of cultural elements ranked at the top is large, to ensure stable system operation.

[0037] Specifically, step A202 includes: B1. Calculate the comprehensive superiority score of each cultural element in the set of cultural elements using a weighted algorithm based on the superiority parameters; B2. Sort each cultural element in the cultural element set in descending order according to the comprehensive superiority score.

[0038] Among them, for the weighted algorithm proposed in step B1, a linear weighting method can be adopted. For example, weights are set for the three superiority parameters of historical access frequency, expert score, and the representativeness score of Dong culture respectively. The weight values can be adjusted according to the actual application scenario and requirements. For example, they can be set as 0.4, 0.3, and 0.3 respectively. When calculating the comprehensive superiority score, multiply the historical access frequency of each cultural element by the corresponding weight value, the expert score by the corresponding weight value, and the representativeness score of Dong culture by the corresponding weight value, and then add the three to obtain the comprehensive superiority score of this cultural element. Among them, before performing the weighted algorithm, the superiority parameters can be normalized first to convert the numerical range of each superiority parameter to [0, 1].

[0039] Among them, the descending order sorting proposed in step B2 means sorting all the cultural elements in the cultural element set from high to low according to the comprehensive superiority score calculated in step B1. The sorting result will be used as the basis for loading cultural elements in the subsequent steps, so that the cultural elements with higher comprehensive superiority scores can be loaded first, thereby ensuring the quality of virtual reality content and the user experience under limited edge computing resources.

[0040] Specifically, after obtaining the cultural element set, the system will first collect superiority parameter data for each cultural element in the set. The superiority parameters can include but are not limited to historical access frequency, expert score, and the representativeness score of Dong culture. Then, for each cultural element, the system will calculate a comprehensive superiority score by weighted summation according to the preset weights. For example, the weight of historical access frequency is 0.4, the weight of expert score is 0.3, and the weight of the representativeness score of Dong culture is 0.3. For example, if the normalized historical access frequency of a certain cultural element is 0.8, the expert score is 0.9, and the representativeness score of Dong culture is 0.7, then its comprehensive superiority score is 0.8 * 0.4 + 0.9 * 0.3 + 0.7 * 0.3 = 0.8. After calculating the comprehensive superiority scores of all cultural elements, the system will sort the cultural elements in descending order according to these scores. The cultural elements with higher sorting results represent higher comprehensive superiority and will be given priority in the subsequent steps to be considered for loading. Thus, it is ensured that under the limited edge computing resources, the system can give priority to presenting more important or more popular Dong cultural elements, enhancing the virtual reality experience of tourists. By comprehensively considering superiority parameters in multiple dimensions through the weighted algorithm, the value of cultural elements can be evaluated more comprehensively and accurately, and sorted accordingly, ensuring the rationality and effectiveness of the sorting of cultural elements.

[0041] Further, after step B1 and before step B2, the following steps may also be included: B3. Obtain the portrait data of the tourist to estimate the personalized preference degree scores of each cultural element in the cultural element set for the tourist; B4. According to the personalized preference degree scores, correct the comprehensive superiority scores of each cultural element in the cultural element set.

[0042] Among them, in step B3, the portrait data may include, but is not limited to, information such as the age, gender, occupation, and hobbies of the tourist. Using this information, analyze the types of cultural elements that the tourist may be interested in. For example, for tourists interested in historical culture, higher personalized preference degree scores will be given to historical buildings and traditional festival cultural elements.

[0043] In one embodiment, the portrait data of the tourist is obtained through the user registration information. Before using the virtual reality tour guide system, the tourist needs to register. When registering, the tourist can fill in personal information such as age, gender, occupation, hobbies, etc. This information is stored in the user portrait database as the portrait data of the tourist. The system can analyze the preferences of the tourist based on this portrait data. For example, tourists who like historical culture may be more interested in cultural relics and historic sites, and tourists who like folk customs may be more interested in ethnic costumes and festival activities.

[0044] Another embodiment is to obtain the portrait data of the tourist through the analysis of user behavior data. During the process of the tourist using the virtual reality tour guide system, the system will record the behavior data of the tourist, such as browsing history, click behavior, stay time, etc. (that is, the portrait data may include this behavior data). By analyzing this behavior data, the interest preferences of the tourist can be inferred. For example, if the tourist frequently browses the introduction information of a certain cultural element, or stays in the virtual scene corresponding to this cultural element for a long time, it can be considered that the tourist is more interested in this cultural element.

