A method and system for digital display of a tourism product

Abstract

The application relates to the technical field of digital display, and discloses a digital display method and system for a tourism product, which comprises the following steps: performing scene semantic analysis on a real scene image of a target tourism scenic spot, identifying key landscape elements and spatial relationships to obtain scene structure data; fusing tourism product digital display content with the scene structure data in space to determine spatial anchor points; obtaining dynamic display content based on real-time environmental state data and adaptive rendering based on the real-time environmental state data; packaging display action sequences and trigger conditions into interactive behavior logic and embedding to obtain intelligent interactive content; superimposing the intelligent interactive content on the real scene image based on the spatial anchor points to obtain a real display picture; and encoding a real-time interactive intention of a user into a control instruction to drive the intelligent interactive content in the real display picture to execute corresponding display actions; and the application can improve the efficiency of digital display of the tourism product.

Description

Technical Field

[0001] This invention relates to the field of digital display technology, and in particular to a method and system for digitally displaying tourism products. Background Technology

[0002] Existing digital display technologies for tourism products mostly use a simple overlay of static digital materials and real-world images. They do not conduct in-depth semantic analysis of the real-world images of the target tourist attractions, and cannot accurately identify key landscape elements and spatial relationships between elements. This results in poor compatibility between digital display content and the layout of the real-world space, often leading to problems such as positional misalignment and hierarchical confusion, creating a sense of visual disconnect and making it difficult for users to intuitively perceive the connection value between tourism products and scenic spots.

[0003] Existing technologies lack the ability to dynamically adapt to the real-time environmental conditions of tourist attractions. The visual effects of digitally displayed content are fixed and cannot be adjusted according to the real-time ambient light, main color tone, and texture complexity of the attraction, which can easily create visual conflicts with the current environment. At the same time, the interaction logic design is simple, only supporting basic click triggers, and does not combine the sequence of display actions with various triggering conditions such as environment, time sequence, and user interaction. It is difficult to accurately translate the user's real-time interaction intentions into corresponding display actions, resulting in insufficient display flexibility, low user participation, and failure to fully leverage the advantages of digital display. Therefore, how to improve the efficiency of digital display of tourism products has become an urgent problem to be solved. Summary of the Invention

[0004] This invention provides a method and system for digitally displaying tourism products to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides a method for digitally displaying tourism products, comprising:

[0006] S1. Perform scene semantic analysis on the real-scene images of the target tourist attraction, identify key landscape elements in the real-scene images and the spatial relationships between the key landscape elements, and obtain scene structure data of the target tourist attraction.

[0007] S2. Spatially fuse the digital display content of tourism products with the scene structure data to determine the spatial anchor point of the digital display content in the real-world image.

[0008] S3. Based on the real-time environmental status data of the target tourist attraction, perform state-adaptive rendering on the digital display content to obtain the dynamic display content of the tourism product.

[0009] S4. Package the display action sequence and triggering conditions of the tourism product into the interactive behavior logic of the tourism product, and embed the interactive behavior logic into the dynamic display content to obtain the intelligent interactive content of the tourism product.

[0010] S5. Using the spatial anchor point as a reference, the intelligent interactive content is superimposed onto the real-scene image to obtain a real-world display of the tourism product.

[0011] S6. Encode the user's real-time interactive intent into control instructions for the tourism product, and drive the intelligent interactive content in the real-world display screen to execute the corresponding display actions.

[0012] In a preferred embodiment, the step of performing scene semantic analysis on the real-scene images of the target tourist attraction to identify key landscape elements in the real-scene images and the spatial relationships between the key landscape elements, thereby obtaining scene structure data of the target tourist attraction, includes:

[0013] Collect real-scene images of the target tourist attraction, and divide the real-scene images into candidate areas of the target tourist attraction through pixel-level segmentation;

[0014] Based on the color consistency and texture continuity characteristics of the candidate areas, the candidate areas are filtered to obtain the key landscape elements of the target tourist attraction;

[0015] By analyzing the relative orientation and distance constraints among the key landscape elements, a spatial relationship descriptor for the target tourist attraction is obtained.

[0016] The attributes of the key landscape elements and the spatial relationship descriptors are structured and parsed to obtain the scene structure data of the target tourist attraction.

[0017] In a preferred embodiment, the step of spatially fusing the digital display content of tourism products with the scene structure data to determine the spatial anchor point of the digital display content in the real-world image includes:

[0018] The digital display content of tourism products is obtained, and the semantic description of the digital display content is matched with the key landscape elements to obtain the candidate fusion position of the tourism products.

[0019] Verify the spatial topological relationship between the scene structure data and the candidate fusion locations, and filter out potential anchor point regions with preset spatial constraints;

[0020] Visual saliency detection is performed on the visual attributes of the digitally displayed content and the background environmental features of the potential anchor point area to determine the optimal spatial positioning coordinates of the tourism product.

[0021] By binding the optimal spatial positioning coordinates and the hierarchical information of the digital display content, the spatial anchor point of the digital display content in the real-world image is obtained.

[0022] In a preferred embodiment, the step of performing state-adaptive rendering on the digital display content based on the real-time environmental status data of the target tourist attraction to obtain the dynamic display content of the tourism product includes:

[0023] The ambient light brightness parameter, ambient color tone parameter, and ambient texture complexity parameter of the real-time environmental status data of the target tourist attraction are extracted to obtain the environmental feature description set of the target tourist attraction;

[0024] Based on the environmental feature description set, a rendering adaptation analysis is performed on the digital display content to obtain the visual fusion coefficient of the target tourist attraction and the tourism product;

[0025] Based on the visual fusion coefficient, the multi-scale feature layer of the digital display content is integrated into the corresponding area of ​​the real-scene image to obtain the intermediate rendering content of the tourism product;

[0026] Verify the consistency between the intermediate rendered content and the current color characteristics of the real-world image to obtain the dynamic display content of the tourism product.

[0027] In a preferred embodiment, the formula for calculating the visual fusion coefficient is:

[0028] ;

[0029] in, This represents the visual fusion coefficient. This represents the ambient light brightness parameter. This represents the dominant color tone parameter of the environment. This represents the environmental texture complexity parameter. This indicates the preset brightness reference value. This represents the preset baseline value for texture complexity. This represents the preset distribution adjustment factor. Represents an exponential function. Represents the natural logarithm. Represents the hyperbolic tangent function. It represents pi (π).

[0030] In a preferred embodiment, the step of packaging the display action sequence and triggering conditions of the tourism product into interactive behavior logic of the tourism product, and embedding the interactive behavior logic into the dynamic display content to obtain the intelligent interactive content of the tourism product, includes:

[0031] Extract the basic action units and execution order relationships of the action sequences displayed in the tourism products to obtain the action descriptor set of the tourism products;

[0032] The triggering conditions of the tourism products are decomposed into environmental triggering, user interaction, and time-series control types to obtain the condition types of the triggering conditions;

[0033] A correlation analysis is performed on the condition types and the display action sequences to establish a condition-action lookup table for the tourism products;

[0034] Based on the condition-action lookup table, construct the interactive behavior logic of the tourism product;

[0035] The interactive behavior logic is serialized into interactive description data of the tourism product, and the interactive description data is injected into the metadata layer of the dynamically displayed content to obtain the intelligent interactive content of the tourism product.