[0045] There is also an embodiment to obtain the portrait data of the tourist through the data of a third-party platform. If the tourist permits, the system can obtain the public data of the tourist on the third-party platform, such as social media accounts, e-commerce platform accounts, etc. By analyzing this data, a more comprehensive understanding of the tourist's interest preferences can be obtained. For example, if the tourist follows accounts related to Dong culture on social media, or has purchased goods related to Dong culture on the e-commerce platform, it can be considered that the tourist is more interested in Dong culture.

[0046] After obtaining the portrait data of tourists, the system needs to process this data to estimate the personalized preference degree scores of tourists for each cultural element in the cultural element set. A commonly used method is to establish a cultural element tagging system, where each cultural element is labeled with several tags, such as "architecture", "clothing", "song and dance", "history", "folk custom", etc. Then, based on the portrait data of tourists, calculate the preference degree of tourists for each tag (for example, it can be calculated using machine learning-based methods). For example, if the portrait data of a tourist shows that they like historical culture and folk customs, the preference degree scores for the "history" and "folk custom" tags will be relatively high. Finally, based on the tags of the cultural element and the preference degree of tourists for the tags, calculate the personalized preference degree score of tourists for this cultural element (the preference degree of tourists for the tag or its normalized value can be directly used as the personalized preference degree score of tourists for this cultural element, or the preference degree of tourists for the tag can be converted into the personalized preference degree score of tourists for this cultural element through a preset conversion formula). For example, if a certain cultural element is labeled with the "architecture" and "history" tags, and the preference degree scores of tourists for the "architecture" and "history" tags are relatively high, then the personalized preference degree score of this tourist for this cultural element will also be relatively high.

[0047] Among them, for step B4, the personalized preference degree score is used to correct the comprehensive superiority score of the cultural element. For example, the personalized preference degree score and the comprehensive superiority score can be weighted and averaged to obtain the corrected comprehensive superiority score.

[0048] Specifically, during the process of sorting cultural elements, first, in step B1, based on superiority parameters such as historical access frequency, expert scores, and the representative scores of Dong culture, the comprehensive superiority scores of each cultural element in the cultural element set are calculated. Then, step B3 is executed, where the edge computing device accesses the user profile database of the tourist to obtain the profile data of the current tourist. The profile data includes the age, gender, and interest tags of the tourist. Based on this profile data, the system analyzes the preferences of the tourist. For example, by analyzing the historical behavior data of the tourist or the explicitly selected interest tags, the system determines the degree of preference of the tourist for different types of Dong cultural elements such as architecture, clothing, singing, and dancing. The system calculates a personalized preference score for each cultural element, with the score ranging from 0 to 1. The higher the score, the more interested the tourist is in the cultural element. Next, step B4 is executed, and the system uses the weighted average method to correct the comprehensive superiority score. For example, the weight of the superiority parameter is set to 0.7, and the weight of the personalized preference score is set to 0.3. The two are weighted averaged to obtain the corrected comprehensive superiority score. Finally, in step B2, the cultural elements are sorted according to the corrected comprehensive superiority score, and the sorting result is used for subsequent cultural element loading. Thus, the sorting result takes into account both the quality and importance of the cultural elements themselves and the personalized interests of the tourists, making the recommended virtual reality content more in line with the expectations of the tourists.

[0049] In some specific embodiments, in step B3, the tourist profile data is obtained from the scenic area tourist management system. When tourists enter the scenic area, they are required to register or log in using a third-party account. During the registration or login process, the demographic information and interest preferences of the tourists are collected and stored. In step B3, the personalized preference score is calculated through a content recommendation algorithm. For example, the collaborative filtering algorithm is used to analyze the historical behavior data of other tourists with similar interests to the current tourist to predict the degree of preference of the current tourist for each cultural element. Alternatively, the content-based recommendation algorithm is used to analyze the matching degree between the attribute tags of the cultural elements and the interest tags of the tourist to calculate the personalized preference score. In step B4, the way to correct the comprehensive superiority score is to perform a weighted average of the personalized preference score and the comprehensive superiority score to obtain the corrected comprehensive superiority score. In this way, the cultural elements that the tourists are particularly interested in can be preferentially loaded and displayed, improving the personalization degree of the tourists' virtual reality experience.

[0050] Furthermore, this application also proposes that step A3 includes: A301. Construct a viewing frustum according to the line-of-sight direction information and the preset field-of-view angle parameters; A302. Traverse each loaded cultural element, and according to the distribution position of each cultural element, determine whether each cultural element meets the geometric constraint conditions of the viewing frustum range, and determine the cultural elements that meet the geometric constraint conditions of the viewing frustum range as the display cultural elements.

[0051] Among them, in step A301, the frustum construction process can be implemented as follows: First, the line-of-sight direction information is used to determine the orientation of the frustum; then, preset field-of-view angle parameters, such as the horizontal field-of-view angle and the vertical field-of-view angle, are used to set the opening angle of the frustum; thus, the six clipping planes of the frustum are defined, and they jointly define the visible space range of the frustum.

[0052] Among them, in step A302, determining whether a cultural element meets the geometric constraint conditions of the frustum range can be implemented as follows: The distribution position of the cultural element is usually represented by the vertex and center point coordinates of its bounding box; the judgment process of the geometric constraint conditions is implemented as checking whether the vertex coordinates of the bounding box of the cultural element are inside the frustum or whether the bounding box of the cultural element intersects with the frustum; if one of the foregoing conditions is met, the cultural element is determined to be a display cultural element.

[0053] Specifically, in this solution, first, the frustum is constructed using the tourist's line-of-sight direction information and preset field-of-view angle parameters, and the frustum simulates the tourist's field of view. Then, the loaded cultural elements are traversed, and for each cultural element, according to its distribution position, geometric constraint condition judgment is performed to determine whether the cultural element is within the frustum range. The geometric constraint condition judgment process effectively filters out the cultural elements within the tourist's line-of-sight area, and these filtered cultural elements are determined to be display cultural elements for subsequent generation of virtual reality content. Thus, through the frustum and geometric constraint judgment, the cultural elements within the line-of-sight area are accurately and efficiently determined. This method avoids unnecessary rendering and processing by traversing all loaded cultural elements, reduces the computational amount, improves the system efficiency, and ensures the smoothness of virtual reality content generation.

[0054] In some specific embodiments, the preset field-of-view angle parameters are set to a horizontal field-of-view angle of 60 degrees and a vertical field-of-view angle of 45 degrees. When constructing the frustum, first, the unit vector of the tourist's line-of-sight direction is obtained, and then the normal vectors and vertex coordinates of each face of the frustum are calculated according to the field-of-view angle. The distribution position of the cultural element is represented by the center point and vertex coordinates of the three-dimensional bounding box of the cultural element. When performing geometric constraint condition judgment, an intersection detection algorithm between the bounding box and the frustum is used to quickly judge whether the bounding box intersects with the frustum. For example, the Separating Axis Theorem can be used for intersection detection. If the bounding box intersects with the frustum, the cultural element is determined to be a display cultural element. Through the above embodiments, the cultural elements within the line-of-sight area can be accurately screened out, providing a data basis for subsequent generation of virtual reality content.

[0055] In some embodiments, step A302 includes: Construct a spatial index structure that includes the distribution positions of the loaded cultural elements; Based on the spatial index structure, using the vertex coordinates of the viewing frustum and the bounding box information of each cultural element, filter out a set of candidate cultural elements that may intersect with the viewing frustum; Traverse each cultural element in the set of candidate cultural elements. According to the distribution positions of the cultural elements, determine whether each cultural element meets the geometric constraint conditions of the viewing frustum range, and determine the cultural elements that meet the geometric constraint conditions of the viewing frustum range as the displayed cultural elements.

[0056] Among them, the construction of the spatial index structure is for the efficient management and query of the position information of cultural elements. For example, structures such as quadtrees or octrees can be used to implement it. The specific construction method is prior art and will not be elaborated here. After constructing the spatial index structure, the position information of cultural elements is organized into a tree structure, enabling the rapid retrieval of cultural elements according to spatial positions.

[0057] Among them, the viewing frustum is determined by the line-of-sight direction information and the preset field-of-view angle parameter, and it defines the three-dimensional space range that the tourist's line of sight reaches. The bounding box is a cube used to simplify the geometric representation of an object, and the bounding box of a cultural element is used for rapid intersection testing. By using the vertex coordinates of the viewing frustum and the bounding box information of the cultural element for intersection testing, the cultural elements that may be located within the viewing frustum can be initially filtered out to form a set of candidate cultural elements. This filtering is fast because it avoids precise geometric calculations for all cultural elements.

[0058] Among them, the geometric constraint conditions refer to the precise geometric conditions that the cultural element needs to be completely or partially located inside the viewing frustum. After the set of candidate cultural elements is filtered out, for each cultural element in the set, precise geometric constraint judgment needs to be performed to finally determine which cultural elements are the displayed cultural elements that are truly located within the line-of-sight area. For example, it can be determined whether the vertices of the cultural element are inside the viewing frustum, or whether there is an intersection line or intersection surface between the cultural element and the viewing frustum. Through the spatial index structure and the two-stage filtering mechanism, the scope of cultural element filtering is effectively reduced, thereby reducing the complexity of geometric calculations and improving the efficiency of determining the displayed cultural elements.