[0036] In a preferred embodiment, constructing the interactive behavior logic of the tourism product based on the condition-action lookup table includes:

[0037] Based on the execution parameters and state transition rules of the basic action unit, assign a corresponding behavior identifier to the basic action unit;

[0038] Based on the condition-action lookup table, priority analysis is performed on the triggering conditions to obtain the execution order of the triggering conditions;

[0039] The execution order and the behavior identifier are encoded into the initial behavior logic of the tourism product;

[0040] The completeness of the initial behavioral logic is verified to obtain the interactive behavioral logic of the tourism product.

[0041] In a preferred embodiment, the step of overlaying the intelligent interactive content onto the real-world image based on the spatial anchor point to obtain a realistic display of the tourism product includes:

[0042] The coordinate information of the spatial anchor point and the scene structure data are transformed to obtain the mapping relationship between the local coordinate system in the intelligent interactive content and the global coordinate system in the real scene image;

[0043] Based on the mapping relationship, the intelligent interactive content is subjected to perspective transformation, and the scale of the transformed intelligent interactive content is adjusted to obtain the optimized interactive content of the tourism product.

[0044] The optimized interactive content and the real-scene image are fused at the pixel level, and the visual boundaries generated during the fusion process are eliminated to obtain the fused image data of the tourism product.

[0045] The fused image data is formatted and encapsulated to obtain a real-world display image of the tourism product.

[0046] In a preferred embodiment, encoding the user's real-time interactive intent into control commands for the tourism product, and driving the intelligent interactive content in the real-world display screen to execute corresponding display actions, includes:

[0047] Decompose the type and spatial location features of the user's real-time interaction intent to obtain the user's interaction description information;

[0048] The interaction description information and the interactive behavior logic are associated and matched to obtain the target behavior identifier and target execution parameters of the interaction description information.

[0049] The target behavior identifier and the target execution parameters are encapsulated into control instructions for the tourism product;

[0050] The control command is sent to the driver terminal of the intelligent interactive content to display the corresponding display action in the real display screen.

[0051] To address the above problems, the present invention also provides a digital display system for tourism products, the system comprising:

[0052] The image analysis module is used to perform scene semantic analysis on the real-scene images of the target tourist attraction, identify key landscape elements in the real-scene images and the spatial relationships between the key landscape elements, and obtain the scene structure data of the target tourist attraction.

[0053] The spatial fusion module is used to spatially fuse the digital display content of tourism products with the scene structure data to determine the spatial anchor point of the digital display content in the real-world image.

[0054] The content rendering module is used to perform state-adaptive rendering of the digital display content based on the real-time environmental status data of the target tourist attraction, so as to obtain the dynamic display content of the tourism product.

[0055] The intelligent interaction module is used to package the display action sequence and triggering conditions of the tourism product into the interactive behavior logic of the tourism product, and embed the interactive behavior logic into the dynamic display content to obtain the intelligent interactive content of the tourism product.

[0056] The display overlay module is used to overlay the intelligent interactive content onto the real-scene image based on the spatial anchor point to obtain a real-world display of the tourism product.

[0057] The display action execution module is used to encode the user's real-time interactive intent into control instructions for the tourism product, and drive the intelligent interactive content in the real-world display screen to execute the corresponding display actions.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] 1. This invention performs scene semantic analysis on real-world images of target tourist attractions to accurately identify key landscape elements and the spatial relationships between them, obtaining structured scene structure data. It then spatially integrates the digital display content of tourism products with the scene structure data to determine spatial anchor points, ensuring accurate positioning of the digital content in the real-world setting and avoiding visual fragmentation. Simultaneously, based on real-time environmental status data of the attraction, it extracts parameters such as ambient light intensity, primary color tone, and texture complexity for adaptive rendering, ensuring visual harmony between the dynamic display content and the real-world environment, thereby enhancing users' perception of the connection between tourism products and the attraction.

[0060] 2. This invention packages the sequence of actions for displaying tourism products with multiple types of triggering conditions into interactive behavioral logic, embeds it into dynamic display content to form intelligent interactive content, and enriches the interactive dimensions; it overlays the intelligent interactive content onto the real scene based on spatial anchor points to obtain a realistic display image, and then encodes the user's real-time interactive intentions into control commands to drive the intelligent interactive content to perform corresponding actions, thereby improving the flexibility of the display and user participation, allowing the value of tourism products to be fully conveyed in a dynamic and interactive way, and effectively optimizing the digital display effect. Attached Figure Description

[0061] Figure 1 This is a flowchart illustrating a method for digitally displaying tourism products according to an embodiment of the present invention.

[0062] Figure 2 A functional module diagram of a digital display system for tourism products provided in an embodiment of the present invention;

[0063] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0064] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0065] This application provides a method for digitally displaying tourism products. The executing entity of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the method for digitally displaying tourism products can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0066] Reference Figure 1 The diagram shown is a flowchart illustrating a method for digitally displaying tourism products according to an embodiment of the present invention. In this embodiment, the method for digitally displaying tourism products includes:

[0067] S1. Perform scene semantic analysis on the real-scene images of the target tourist attraction, identify key landscape elements in the real-scene images and the spatial relationships between the key landscape elements, and obtain scene structure data of the target tourist attraction.

[0068] In this embodiment of the invention, the step of performing scene semantic analysis on the real-scene images of the target tourist attraction, identifying key landscape elements in the real-scene images and the spatial relationships between the key landscape elements, and obtaining scene structure data of the target tourist attraction includes:

[0069] Collect real-scene images of the target tourist attraction, and divide the real-scene images into candidate areas of the target tourist attraction through pixel-level segmentation;

[0070] Based on the color consistency and texture continuity characteristics of the candidate areas, the candidate areas are filtered to obtain the key landscape elements of the target tourist attraction;

[0071] By analyzing the relative orientation and distance constraints among the key landscape elements, a spatial relationship descriptor for the target tourist attraction is obtained.

[0072] The attributes of the key landscape elements and the spatial relationship descriptors are structured and parsed to obtain the scene structure data of the target tourist attraction.

[0073] Using a high-definition panoramic camera equipped with a 16K resolution sensor, shooting points were evenly set up at 3-meter intervals around the target tourist attraction. Each point captured images from three angles: horizontal, 15° elevation, and 15° depression, ensuring coverage of all core areas within the attraction, including buildings, vegetation, waterways, and roads. After acquisition, image stitching technology was used to seamlessly merge the multi-view images into a complete real-scene image. Pixel-level segmentation was performed using a pixel-by-pixel comparison method, based on the RGB color and brightness differences between adjacent pixels. When the color and brightness differences of two adjacent pixels were both below preset fixed values, they were determined to be the same continuous area. This rule was applied row by row and column by column to traverse the entire real-scene image, dividing it into multiple independent and continuous small areas. Each small area was labeled with its corresponding horizontal and vertical pixel ranges, resulting in candidate areas for the target tourist attraction.

[0074] For each candidate region, 20 sampled pixels are evenly selected within the region. The average RGB color value of these 20 sampled pixels is calculated. Then, the color difference between each sampled pixel and the average value is calculated. If the color difference of all sampled pixels is within a fixed threshold, the region is considered to meet color consistency. Simultaneously, the texture arrangement pattern of pixels within the region is observed, and the repetition frequency of the same basic texture pattern within the region is counted. If the repetition frequency exceeds a preset fixed value, the region is considered to meet texture continuity. Only candidate regions that simultaneously meet both color consistency and texture continuity are retained, while regions that do not meet either condition are eliminated. The retained regions are labeled with their corresponding landscape types to obtain the key landscape elements of the target tourist attraction.