[0059] Specifically, for the loaded cultural elements, a spatial index structure is first constructed. As a preferred implementation, an octree is selected as the spatial index structure. The octree organizes the position information of cultural elements by recursively dividing the three-dimensional space into eight sub-cubes. The distribution position of each cultural element is recorded in the leaf nodes of the octree. Then, a frustum is constructed based on the viewing direction information of the tourist and the preset field-of-view angle parameter. The shape and range of the frustum are determined by the field-of-view angle and the viewing direction. After that, using the vertex coordinates of the frustum and the axis-aligned bounding box (AABB) information of the cultural element, an intersection test is performed. The axis-aligned bounding box is a cube that tightly wraps the cultural element and is aligned with the coordinate axes, and it can be quickly used for intersection detection. Through the spatial query function of the octree and the intersection detection algorithm between the axis-aligned bounding box and the frustum, a set of candidate cultural elements that may intersect with the frustum is quickly screened out. Finally, traverse the set of candidate cultural elements, and for each cultural element in the set, perform an accurate geometric constraint judgment. For example, the point-frustum test algorithm can be used to check whether each vertex of the cultural element is inside the frustum, or a more refined clipping algorithm can be used to calculate the actual intersection between the cultural element and the frustum. Only the cultural elements that meet the geometric constraint conditions are finally determined as the displayed cultural elements.

[0060] In some specific embodiments, it is assumed that one hundred cultural elements are loaded in the virtual reality scene of the Dongzhai scenic area. Without using the spatial index and two-stage screening method, each time the displayed cultural elements are determined, the edge computing device needs to traverse all one hundred cultural elements and perform complex frustum geometric constraint judgments on each cultural element, which consumes a large amount of computing resources and may cause delays in VR content generation. However, if this solution is adopted, first construct an octree spatial index structure to organize the position information of these one hundred cultural elements. When the viewing direction of the tourist changes, first use the frustum and the axis-aligned bounding box of the cultural element to perform a quick query and intersection test in the octree, and possibly screen out only ten candidate cultural elements. Then, only need to perform accurate geometric constraint judgments on these ten candidate cultural elements, such as the point-frustum test. Thus, the number of cultural elements that need to perform accurate geometric calculations is reduced from one hundred to ten, the amount of calculation is greatly reduced, the efficiency of determining the displayed cultural elements is effectively improved, and the real-time and smoothness of virtual reality content generation are ensured.

[0061] In some embodiments, step A4 includes: A401. Calculate the distance between each displayed cultural element and the tourist's virtual reality device according to the distribution position of each displayed cultural element; A402. Determine the distance level according to the distance; A403. Determine the initial fineness level of each displayed cultural element according to the preset priority and distance level of each displayed cultural element; A404. Obtain the moving speed of the tourist's virtual reality device to correct the initial fineness level of each displayed cultural element and obtain the final fineness level.

[0062] Among them, in step A401, the distribution position of the displayed cultural element and the position of the tourist's virtual reality device are used for distance calculation. Specifically, the spatial coordinates of the cultural element and the virtual reality device are obtained, and the Euclidean distance between the two points is calculated as the distance.

[0063] Among them, in step A402, the distance level can be determined based on a preset distance threshold range. Multiple distance levels can be set in advance, and a corresponding distance range is set for each distance level. According to the distance range in which the calculated distance falls, the distance level is determined. For example, three distance levels can be preset in advance: close distance, medium distance, and long distance, and a distance range is set for each level. For example, 0 - 10 meters is the close distance, 10 - 30 meters is the medium distance, and more than 30 meters is the long distance. The calculated distance value will be compared with these preset ranges to determine the distance level to which the cultural element belongs.

[0064] Among them, in step A403, the determination of the initial fineness level comprehensively considers the preset priority of the cultural element and the distance level determined in step A402. The preset priority of the cultural element can be set according to its cultural importance (the cultural importance can be determined in advance by an expert group). For example, important cultural buildings can be set to a high priority, while general decorations can be set to a low priority. The distance level reflects the distance between the cultural element and the tourist. The priority and the distance level will be combined, for example, by means of a lookup table or weighted calculation, to determine an initial fineness level. Specifically, an initial fineness level can be set in advance for each combination of priority and distance level to form an initial fineness level lookup table, and the corresponding initial fineness level is found in the initial fineness level lookup table according to the actual priority and distance level; or, a weighted calculation is performed on the priority and the distance level to obtain a comprehensive grade value. Multiple comprehensive grade value ranges are set in advance, and a corresponding initial fineness level is set for each comprehensive grade value range. According to the comprehensive grade value range in which the actual calculated comprehensive grade value falls, the corresponding initial fineness level is determined.

[0065] Among them, in step A404, the moving speed of the tourist's virtual reality device is obtained and used to correct the initial fineness level. The moving speed can be obtained through the sensors or positioning system built into the virtual reality device. The obtained speed value is compared with a preset speed threshold. If the moving speed is greater than the speed threshold, it indicates that the tourist is in a fast moving state, and the fineness attenuation coefficient will be calculated based on the moving speed and the distance level. The greater the fineness attenuation coefficient, the greater the degree of reduction of the initial fineness level. For example, when the moving speed is faster or the distance level is higher, the fineness attenuation coefficient will increase accordingly, thus more significantly reducing the fineness level of the cultural element. If the moving speed is not greater than the speed threshold, it indicates that the tourist is in a slow moving or stationary state, and the initial fineness level will be directly used as the final fineness level without adjustment.

[0066] Specifically, this solution adds a technical means of considering the moving speed of the tourist's virtual reality device to dynamically adjust the fineness level of cultural elements, in order to solve the problems that may be caused by the static fineness level strategy during the tourist's movement. First, step A401 calculates the distance between the displayed cultural element and the tourist's virtual reality device, which is one of the basic parameters for determining the fineness level. Cultural elements with a short distance usually require a higher fineness. Then, step A402 divides the calculated distance into different distance levels for subsequent setting of the fineness level based on the distance level. Next, step A403 combines the preset priority of the cultural element and the distance level determined in step A402 to determine an initial fineness level. The preset priority ensures that important cultural elements have a higher initial fineness, and the distance level makes a preliminary fineness adjustment based on the proximity of the element. Finally, step A404 obtains the moving speed of the tourist's virtual reality device and uses the moving speed to correct the initial fineness level obtained in step A403 to obtain the final fineness level. When the tourist's moving speed is fast, the fineness level of the cultural element can be appropriately reduced, especially for cultural elements at a long distance, because tourists moving fast may not notice the details of too high fineness. Reducing the fineness can save computing resources and ensure the smooth operation of the virtual reality system. Thus, while ensuring the smoothness of the virtual reality experience, the optimization of resource utilization efficiency is achieved. On the contrary, when the tourist's moving speed is slow or stationary, the fineness level of the cultural element can be appropriately increased to provide richer cultural details and enhance the immersive experience. By introducing the parameter of moving speed, the fineness level of cultural elements can be adjusted more intelligently and dynamically, thus effectively managing and optimizing the computing resources of edge computing devices while ensuring the quality of the tourist's virtual reality experience. Especially in the scenario of tourists' mobile visits, this dynamic adjustment strategy has more advantages.

[0067] In some specific embodiments, the distance levels are divided into three levels: short distance, medium distance, and long distance, with corresponding distance ranges of 0 - 10 meters, 10 - 30 meters, and greater than 30 meters respectively. The speed threshold is set at 1.5 meters per second. The preset priorities of cultural elements are divided into three levels: high, medium, and low. The initial fineness level is determined according to the combination of priority and distance level. For example, cultural elements with high priority and short distance are set to the highest fineness level, and cultural elements with low priority and long distance are set to the lowest fineness level. In step A404, if it is detected that the moving speed of the tourist is greater than 1.5 meters per second, the fineness attenuation coefficient is calculated based on the speed and distance level. For example, a calculation formula for the fineness attenuation coefficient can be designed such that the greater the speed and the higher the distance level, the greater the attenuation coefficient. The attenuation coefficient is used to reduce the initial fineness level to obtain the final fineness level. For example, the initial fineness level is multiplied by the attenuation coefficient to obtain the final fineness level. If the moving speed of the tourist is not greater than 1.5 meters per second, the initial fineness level is directly used as the final fineness level. In this way, the fineness level of cultural elements can be dynamically adjusted according to the moving state of the tourist and the distance from the cultural elements, achieving the optimal utilization of edge computing resources while ensuring the smoothness of the virtual reality experience.

[0068] In some possible embodiments, step A404 includes: Obtain the moving speed of the tourist's virtual reality device; Determine whether the moving speed is greater than the preset speed threshold; If the moving speed is greater than the preset speed threshold, calculate the fineness attenuation coefficient based on the moving speed and distance level, and reduce the initial fineness level according to the fineness attenuation coefficient to obtain the final fineness level; the greater the moving speed and the higher the distance level, the greater the fineness attenuation coefficient; If the moving speed is not greater than the preset speed threshold, use the initial fineness level as the final fineness level.