[0075] A pixel coordinate system is established with the top left corner of the real-scene image as the origin, the horizontal axis as the X-axis, and the vertical axis as the Y-axis. The boundary pixel coordinates of each key landscape element are determined, and the center pixel coordinates of the elements are calculated. The relative orientation is determined by comparing the center pixel coordinates of different elements: if the X-center value of element A is less than that of element B and the difference in Y-center values ​​is within a fixed range, element A is determined to be to the left of element B; if the Y-center value of element A is less than that of element B and the difference in X-center values ​​is within a fixed range, element A is determined to be above element B; if the X-center value of element A is greater than that of element B and the Y-center value is less than that of element B, element A is determined to be to the lower right of element B. The distance between the center pixel coordinates of two elements is calculated as the square root of the sum of the squares of the horizontal and vertical coordinate differences, yielding the specific distance value. The relative orientation and distance values ​​of each key landscape element with all other elements are recorded in the format "Element No. 1 - Relative Orientation - Element No. 2 - Distance" to obtain the spatial relationship descriptor of the target tourist attraction.

[0076] Extract the attribute information for each key landscape element, including landscape type, pixel size, and core features, and organize it into an attribute table according to the structure of "element number - landscape type - horizontal pixel count - vertical pixel count - core features". Associate spatial relationship descriptors with the attribute table, for example, "element 3 is northeast of element 5, 80 pixels away". In ascending order of element number, integrate the attribute information with the corresponding spatial relationship descriptors into a structured document containing two levels: "element attributes" and "spatial associations", to obtain the scene structure data of the target tourist attraction.

[0077] The beneficial effects include ensuring complete coverage of the scenic spot with precise boundaries through high-definition panoramic acquisition and pixel-by-pixel segmentation; effectively eliminating invalid areas and accurately identifying key landscape elements based on dual screening criteria of color and texture; making spatial relationship descriptors objective and traceable by using pixel coordinate system to quantify and analyze relative orientation and distance; and providing high-precision data support for the spatial integration of digital display content of tourism products with real-world images, thus ensuring the positioning accuracy and visual coordination of digital content in the real scene.

[0078] S2. Spatially fuse the digital display content of tourism products with the scene structure data to determine the spatial anchor point of the digital display content in the real-world image.

[0079] In this embodiment of the invention, the step of spatially fusing the digital display content of tourism products with the scene structure data to determine the spatial anchor point of the digital display content in the real-world image includes:

[0080] The digital display content of tourism products is obtained, and the semantic description of the digital display content is matched with the key landscape elements to obtain the candidate fusion position of the tourism products.

[0081] Verify the spatial topological relationship between the scene structure data and the candidate fusion locations, and filter out potential anchor point regions with preset spatial constraints;

[0082] Visual saliency detection is performed on the visual attributes of the digitally displayed content and the background environmental features of the potential anchor point area to determine the optimal spatial positioning coordinates of the tourism product.

[0083] By binding the optimal spatial positioning coordinates and the hierarchical information of the digital display content, the spatial anchor point of the digital display content in the real-world image is obtained.

[0084] Digital display content for corresponding tourism products is retrieved from the digital resource library of tourism products. This content includes 3D models, dynamic graphic descriptions, and service information pop-ups. Semantic descriptions for each type of content are extracted; for example, the semantic description of a 3D homestay model is "lakeside homestay accommodation unit," and the semantic description of a food set meal graphic is "introduction to a lake-themed dining set meal." These semantic descriptions are then compared word-by-word with the semantic tags of key landscape elements, such as "artificial lake," "lakeside dining area," and "viewing platform." If the semantic description of the digital display content is directly related to the semantic tag of a key landscape element (e.g., "lakeside homestay" is associated with "artificial lake," and "lake-themed dining set meal" is associated with "lakeside dining area"), then a pre-defined area of ​​20-50 pixels horizontally and vertically surrounding that key landscape element is marked as the adaptation area. All adaptation areas together constitute the candidate integration location for the tourism product.

[0085] The spatial topological relationships of key landscape elements are extracted from the scene structure data, including the relative orientation between elements (e.g., "the artificial lake is north of the lakeside dining area"), distance constraints (e.g., "the viewing platform is 30 pixels away from the edge of the artificial lake"), and the spatial boundaries of the elements themselves (e.g., "the lakeside dining area covers a horizontal pixel range of 100-200 and a vertical pixel range of 200-300"). The pixel coordinate range of the candidate fusion locations is matched and verified against these topological relationships. The preset spatial constraint is that "the candidate fusion location must be within a reasonable radiation range of the associated key landscape element, and not exceed the distance limit between the element and its adjacent elements, while not covering the core visual area of ​​the key landscape element." For example, "the candidate fusion location of the lakeside homestay must be within 20-50 pixels south of the artificial lake, and not cover the core water area of ​​the artificial lake (300-400 pixels horizontally and 250-350 pixels vertically)." All candidate fusion locations that meet this constraint are selected and identified as potential anchor areas for tourism products.

[0086] Visual attributes of the digital display content are extracted, including the main color scheme (e.g., a warm yellow for the homestay model), overall size (e.g., 80 pixels horizontally, 60 pixels vertically), and visual style (e.g., minimalist Chinese style). Simultaneously, background environmental characteristics of each potential anchor point area are collected, including background color (e.g., a light gray walkway background for the lakeside area), background texture (e.g., the brick and stone texture of the walkway), and background element density (e.g., no dense vegetation obstructing the view). Visual saliency is assessed using visual contrast analysis. First, the contrast between the main color scheme of the digital display content and the background color is determined to be within a preset appropriate range—neither too low a contrast causing the product to be obscured by the background nor too high a contrast creating visual discontinuity. Next, the size of the digital display content is confirmed to be compatible with the background space, not exceeding the background boundary and having a reasonable proportion. Finally, the visual style is checked for harmony with the background environment; for example, a Chinese-style homestay harmonizes with a Chinese-style lakeside landscape. The pixel coordinates (e.g., horizontal coordinate X=600, vertical coordinate Y=400) corresponding to the potential anchor point areas that comprehensively satisfy contrast, size compatibility, and style harmony are determined as the optimal spatial positioning coordinates for the tourism product.

[0087] The hierarchical information of the digital display content within the real-world imagery is determined. This hierarchical information is divided according to the spatial layers of the real-world imagery, into a foreground layer (e.g., near-view vegetation), a middle layer (e.g., visitor trails, small landscape features), and a background layer (e.g., distant mountains, tall buildings). The digital display content must be matched to the corresponding layer to avoid obscuring key landscapes or being excessively obscured. For example, a 3D homestay model should be adapted to the middle layer to avoid obscuring foreground vegetation or being covered by background mountains; a restaurant menu pop-up should be adapted to the upper layer to ensure clear visibility and not to permanently obscure the core landscape. The optimal spatial positioning coordinates (e.g., X=600, Y=400) are structurally bound to the corresponding hierarchical information (e.g., "middle layer") to form the correspondence data of "optimal spatial positioning coordinates - hierarchical information." This data serves as the spatial anchor point of the digital display content within the real-world imagery.

[0088] The beneficial effects are as follows: semantic consistency matching ensures a strong correlation between digital display content and key landscape elements, avoiding a disconnect between the fusion location and the scenic spot scene; spatial topology verification identifies potential anchor point areas that conform to the logic of the real-world space, ensuring the rationality of the fusion location; visual saliency detection ensures visual harmony between digital content and the background environment, highlighting tourism products without compromising the integrity of the real scene; binding hierarchical information ensures the correct spatial hierarchy when digital content is overlaid, and the resulting spatial anchor points accurately adapt to the real-world scene and the characteristics of tourism products, providing a stable and accurate positioning benchmark for subsequent intelligent interactive content overlay on real-world images, and improving the spatial adaptability and visual comfort of digital displays of tourism products.

[0089] S3. Based on the real-time environmental status data of the target tourist attraction, perform state-adaptive rendering on the digital display content to obtain the dynamic display content of the tourism product.

[0090] In this embodiment of the invention, the step of performing state-adaptive rendering on the digital display content based on the real-time environmental status data of the target tourist attraction to obtain the dynamic display content of the tourism product includes:

[0091] The ambient light brightness parameter, ambient color tone parameter, and ambient texture complexity parameter of the real-time environmental status data of the target tourist attraction are extracted to obtain the environmental feature description set of the target tourist attraction;

[0092] Based on the environmental feature description set, a rendering adaptation analysis is performed on the digital display content to obtain the visual fusion coefficient of the target tourist attraction and the tourism product;

[0093] Based on the visual fusion coefficient, the multi-scale feature layer of the digital display content is integrated into the corresponding area of ​​the real-scene image to obtain the intermediate rendering content of the tourism product;

[0094] Verify the consistency between the intermediate rendered content and the current color characteristics of the real-world image to obtain the dynamic display content of the tourism product.

[0095] The formula for calculating the visual fusion coefficient is as follows:

[0096] ;

[0097] in, This represents the visual fusion coefficient. This represents the ambient light brightness parameter. This represents the dominant color tone parameter of the environment. This represents the environmental texture complexity parameter. This indicates the preset brightness reference value. This represents the preset baseline value for texture complexity. This represents the preset distribution adjustment factor. Represents an exponential function. Represents the natural logarithm. Represents the hyperbolic tangent function. It represents pi (π).

[0098] Three types of sensors were evenly deployed around key landscape elements of the target tourist attraction. Ambient light intensity parameters were collected using a light sensor, which measured the ambient light intensity every 10 seconds, converting the collected light signals into numerical values ​​that directly reflected the ambient light intensity. Ambient dominant color parameters were collected using a color sensor, which collected color information from three different locations at each sensor placement point, extracted the RGB color values ​​for each location, and calculated the average value. This average value was the ambient dominant color parameter. Ambient texture complexity parameters were obtained through image analysis. 100×100 pixel local real-world images of the area surrounding the sensors were captured, and the frequency of repetition of the same basic texture pattern in the images was counted. A higher frequency indicated lower texture complexity, and a lower frequency indicated higher texture complexity. The ambient light intensity parameters, ambient dominant color parameters, and ambient texture complexity parameters were organized according to the structure of "parameter type - acquisition time - parameter value" to obtain the environmental feature description set of the target tourist attraction.

[0099] The ambient light intensity parameter, also known as the ambient light intensity parameter in the formula, is derived from the specific values ​​collected by the light sensor mentioned above, and this parameter has been included in the environmental characteristic description set of the target tourist attraction.

[0100] The dominant environmental color parameter, also known as the dominant environmental color parameter in the formula, is derived from the average RGB color value calculated by the color collector. This parameter is also part of the environmental feature description set of the target tourist attraction.

[0101] The environmental texture complexity parameter, also known as the environmental texture complexity parameter in the formula, is obtained by counting the number of repetitions of the basic texture pattern after capturing the local real-world image. This parameter is also included in the environmental feature description set of the target tourist attraction.

[0102] The preset brightness benchmark value, which is the preset brightness benchmark value in the formula, is determined by analyzing the historical ambient light brightness data of the target tourist attraction over the past year. The average brightness values ​​of the attraction at different times of different seasons are statistically analyzed, and the median value of all average values ​​is taken as the preset brightness benchmark value to ensure that the benchmark value can represent the brightness level of the attraction under normal conditions.

[0103] The preset texture complexity benchmark value, which is the preset texture complexity benchmark value in the formula, is determined based on the historical environmental texture data of the target tourist attraction. The average number of texture repetitions in different landscape areas of the attraction, such as building areas, vegetation areas, and water areas, is statistically analyzed. The comprehensive average of all area averages is used as the preset texture complexity benchmark value, reflecting the texture complexity level of the attraction under normal environmental conditions.

[0104] The preset distribution adjustment factor, which is the preset distribution adjustment factor in the formula, is determined through multiple rendering tests. Different values ​​of the distribution adjustment factor are set in different test scenarios to observe the fusion effect of digital display content and real-world images. The value with the most harmonious visual effect and no obvious sense of separation after fusion is selected as the final preset distribution adjustment factor to ensure that this factor can optimize the impact of brightness and tone differences on the fusion effect.

[0105] The exponential function, as used in the formula, is used to calculate the opposite value of the value within parentheses and then calculate the exponent of that opposite value. The smaller the value within parentheses, the smaller the difference between the ambient light brightness parameter and the preset brightness reference value, and the smaller the difference between the ambient main color parameter and the reference color. The larger the opposite value, the closer the result of the exponential function is to 1, and vice versa. This quantifies the degree of matching between brightness and color.

[0106] The natural logarithm, as used in the formula, is used to calculate the logarithm of the ratio of the ambient light brightness parameter to the preset brightness reference value. If the ambient light brightness parameter is equal to the preset brightness reference value, the ratio is 1, and the natural logarithm result is 0. If the ambient light brightness parameter deviates from the preset brightness reference value, the ratio deviates from 1, and the natural logarithm result increases accordingly. This method converts the brightness difference into a quantifiable value, providing a basis for subsequent calculations.

[0107] The hyperbolic tangent function, as mentioned in the formula, is used to calculate the hyperbolic tangent of the ratio of the environment texture complexity parameter to the preset texture complexity benchmark value. When the environment texture complexity parameter is close to the preset texture complexity benchmark value, the ratio is close to 1, and the hyperbolic tangent function result is stable at around 0.7. When the difference between the two increases, the ratio deviates from 1, and the hyperbolic tangent function result shifts towards either 0 or 1, thereby quantifying the degree of texture complexity adaptation.

[0108] Pi, or the circumference of a circle in the formula, is used to standardize the difference between the environmental primary color parameter and the reference color. Dividing the difference by pi keeps the difference between 0 and 1, avoiding abnormal calculation results due to excessive difference, and ensuring that the influence of the environmental primary color parameter on the visual fusion coefficient is within a reasonable range.

[0109] The significance of this formula is to comprehensively quantify the visual adaptation degree between the real-time environment of the target tourist attraction and the digital display content of tourism products. The first part of the formula uses the natural logarithm of pi and the exponential function to convert the difference between the ambient light brightness parameter and the preset brightness benchmark value and the difference between the ambient main color parameter and the benchmark color into a brightness and color adaptation coefficient. The smaller the difference, the larger the adaptation coefficient. The second part uses the hyperbolic tangent function to convert the difference between the ambient texture complexity parameter and the preset texture complexity benchmark value into a texture adaptation coefficient. The smaller the difference, the more stable the adaptation coefficient. The visual fusion coefficient obtained by multiplying the two can accurately reflect the comprehensive adaptation level of the digital display content and the real-world environment in terms of brightness, color, and texture. The larger the visual fusion coefficient, the stronger the visual coordination between the two. This provides a quantitative basis for the subsequent integration of the multi-scale feature layers of the digital display content into the real-world image, ensuring that the generated intermediate rendering content fits the real-time environment and ultimately obtains visually coordinated dynamic display content.