[0069] Among them, for obtaining the moving speed of the tourist's virtual reality device, as an implementation, it can be achieved through sensors built into the virtual reality device. For example, motion sensors such as acceleration sensors or gyroscopes can be used to capture the motion data of the device, and the moving speed of the device is calculated based on these data.

[0070] Among them, the preset speed threshold is a boundary value used to distinguish the moving states of tourists, which can be set according to the actual application scenarios and requirements. For example, it can be set to 1.5 m / s - 2 m / s. When it is determined that the moving speed is greater than the preset speed threshold, it indicates that the tourist is in a fast moving state. At this time, the fineness attenuation coefficient is calculated. The calculation of this coefficient takes into account two factors: moving speed and distance level. The greater the moving speed and the higher the distance level, the greater the fineness attenuation coefficient. The fineness attenuation coefficient is used to reduce the initial fineness level to obtain the final fineness level. For example, the initial fineness level can be multiplied by the fineness attenuation coefficient to obtain the final fineness level (at this time, each fineness level is represented by a level value. Multiplying the initial fineness level by the fineness attenuation coefficient can obtain a calculated level value, and the fineness level corresponding to the level value closest to this calculated level value is used as the final fineness level; for example, it is set that there are five fineness levels, and the corresponding level values are 1, 2, 3, 4, and 5 respectively. The level value corresponding to the initial fineness level is 5, and the fineness attenuation coefficient is 0.85. The calculated level value obtained by multiplication is 4.25, and the level value closest to 4.25 is 4. Therefore, the fineness level corresponding to the level value 4 is used as the final fineness level). When it is determined that the moving speed is not greater than the preset speed threshold, it indicates that the tourist is in a relatively stationary or slow moving state. At this time, the initial fineness level remains unchanged and is used as the final fineness level.

[0071] In some specific embodiments, the calculation method of the fineness attenuation coefficient can be flexibly designed according to actual requirements. For example, various functional forms such as linear functions, exponential functions, or piecewise functions can be used to establish the mapping relationship between the fineness attenuation coefficient and the moving speed and distance level. As a preferred embodiment, a piecewise function can be used to calculate the fineness attenuation coefficient. For example, multiple speed intervals and distance levels can be preset in advance, and a preset fineness attenuation coefficient value is assigned to each combination of speed interval and distance level. When the fineness attenuation coefficient needs to be calculated, first determine the speed interval and distance level to which it belongs according to the current moving speed and distance level, and then look up the table to obtain the corresponding preset fineness attenuation coefficient value as the calculation result. Using a piecewise function to calculate the fineness attenuation coefficient for the initial fineness level can more precisely control the adjustment process of the fineness level to meet the requirements in different application scenarios.

[0072] In some embodiments, step A5 includes: A501. Select the cultural element model corresponding to the determined fineness level from the preset cultural element model library; A502. Select a texture map corresponding to the selected cultural element model at the corresponding level of fineness from a preset texture library, and map the texture map onto the cultural element model to generate a visual resource of the cultural element with the corresponding level of fineness; A503. Integrate the generated visual resources of each cultural element in terms of spatial position to construct virtual reality scene content that matches the current line-of-sight area.

[0073] Among them, in step A501, a cultural element model library is established in advance, and the library stores multiple models of the same cultural element at different levels of fineness. The levels of fineness are divided from low to high, and the number of polygons (i.e., the number of faces) of the corresponding models increases from less to more. When the level of fineness is determined, the system selects the corresponding cultural element model from the model library to ensure that the model fineness matches the level.

[0074] Among them, in step A502, a texture library is also established in advance, and the texture library stores texture maps of different levels of fineness that match the cultural element models. The level of fineness of the texture map corresponds to the level of fineness of the cultural element model, ensuring that the texture details are coordinated with the model fineness. The texture map is mapped onto the selected cultural element model, and a visual resource of the cultural element is thus generated.

[0075] Among them, in step A503, the visual resources of each cultural element are integrated in the virtual space, and the integration process takes into account the spatial position relationship between the cultural elements and the range of the line-of-sight area. Through the spatial position integration, virtual reality scene content that matches the current line-of-sight area of the tourist is constructed.

[0076] Specifically, for step A501, the cultural element model library is constructed as follows. For each cultural element, such as Dongzhai architecture, ethnic costumes, or traditional handicrafts, modelers will pre-produce multiple 3D models with different levels of detail. For example, for the cultural element of the drum tower, models with low, medium, and high levels of detail can be made. The low-detail model has fewer polygons and relatively simplified details, while the high-detail model has more polygons and rich details. These models are stored in the cultural element model library classified by the level of detail. In step A502, the texture library is constructed in a similar way. For different levels of detail models of each cultural element, graphic designers will produce matching texture maps. For example, for the high-detail model of the drum tower, a high-resolution texture map will be produced to clearly show the carved patterns and color details of the drum tower; for the low-detail model, a lower-resolution texture map will be used. During content generation, the level of detail is determined, and the model and texture map are selected and combined to ensure that the level of detail of the generated visual resources is adapted to the performance of the current device and the network conditions. In the spatial location integration process of step A503, using the spatial coordinate system of the virtual reality scene, the generated visual resources of each cultural element are placed at predetermined spatial positions. These spatial position information corresponds to the actual geographical locations of the cultural elements in the real Dongzhai scenic area. The parameters of the line of sight area are considered to ensure that the finally constructed virtual reality scene content conforms to the current viewing perspective of the tourist.

[0077] In some specific embodiments, for the cultural element of the drum tower, the level of detail is determined to be medium. In step A501, the cultural element model library in the system is accessed, and the medium-detail model of the drum tower is selected. The number of polygons and the level of detail of this model are moderate, taking into account both the visual effect and the rendering efficiency. Subsequently, in step A502, the texture library is accessed, and a medium-resolution texture map matching the medium-detail model of the drum tower is selected and mapped onto the surface of the drum tower model, and the visual resource of the drum tower is thus generated. For other displayed cultural elements, such as Dongzhai folk houses, terraced fields, etc., the selection and mapping operations of the model and texture map are also performed to generate their respective visual resources. Finally, in step A503, these generated visual resources of the drum tower, folk houses, terraced fields, etc. are reasonably arranged and integrated in the virtual space according to the preset spatial position information to form virtual reality scene content that conforms to the current line of sight of the tourist. Thus, the virtual reality scene seen by the tourist not only ensures a smooth VR experience but also displays rich details of Dong culture.

[0078] Reference Figure 2 , this application also proposes a device for generating Dong cultural content information, which is applied to an edge computing device in a Dongzhai scenic area to generate virtual reality content of Dong culture for tourists. The device includes: Position and line-of-sight acquisition module 1, which is used to acquire the position information and line-of-sight direction information of the tourist's virtual reality device (for the specific process, refer to step A1 in the previous text); Scene loading module 2, which is used to load various cultural elements of the corresponding Dong culture virtual reality scene according to the position information (for the specific process, refer to step A2 in the previous text); Display element determination module 3, which is used to determine the cultural elements within the tourist's line-of-sight area based on the line-of-sight direction information and the distribution positions of the loaded various cultural elements, and record them as display cultural elements (for the specific process, refer to step A3 in the previous text); Detail determination module 4, which is used to determine the detail levels of the various display cultural elements according to the preset priorities and distribution positions of the display cultural elements (for the specific process, refer to step A4 in the previous text); Content generation module 5, which is used to generate virtual reality content corresponding to the various display cultural elements according to the determined detail levels (for the specific process, refer to step A5 in the previous text); Content transmission module 6, which is used to transmit the generated virtual reality content to the tourist's virtual reality device (for the specific process, refer to step A6 in the previous text).

[0079] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only illustrative. For example, the division of the units is only a logical function division, and there can be other division methods in actual implementation. For another example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point, the displayed or discussed coupling or direct coupling or communication connection between each other can be through some communication interfaces. The indirect coupling or communication connection of the devices or units can be in an electrical, mechanical or other form.

[0080] In addition, the units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units. They can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0081] Furthermore, in each embodiment of the present application, the various functional modules can be integrated together to form an independent part, or each module can exist alone, or two or more modules can be integrated to form an independent part.

[0082] In this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0083] The above are only embodiments of the present application and are not intended to limit the protection scope of the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

Claims

1. A method for generating Dong ethnic culture content information, which is applied to edge computing devices in Dong ethnic villages scenic spots to generate virtual reality content of Dong ethnic culture for tourists, and is characterized in that, The method includes: A1. Obtain the location information and line-of-sight direction information of the tourist's virtual reality device; A2. According to the location information, load various cultural elements of the corresponding Dong culture virtual reality scene; A3. According to the line-of-sight direction information and the distribution positions of the loaded various cultural elements, determine the cultural elements within the tourist's line-of-sight area, denoted as display cultural elements; A4. According to the preset priorities and distribution positions of the respective display cultural elements, determine the level of detail of each display cultural element; A5. According to the determined level of detail, generate virtual reality content corresponding to each display cultural element; A6. Transmit the generated virtual reality content to the tourist's virtual reality device.