[0110] The digital display content is broken down into three multi-scale feature layers: outline, detail, and color. The outline layer contains the overall shape and boundary of the tourism product; the detail layer contains the product's local textures and decorative elements; and the color layer contains the product's main color information. The integration method of each feature layer is adjusted according to the visual fusion coefficient calculated using the above formula. If the visual fusion coefficient is high, the outline layer is fully aligned with the boundary of the corresponding area in the real-world image, the detail layer retains all texture elements, and the color layer is directly overlaid. If the visual fusion coefficient is medium, the transparency of the outline layer is slightly adjusted to adapt to the real-world scene, some non-core textures in the detail layer are simplified, and the color layer's hue is finely adjusted to match the main color tone of the environment. If the visual fusion coefficient is low, the transparency of the outline layer is increased, the detail layer retains only the core outline texture, and the color layer's hue is significantly adjusted to match the main color tone of the environment. The adjusted multi-scale feature layers are then integrated one by one into the corresponding area of ​​the real-world image to obtain the intermediate rendered content of the tourism product.

[0111] Five evenly distributed sampling points are selected from the intermediate rendered content, and the RGB color value of each sampling point is extracted. Simultaneously, five sampling points at the same locations in the corresponding area of ​​the intermediate rendered content in the real-world image are selected, and the RGB color values ​​of these sampling points are extracted. The differences between the two sets of RGB color values ​​are compared. If the color difference of all sampling points is within a fixed and reasonable range, and the edge transition between the intermediate rendered content and the real-world image is natural, without obvious color breaks or abrupt color blocks, the color features of the two are considered to be coordinated. If there are cases where the color difference exceeds the range or the edge transition is unnatural, the process is returned to the previous step to adjust the integration method of the multi-scale feature layer, regenerate the intermediate rendered content, and verify it again until the color feature coordination requirements are met. At this point, the intermediate rendered content is the dynamic display content of the tourism product.

[0112] The beneficial effects are that by accurately collecting real-time environmental parameters through categorized sensors and forming a structured set of environmental feature descriptions, objective data support is provided for rendering adaptation and formula calculation of visual fusion coefficients; the visual fusion coefficients obtained based on the formulas can accurately match the adaptation needs of digital content and real-world environments, avoiding subjective judgment bias; multi-scale feature layers are integrated according to the fusion coefficients to ensure that the intermediate rendered content fits the real scene; finally, the dynamic display content obtained through color coordination verification can be highly consistent with the real-time environment of the target tourist attraction, avoiding visual disjointedness, making the digital display of tourism products more natural and realistic, and effectively improving users' perception experience of the integration of tourism products and scenic spot scenes.

[0113] S4. Package the display action sequence and triggering conditions of the tourism product into the interactive behavior logic of the tourism product, and embed the interactive behavior logic into the dynamic display content to obtain the intelligent interactive content of the tourism product.

[0114] In this embodiment of the invention, the step of packaging the display action sequence and triggering conditions of the tourism product into the interactive behavior logic of the tourism product, and embedding the interactive behavior logic into the dynamic display content to obtain the intelligent interactive content of the tourism product, includes:

[0115] Extract the basic action units and execution order relationships of the action sequences displayed in the tourism products to obtain the action descriptor set of the tourism products;

[0116] The triggering conditions of the tourism products are decomposed into environmental triggering, user interaction, and time-series control types to obtain the condition types of the triggering conditions;

[0117] A correlation analysis is performed on the condition types and the display action sequences to establish a condition-action lookup table for the tourism products;

[0118] Based on the condition-action lookup table, construct the interactive behavior logic of the tourism product;

[0119] The interactive behavior logic is serialized into interactive description data of the tourism product, and the interactive description data is injected into the metadata layer of the dynamically displayed content to obtain the intelligent interactive content of the tourism product.

[0120] The step of constructing the interactive behavior logic of the tourism product based on the condition-action lookup table includes:

[0121] Based on the execution parameters and state transition rules of the basic action unit, assign a corresponding behavior identifier to the basic action unit;

[0122] Based on the condition-action lookup table, priority analysis is performed on the triggering conditions to obtain the execution order of the triggering conditions;

[0123] The execution order and the behavior identifier are encoded into the initial behavior logic of the tourism product;

[0124] The completeness of the initial behavioral logic is verified to obtain the interactive behavioral logic of the tourism product.

[0125] The complete sequence of actions for showcasing tourism products is analyzed. For example, when the tourism product is a "lake view homestay package," the sequence of actions includes "loading and displaying the homestay 3D model," "model rotation," "room interior scene unfolding," "pop-up display of supporting service information," and "price and booking button appearing." These continuous actions are broken down into independent basic action units, each corresponding to a single, indivisible action. The execution order is determined by recording the chronological order of the actions. For example, after "model loading and displaying" is completed, "model rotation" is executed; after "model rotation" is completed, "room interior scene unfolding" is executed. These actions are then organized according to the structure of "basic action unit name - execution sequence number" to obtain the action descriptor set for the tourism product.

[0126] Analyzing the trigger sources for tourism product display actions, the trigger conditions are clearly divided into three categories: environmental triggers based on the real-time environmental status of the target tourist attraction, such as "the lighting effect of the homestay 3D model is triggered when the ambient light is below 200 lux"; user interaction triggers based on user-initiated actions, such as "the interior scene of the room is triggered when the user clicks on the homestay 3D model"; and time-controlled triggers based on preset time nodes, such as "the pop-up window for supporting service information is triggered 5 seconds after the homestay 3D model is loaded". All trigger conditions are categorized one by one, and the type of each condition is clearly labeled to obtain the condition type of the trigger conditions.

[0127] The specific trigger conditions under each condition type are matched one by one with the basic action units in the displayed action sequence. For example, in the environment-triggered type, "ambient light brightness is less than 200 lux" corresponds to the action "lighting effect of homestay 3D model"; in the user interaction type, "user clicks on model" corresponds to the action "room interior scene unfolds"; and in the timing-controlled type, "5 seconds after loading is complete" corresponds to the action "pop-up display of supporting service information". The matching results are organized in the format of "condition type - specific trigger condition - corresponding basic action unit" to form a table containing all the correspondences between conditions and actions, resulting in the condition-action mapping table for tourism products.

[0128] Extract the execution parameters and state transition rules for each basic action unit. Execution parameters include the rotation speed and direction of "Model Rotation," and the size of the pop-up window for "Information Pop-up Display." State transition rules include the state of "Model Rotation" changing from "stationary" to "rotating" and then back to "stationary," and the state of "Information Pop-up Display" changing from "hidden" to "shown" and then back to "hidden." Assign a unique behavior identifier to each basic action unit. The identifier consists of "ACT-" followed by three digits, such as "ACT-002" for "Model Rotation" and "ACT-003" for "Room Interior Scene Unfolding." Ensure that the identifier for each unit is unique, thus completing the binding between the basic action unit and the behavior identifier.

[0129] The reference condition-action table prioritizes trigger conditions based on their impact on user experience: User-interactive trigger conditions directly respond to user actions and have the highest priority, such as "user clicks the model," which should be executed first; Environment-triggered trigger conditions relate to real-time environmental changes and have the next highest priority, such as "changes in ambient light," which should be executed when there is no user interaction; Time-controlled trigger conditions are pre-defined processes and have the lowest priority, such as "pop-up window 5 seconds after loading," which should be executed when there is no user interaction or environmental change. All trigger conditions are arranged in the order of "User-interactive > Environment-triggered > Time-controlled" to determine the execution order.