2. The method for generating Dong ethnic culture content information according to claim 1, wherein Step A2 includes: A201. According to the location information, screen out a set of cultural elements related to the location information from the virtual reality content library; A202. Based on the superiority parameters of each cultural element, sort the cultural elements in the set of cultural elements, the higher the superiority, the higher the ranking; the superiority parameters include historical access frequency, expert scoring, and Dong culture representativeness scores; A203. According to the sorting result and the remaining storage space of the edge computing device, load a number of the top-ranked cultural elements.

3. A method for generating Dong ethnic culture content information according to claim 2, characterized in that, Step A202 includes: B1. According to the superiority parameters, calculate the comprehensive superiority score of each cultural element in the set of cultural elements through a weighted algorithm; B2. According to the comprehensive superiority score, sort the cultural elements in the set of cultural elements in descending order.

4. A method for generating Dong ethnic culture content information according to claim 3, characterized in that, After step B1 and before step B2, there is also a step: B3. Obtain the portrait data of the tourist to estimate the personalized preference score of each cultural element in the set of cultural elements by the tourist; B4. According to the personalized preference score, correct the comprehensive superiority score of each cultural element in the set of cultural elements.

5. A method for generating Dong ethnic culture content information according to claim 1, characterized in that Step A3 includes: A301. According to the line-of-sight direction information and the preset field-of-view angle parameters, construct a frustum; A302. Traverse each loaded cultural element, and according to the distribution position of each cultural element, judge whether each cultural element meets the geometric constraint conditions of the frustum range, and determine the cultural elements that meet the geometric constraint conditions of the frustum range as display cultural elements.

6. A method for generating Dong ethnic culture content information according to claim 5, characterized in that Step A302 includes: Construct a spatial index structure containing the distribution positions of each loaded cultural element; Based on the spatial index structure, use the vertex coordinates of the frustum and the bounding box information of each cultural element to screen out a set of candidate cultural elements that may intersect with the frustum; Traverse each cultural element in the set of candidate cultural elements, and according to the distribution position of each cultural element, judge whether each cultural element meets the geometric constraint conditions of the frustum range, and determine the cultural elements that meet the geometric constraint conditions of the frustum range as display cultural elements.

7. A method for generating Dong ethnic culture content information according to claim 1, characterized in that Step A4 includes: A401. According to the distribution positions of the respective display cultural elements, calculate the distance between each display cultural element and the tourist's virtual reality device; A402. According to the distance, determine the distance level; A403. According to the preset priorities and distance levels of the respective display cultural elements, determine the initial level of detail of each display cultural element; A404. Obtain the moving speed of the tourist's virtual reality device to correct the initial fineness level of each displayed cultural element and obtain the final fineness level.

8. A method for generating Dong ethnic culture content information according to claim 7, characterized in that, Step A404 includes: Obtain the moving speed of the tourist's virtual reality device; Determine whether the moving speed is greater than a preset speed threshold; If the moving speed is greater than the preset speed threshold, calculate a fineness attenuation coefficient according to the moving speed and the distance level, and reduce the initial fineness level according to the fineness attenuation coefficient to obtain the final fineness level; the greater the moving speed and the higher the distance level, the greater the fineness attenuation coefficient; If the moving speed is not greater than the preset speed threshold, use the initial fineness level as the final fineness level.

9. A method for generating Dong ethnic culture content information according to claim 1, characterized in that, Step A5 includes: A501. Select a cultural element model corresponding to the determined fineness level from a preset cultural element model library; A502. Select a texture map corresponding to the determined fineness level from a preset texture library according to the selected cultural element model, and map the texture map onto the cultural element model to generate a cultural element visual resource with the corresponding fineness level; A503. Integrate the spatial positions of the generated cultural element visual resources to construct virtual reality scene content matching the current line-of-sight area.

10. A Dong ethnic culture content information generation device, which is applied to edge computing devices in Dong ethnic villages scenic spots to generate virtual reality content of Dong ethnic culture for tourists, is characterized in that, The device includes: A position and line-of-sight acquisition module, configured to acquire the position information and line-of-sight direction information of the tourist's virtual reality device; A scene loading module, configured to load various cultural elements of the corresponding Dong ethnic culture virtual reality scene according to the position information; A display element determination module, configured to determine the cultural elements within the tourist's line-of-sight area according to the line-of-sight direction information and the distribution positions of the loaded various cultural elements, and record them as displayed cultural elements; A fineness determination module, configured to determine the fineness level of each displayed cultural element according to the preset priority and distribution position of each displayed cultural element; A content generation module, configured to generate virtual reality content corresponding to each displayed cultural element according to the determined fineness level; A content transmission module, configured to transmit the generated virtual reality content to the tourist's virtual reality device.

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