[0130] The execution order of trigger conditions is associated and integrated with the corresponding behavior identifiers, and recorded in descending order of priority as follows: "Trigger Condition Priority - Condition Type - Specific Trigger Condition - Corresponding Behavior Identifier - Basic Action Unit", for example, "1-User Interaction Type - User Click Model - ACT-003 - Room Interior Scene Unfolds", "2-Environment Trigger Type - Light Intensity Below 200 lux - ACT-004 - Model Lights Turn On", "3-Time-Control Type - 5 Seconds After Loading - ACT-005 - Service Pop-up Display". This associated information is then organized into structured text in a fixed format to obtain the initial behavioral logic of the tourism product.

[0131] Check whether the initial behavioral logic covers all basic action units and triggering conditions. Confirm that each basic action unit has a corresponding triggering condition and behavior identifier, and each triggering condition has a matching basic action unit and execution order, with no omissions or unrelated content. Simultaneously verify whether there are any conflicts in the execution order when different triggering conditions are triggered simultaneously. For example, when user actions and environmental changes occur simultaneously, should the action corresponding to the user interaction be executed first? If conflicts exist, adjust the execution order; if omissions exist, supplement the relationships until the initial behavioral logic contains all necessary elements and has no conflicts, thus obtaining the interactive behavioral logic for the tourism product.

[0132] A fixed text serialization format is used to transform the "behavior identifier-trigger condition-execution order-basic action unit execution parameters" in the interactive behavior logic into text data with a unified structure, such as "ACT-003|User Click Model|1|Room Expansion Speed: 0.5 seconds / frame". The text set formed after all related information is organized in this format is the interactive description data of the tourism product. The metadata layer of the dynamically displayed content is located. This layer is used to store the attribute information and interaction rules of the displayed content. The interactive description data is written into the "interaction logic" field of the metadata layer to ensure that the interactive description data is associated and bound with the core data of the dynamically displayed content, thus obtaining the intelligent interactive content of the tourism product.

[0133] The beneficial effects are that the interactive behavioral logic constructed through steps such as decomposing actions, classifying conditions, and associating and matching can comprehensively cover all actions and triggering scenarios in the display of tourism products. The clear behavioral identifiers and execution order make the logical structure clear and traceable. The intelligent interactive content formed by injecting metadata layer after serialization can accurately respond to three types of triggering conditions: environment, user, and time sequence. This ensures that the actions of tourism product display are executed in an orderly manner and meet user needs, effectively improving the interactivity and flexibility of digital display of tourism products and enhancing users' awareness and participation in tourism products.

[0134] S5. Using the spatial anchor point as a reference, the intelligent interactive content is superimposed onto the real-scene image to obtain a real-world display of the tourism product.

[0135] In this embodiment of the invention, the step of overlaying the intelligent interactive content onto the real-scene image based on the spatial anchor point to obtain a realistic display image of the tourism product includes:

[0136] The coordinate information of the spatial anchor point and the scene structure data are transformed to obtain the mapping relationship between the local coordinate system in the intelligent interactive content and the global coordinate system in the real scene image;

[0137] Based on the mapping relationship, the intelligent interactive content is subjected to perspective transformation, and the scale of the transformed intelligent interactive content is adjusted to obtain the optimized interactive content of the tourism product.

[0138] The optimized interactive content and the real-scene image are fused at the pixel level, and the visual boundaries generated during the fusion process are eliminated to obtain the fused image data of the tourism product.

[0139] The fused image data is formatted and encapsulated to obtain a real-world display image of the tourism product.

[0140] The optimal spatial positioning coordinates and hierarchical information contained in the spatial anchor points are obtained. The optimal spatial positioning coordinates are the initial position coordinates of the intelligent interactive content in the real-world image, belonging to the coordinates under the local coordinate system of the intelligent interactive content itself. Simultaneously, the global coordinate system parameters of the real-world image are extracted from the scene structure data. This global coordinate system has its origin at the top-left pixel of the real-world image, with the X-axis horizontally and the Y-axis vertically, and includes the global coordinate range of key landscape elements. The origin of the local coordinate system of the intelligent interactive content is aligned with the optimal spatial positioning coordinates of the spatial anchor points, i.e., the origin of the local coordinate system corresponds to the optimal spatial positioning coordinates (X0, Y0) in the global coordinate system. Then, the corresponding coordinates of each boundary point in the local coordinate system of the intelligent interactive content in the global coordinate system are calculated. For example, the top-left corner point (-a, -b) of the local coordinate system corresponds to (X0-a, Y0-b) in the global coordinate system. Through this point-to-point correspondence, the transformation rules between any point in the local coordinate system of the intelligent interactive content and its corresponding point in the global coordinate system of the real-world image are established, resulting in the mapping relationship between the local coordinate system of the intelligent interactive content and the global coordinate system of the real-world image.

[0141] Based on the obtained mapping relationship, the perspective adaptation direction of the intelligent interactive content in the real-world image is determined. If the real-world image was acquired using a 15° elevation angle, the intelligent interactive content undergoes a perspective transformation at the same angle: taking the side of the intelligent interactive content furthest from the observer as a reference, the horizontal and vertical dimensions of that side are reduced by a preset ratio, while the dimensions of the side closer to the observer remain unchanged, so that the intelligent interactive content presents a "nearer is larger, farther is smaller" perspective effect, matching the perspective characteristics of the real-world image. Subsequently, referring to the dimensions of key landscape elements in the scene structure data, the scale of the intelligent interactive content after the perspective transformation is adjusted. If the intelligent interactive content is a 3D model of a homestay, its horizontal width is kept in a ratio of approximately 1:1.2 to the width of the viewing pavilion, ensuring that the intelligent interactive content in the real-world image is neither too large to obscure the core landscape nor too small to be observed. After adjustment, the optimized interactive content for the tourism product is obtained.

[0142] The optimized interactive content is overlaid with the real-world image, ensuring perfect alignment of corresponding pixel positions. Pixel-level fusion processing is then performed on the overlaid pixels: for opaque main areas in the optimized interactive content, the RGB values ​​of the optimized interactive content are directly used to overwrite the corresponding pixel values ​​in the real-world image; for semi-transparent areas in the optimized interactive content, the average of the RGB values ​​of the corresponding pixels in the optimized interactive content and the real-world image is calculated, and this average is used as the fused pixel value. After fusion, a 10-pixel-wide transition band is set at the edge where the optimized interactive content and the real-world image meet. From the inside to the outside of the transition band, the transparency of the optimized interactive content pixels gradually decreases from 100% to 0%, while the transparency of the real-world image pixels gradually increases from 0% to 100%, eliminating obvious visual boundaries generated during the fusion process and obtaining the fused image data for the tourism product.

[0143] Determine the target encapsulation format for the merged image data. For static images, select JPEG; for dynamic images, select MP4. During encapsulation, first adjust the pixel arrangement of the merged image data to the order required by the target format, then add necessary metadata information, including image resolution, color space, and frame rate of the dynamic images. After adding the metadata, encode the merged image data according to the target format's encoding rules to generate a file that conforms to the playback standards of the terminal device, resulting in the actual display image of the tourism product.

[0144] The beneficial effects include establishing a precise coordinate system mapping relationship through coordinate transformation, ensuring that the intelligent interactive content is positioned accurately in the real-world imagery; perspective transformation based on the real-world viewpoint and scale adjustment of reference landscape elements, making the optimized interactive content visually highly compatible with the real-world scene and conforming to human visual observation habits; pixel-level fusion and transition zone processing effectively eliminate visual boundaries and avoid a sense of disjointedness at the fusion points; and targeted format encapsulation ensures that the real-world display can be played stably on various terminal devices. The entire process is progressive, ultimately presenting a visually harmonious, accurately positioned, and stably played real-world display, significantly enhancing the realism of digital tourism product displays and the user viewing experience.

[0145] S6. Encode the user's real-time interactive intent into control instructions for the tourism product, and drive the intelligent interactive content in the real-world display screen to execute the corresponding display actions.

[0146] In this embodiment of the invention, encoding the user's real-time interactive intent into control instructions for the tourism product, and driving the intelligent interactive content in the real-world display screen to execute corresponding display actions, includes:

[0147] Decompose the type and spatial location features of the user's real-time interaction intent to obtain the user's interaction description information;

[0148] The interaction description information and the interactive behavior logic are associated and matched to obtain the target behavior identifier and target execution parameters of the interaction description information.

[0149] The target behavior identifier and the target execution parameters are encapsulated into control instructions for the tourism product;

[0150] The control command is sent to the driver terminal of the intelligent interactive content to display the corresponding display action in the real display screen.

[0151] Real-time interactive actions are collected through the sensing module of the user interaction device. If the user performs a touch screen operation, the device's touch sensor records the action type and identifies it as a type feature. Simultaneously, the pixel coordinates of this interaction action on the device screen are obtained. Based on a preset mapping ratio between the device screen and the global coordinate system of the real-world image, the screen pixel coordinates are converted into coordinate values ​​in the global coordinate system of the real-world image. These coordinate values ​​are the spatial location features. The type feature and spatial location features are then organized into a fixed structure: "Type feature: XX; Spatial location feature: Global coordinate system X=XX, Y=XX," to obtain the user's interaction description information.

[0152] Retrieve the interactive behavior logic of the existing tourism products and extract a condition-action lookup table containing "trigger condition type - trigger spatial coordinate range - corresponding behavior identifier - execution parameters". Perform a complete match between the type features in the interaction description information and the trigger condition types in the lookup table; simultaneously, determine whether the global coordinates corresponding to the spatial location features of the interaction description information fall within the trigger spatial coordinate range marked by the matching entry. If both meet the matching requirements, extract the behavior identifier within that entry as the target behavior identifier, and extract information such as the action speed and display duration within that entry as target execution parameters, thus obtaining the target behavior identifier and target execution parameters of the interaction description information.

[0153] A dedicated encapsulation format for tourism product control instructions is adopted. This format consistently includes four parts: "Instruction Prefix - Target Behavior Identifier - Target Execution Parameter - Instruction Suffix". The instruction prefix is ​​uniformly "TP-CMD", and the instruction suffix is ​​uniformly "END". The target behavior identifier and target execution parameters are filled into the corresponding positions in the format and combined in the order of "Instruction Prefix | Target Behavior Identifier | Target Execution Parameter | Instruction Suffix". The complete string formed by this combination constitutes the control instruction for the tourism product.

[0154] Control commands are transmitted via a stable communication link between the user interaction device and the intelligent interactive content driving terminal. For mobile devices, 5G or WiFi communication is used; for fixed display equipment in scenic areas, wired Ethernet communication is used. Before transmission, the control commands are format-verified to ensure they contain all parts of the sequence "command prefix - target behavior identifier - target execution parameters - command suffix" without missing or incorrect characters. Once verification is successful, transmission begins. After receiving the command, the driving terminal uses its built-in command parsing module to break down the command into its components, extracting the target behavior identifier and target execution parameters. Based on the target behavior identifier, the corresponding action driver is called, and the specific parameters of the action are set according to the target execution parameters. The intelligent interactive content is then driven to execute this action on the real-world display screen to display the corresponding action.

[0155] The beneficial effects include: accurately collecting and decomposing the type and spatial characteristics of user interaction intent through the sensing module, ensuring that the interaction description information can truly reflect the user's operation needs; based on the bidirectional matching of the condition-action lookup table, the corresponding target behavior identifier and execution parameters can be quickly and accurately located, avoiding interaction response deviations; the standardized control instruction encapsulation format ensures that the driver terminal can be stably parsed; and the stable communication transmission and terminal action driving process realize the accurate conversion of user interaction intent into actual display screen actions, effectively improving the interactive response efficiency and accuracy of digital display of tourism products, and enhancing the user's sense of smoothness and participation experience during operation.

[0156] like Figure 2 The diagram shown is a functional module diagram of a digital display system for tourism products provided in an embodiment of the present invention.

[0157] The digital display system 100 for tourism products described in this invention can be installed in an electronic device. Depending on the functions implemented, the digital display system 100 for tourism products may include an image analysis module 101, a spatial fusion module 102, a content rendering module 103, an intelligent interaction module 104, a display screen overlay module 105, and a display action execution module 106. The modules described in this invention can also be referred to as units, which are a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and are stored in the memory of the electronic device.

[0158] In this embodiment, the functions of each module / unit are as follows:

[0159] The image analysis module 101 is used to perform scene semantic analysis on the real-scene images of the target tourist attraction, identify key landscape elements in the real-scene images and the spatial relationships between the key landscape elements, and obtain scene structure data of the target tourist attraction.

[0160] The spatial fusion module 102 is used to spatially fuse the digital display content of tourism products with the scene structure data to determine the spatial anchor point of the digital display content in the real-scene image.

[0161] The content rendering module 103 is used to perform state-adaptive rendering of the digital display content based on the real-time environmental status data of the target tourist attraction, so as to obtain the dynamic display content of the tourism product.

[0162] The intelligent interaction module 104 is used to package the display action sequence and triggering conditions of the tourism product into the interactive behavior logic of the tourism product, and embed the interactive behavior logic into the dynamic display content to obtain the intelligent interactive content of the tourism product.

[0163] The display overlay module 105 is used to overlay the intelligent interactive content onto the real-scene image based on the spatial anchor point to obtain a real-world display of the tourism product.

[0164] The display action execution module 106 is used to encode the user's real-time interactive intent into control instructions for the tourism product, and drive the intelligent interactive content in the real-world display screen to execute corresponding display actions.

[0165] In the several embodiments provided by this invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0166] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0167] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0168] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0169] This application embodiment can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0170] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for digital presentation of a tourism product, characterized by, The method comprises: S1, scene semantic analysis is performed on the real scene image of the target tourist attraction, key landscape elements in the real scene image and spatial relationships between the key landscape elements are identified, and scene structure data of the target tourist attraction is obtained; S2, the digital display content of the tourism product is spatially fused with the scene structure data to determine the spatial anchor point of the digital display content in the real scene image; S3, based on the real-time environmental state data of the target tourist attraction, the state adaptability of the digital display content is rendered, and the dynamic display content of the tourism product is obtained, including: extracting the environmental brightness parameter, the environmental dominant color parameter and the environmental texture complexity parameter of the real-time environmental state data in the target tourist attraction to obtain the environmental feature description set of the target tourist attraction; based on the environmental feature description set, the rendering adaptation degree analysis is performed on the digital display content, and the visual fusion coefficient of the target tourist attraction and the tourism product is obtained, wherein the calculation formula of the visual fusion coefficient is: ； wherein, denotes the visual fusion coefficient, denotes the ambient light brightness parameter, denotes the ambient dominant hue parameter, denotes the ambient texture complexity parameter, denotes a preset brightness reference value, denotes a preset texture complexity reference value, denotes a preset distribution adjustment factor, denotes an exponential function, denotes a natural logarithm, denotes a hyperbolic tangent function, denotes a circular constant; according to the visual fusion coefficient, the multi-scale feature layer of the digital display content is fused into the corresponding area in the real scene image to obtain the intermediate rendering content of the tourism product; verify the coordination of the intermediate rendering content and the current color feature of the real scene image to obtain the dynamic display content of the tourism product; S4, the display action sequence and the trigger condition of the tourism product are packaged as the interactive behavior logic of the tourism product, and the interactive behavior logic is embedded in the dynamic display content to obtain the intelligent interactive content of the tourism product; S5, taking the spatial anchor point as the reference, the intelligent interactive content is superimposed into the real scene image to obtain the real display picture of the tourism product; S6, the real-time interactive intention of the user is encoded as the control instruction of the tourism product, and the intelligent interactive content is driven in the real display picture to perform the corresponding display action.

2. The method for digital presentation of a tourism product according to claim 1, characterized in that, The scene semantic analysis of the real scene image of the target tourist attraction, the identification of the key landscape elements in the real scene image and the spatial relationship between the key landscape elements, and the obtaining of the scene structure data of the target tourist attraction, comprise: collecting the real scene image of the target tourist attraction, and dividing the real scene image into candidate regions of the target tourist attraction through pixel-level segmentation; according to the color consistency and texture continuity features of the candidate regions, the candidate regions are screened to obtain the key landscape elements of the target tourist attraction; analyze the relative orientation and distance constraints between the key landscape elements to obtain the spatial relationship descriptor of the target tourist attraction; structurally analyzing the attributes of the key landscape elements and the spatial relationship descriptor to obtain the scene structure data of the target tourist attraction.

3. The method for digital presentation of a tourism product according to claim 1, characterized in that, The spatial fusion of the digital display content of the tourism product and the scene structure data to determine the spatial anchor point of the digital display content in the real scene image, comprises: The digital display content of the tourism product is acquired, semantic description of the digital display content is matched with the key landscape elements to obtain a candidate fusion position of the tourism product; The spatial topological relationship between the scene structure data and the candidate fusion position is verified, and a potential anchor area of a preset spatial constraint condition is screened out; Visual saliency detection is performed on visual attributes of the digital display content and background environment features of the potential anchor area to determine optimal spatial positioning coordinates of the tourism product; The optimal spatial positioning coordinates and hierarchical information of the digital display content are bound to obtain a spatial anchor point of the digital display content in the real scene image.

4. The method for digital presentation of a tourism product according to claim 1, characterized in that, The display action sequence and trigger condition of the tourism product are packaged as interactive behavior logic of the tourism product, and the interactive behavior logic is embedded in the dynamic display content to obtain intelligent interaction content of the tourism product, including: Basic action units and execution order relationships of the display action sequence in the tourism product are extracted to obtain an action descriptor set of the tourism product; Trigger conditions of the tourism product are decomposed into environment trigger type, user interaction type and time sequence control type to obtain condition types of the trigger conditions; The condition types and the display action sequence are associated and analyzed to establish a condition-action correspondence table of the tourism product; According to the condition-action correspondence table, interactive behavior logic of the tourism product is constructed; The interactive behavior logic sequence is serialized as interaction description data of the tourism product, and the interaction description data is injected into a metadata layer of the dynamic display content to obtain intelligent interaction content of the tourism product.

5. A method of digital presentation of a travel product as claimed in claim 4, characterized in that, According to the condition-action correspondence table, interactive behavior logic of the tourism product is constructed, including: According to execution parameters and state transition rules of the basic action units, corresponding behavior identifiers are assigned to the basic action units; Based on the condition-action correspondence table, priority analysis is performed on the trigger conditions to obtain an execution order of the trigger conditions; The execution order and the behavior identifiers are encoded as initial behavior logic of the tourism product; The integrity of the initial behavior logic is verified to obtain the interactive behavior logic of the tourism product.

6. The method for digital presentation of a travel product according to claim 1, wherein, The intelligent interaction content is superimposed into the real scene image based on the spatial anchor point to obtain a real display picture of the tourism product, including: Coordinate conversion is performed on coordinate information of the spatial anchor point and the scene structure data to obtain a mapping relationship between a local coordinate system in the intelligent interaction content and a global coordinate system in the real scene image; Based on the mapping relationship, perspective transformation is performed on the intelligent interaction content, and the size of the transformed intelligent interaction content is adjusted to obtain optimized interaction content of the tourism product; Pixel-level fusion processing is performed on the optimized interaction content and the real scene image, and visual boundaries generated in the fusion process are eliminated to obtain fusion picture data of the tourism product; The fusion picture data is format packaged to obtain a real display picture of the tourism product.

7. The method for digital presentation of a travel product according to claim 1, wherein, The method comprises the following steps: Decompose the type characteristics and spatial position characteristics of the real-time interaction intention of the user to obtain the interaction description information of the user; Correlate and match the interaction description information and the interactive behavior logic to obtain the target behavior identifier and the target execution parameter of the interaction description information; Encapsulate the target behavior identifier and the target execution parameter into the control instruction of the tourism product; Send the control instruction to the driving terminal of the intelligent interaction content to display the corresponding display action in the real display picture.

8. A digital display system of a tourism product, used to implement the method of claim 1, the system comprising: An image analysis module for performing scene semantic analysis on a real scene image of a target tourist attraction, identifying key landscape elements in the real scene image and spatial relationships between the key landscape elements, and obtaining scene structure data of the target tourist attraction; A spatial fusion module for spatially fusing digital display content of a tourism product with the scene structure data to determine spatial anchor points of the digital display content in the real scene image; A content rendering module for performing state adaptive rendering of the digital display content based on real-time environmental state data of the target tourist attraction to obtain dynamic display content of the tourism product, comprising: Extracting environmental brightness parameters, environmental dominant color parameters, and environmental texture complexity parameters of the real-time environmental state data of the target tourist attraction to obtain an environmental feature description set of the target tourist attraction; Based on the environmental feature description set, performing rendering adaptation degree analysis on the digital display content to obtain a visual fusion coefficient of the target tourist attraction and the tourism product, wherein the calculation formula of the visual fusion coefficient is: ； wherein, represents the visual fusion coefficient, represents the ambient light brightness parameter, represents the ambient dominant hue parameter, represents the ambient texture complexity parameter, represents a preset brightness reference value, represents a preset texture complexity reference value, represents a preset distribution adjustment factor, represents an exponential function, represents a natural logarithm, represents a hyperbolic tangent function, represents a circular constant; According to the visual fusion coefficient, integrating multi-scale feature layers of the digital display content into corresponding regions in the real scene image to obtain intermediate rendering content of the tourism product; Verifying the coordination of the intermediate rendering content and the current color features of the real scene image to obtain dynamic display content of the tourism product; An intelligent interaction module for packaging display action sequences and trigger conditions of the tourism product into interactive behavior logic of the tourism product, and embedding the interactive behavior logic into the dynamic display content to obtain intelligent interaction content of the tourism product; A display picture superposition module for superimposing the intelligent interaction content onto the real scene image based on the spatial anchor points to obtain a real display picture of the tourism product; A display action execution module for encoding real-time interaction intentions of users into control instructions of the tourism product to drive the intelligent interaction content in the real display picture to perform corresponding display actions.

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