A method for importing, constructing and analyzing three-dimensional scene portrait design elements

Abstract

The present invention belongs to the field of three-dimensional scene construction and intelligent design, and particularly relates to exhibit layout and lighting design technology in a three-dimensional scene of an exhibition hall. The invention discloses a method for importing, constructing and analyzing three-dimensional scene portrait design elements. A structured exhibit theme knowledge graph is established in the constructed three-dimensional exhibition hall model according to the theme classification and hierarchical labels of the exhibits. On this basis, the exhibits are targetedly arranged in the exhibition hall in combination with the spatial proximity relationship of the exhibition area, so that exhibits with the same theme can be adjacent or clustered in the physical space, which effectively improves the logical coherence and thematic consistency of the exhibition content. After the exhibits are arranged, a dynamic simulation of the crowd density is performed based on the historical crowd distribution data of the exhibition area, and a variety of lighting conditions are set in combination with the light source arranged above the exhibition area for lighting rendering. During the rendering process, the user's perspective is simulated and visual effect data is collected to match the optimal lighting scheme for scenes with different crowd densities.

Description

Technical Field

[0001] The present invention belongs to the field of three-dimensional scene construction and intelligent design, and particularly relates to exhibit layout and lighting design technology in a three-dimensional scene of an exhibition hall. It specifically discloses a method for importing, constructing and analyzing three-dimensional scene portrait design elements. Background Art

[0002] With the public's growing awareness of cultural consumption, exhibition halls, as crucial spaces for information dissemination and cultural exchange, have become a core venue for people to acquire knowledge, experience art, and access new technologies. The early stages of exhibition hall construction are particularly crucial. In recent years, driven by digital and intelligent technologies, traditional exhibition hall design models are rapidly transforming towards visualization, data-driven design, and intelligent decision-making. Against this backdrop, three-dimensional scene construction and design based on 3D modeling and spatial analysis have gradually become a major trend in modern exhibition hall planning and design. Widely used in multiple design stages, including exhibit layout and exhibition area lighting, they have significantly enhanced exhibition hall functionality and the quality of the exhibition experience.

[0003] However, existing 3D scene construction designs for exhibition halls often rely on empirical arrangements for exhibit layout, failing to fully consider the spatial proximity of exhibition areas and the thematic relevance of exhibits. This approach often results in a disorganized distribution of exhibits and a break in thematic logic. For example, historical artifacts and technological exhibits are mixed in the same exhibition area, disrupting the coherence and thematic consistency of the exhibition, affecting the visitor's understanding and immersion.

[0004] Furthermore, in current exhibition hall three-dimensional scene construction, lighting design primarily focuses on the presentation of the exhibits themselves, resulting in static lighting parameter settings that fail to fully consider the impact of dynamically changing crowd density on the exhibition area's lighting needs. Visitor behavior within an exhibition hall exhibits significant spatiotemporal flow characteristics, with crowd density constantly changing over time. Fixed lighting configurations struggle to adapt to the visual perception needs of different scenarios. For example, in high crowd density situations, visitors' vision is easily distracted, requiring enhanced contrast between exhibits and the background to improve recognition efficiency. In contrast, in low crowd density situations, greater emphasis is placed on visual comfort and detail. Therefore, static lighting design cannot achieve precise control of the exhibition environment, impacting the quality of the visitor's visual experience and the optimal presentation of exhibits. Summary of the Invention

[0005] To this end, one purpose of an embodiment of the present application is to provide a method for importing, constructing and analyzing three-dimensional scene portrait design elements, which effectively solves the problems existing in the prior art by focusing on optimizing the exhibit layout and lighting design in the three-dimensional scene construction of the exhibition hall.

[0006] The purpose of the present invention can be achieved through the following technical solutions: A method for importing, constructing and analyzing three-dimensional scene portrait design elements, comprising the following steps: S1. Obtaining the spatial structure data of the exhibition hall, specifically including the geometric boundaries of each exhibition area, the topological relationship of the exhibition area and the distribution position of the light source, thereby constructing a three-dimensional model of the exhibition hall.

[0007] S2. Extract the exhibit display themes and their theme label hierarchy from the exhibition hall design documents to construct the exhibit theme knowledge graph and import it into the exhibition hall 3D model.

[0008] S3. Arrange exhibits in the three-dimensional model of the exhibition hall based on the spatial proximity relationship of the exhibition areas and the knowledge graph of the exhibit themes.

[0009] S4. Extract the crowd density distribution characteristics of exhibits in similar exhibition halls in history and divide them into gradient-increasing crowd density. Based on this, conduct a dynamic simulation of the crowd density in the exhibition area where the exhibits are arranged. After the simulation, use the light sources arranged above the exhibition area to set different lighting conditions for lighting rendering.

[0010] S5. During the lighting rendering process, several virtual observation points are selected based on the exhibition area's viewing activity area to simulate the user's perspective to collect visual effect data. Based on the different lighting conditions corresponding to different crowd densities in the exhibition area and the visual effect data at different observation points, the lighting conditions suitable for different crowd densities are determined.

[0011] Combining all the above technical solutions, the positive effects of the present invention are as follows: 1. The present invention establishes a structured exhibit theme knowledge graph based on the display theme of the exhibits and their label hierarchy in the constructed three-dimensional exhibition hall model, and on this basis combines the spatial proximity relationship of the exhibition area to achieve targeted layout of exhibits in the exhibition hall, so that exhibits with the same theme can be adjacent or clustered in physical space, effectively improving the logical coherence and thematic consistency of the exhibition content, and enhancing the audience's cognitive continuity and immersive experience during the visit.

[0012] 2. After completing the layout of the exhibits, the present invention performs a dynamic simulation of the crowd density based on the historical crowd distribution data of the exhibition area, and sets a variety of lighting conditions in combination with the light sources arranged above the exhibition area for lighting rendering. During the rendering process, the user's perspective is simulated and visual effect data is collected to match the optimal lighting scheme for different crowd density scenes, thereby realizing refined and adaptive control of the display lighting, effectively improving the display effect and visual comfort of the exhibits in multiple scenarios, and at the same time enhancing the intelligence level and energy efficiency management capabilities of the exhibition hall lighting system. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The present invention is further described with reference to the accompanying drawings. However, the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative effort.

[0014] Figure 1 This is a diagram of the steps for implementing the method of the present invention.

[0015] Figure 2 This is a schematic diagram of the exhibit theme knowledge graph structure in the present invention.

[0016] Figure 3 This is a schematic diagram of the positioning triangle in the present invention.

[0017] Reference numerals: 1—main entrance of the exhibition hall, 2—central axis of the ground, 3—exhibition area, 4—positioning triangle. DETAILED DESCRIPTION

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0019] See also Figure 1 As shown, the present invention proposes a method for importing, constructing and analyzing three-dimensional scene portrait design elements, including the following steps: S1. Acquire the spatial structure data of the exhibition hall, specifically including the geometric boundaries of each exhibition area 3, the topological relationship of the exhibition area and the distribution position of the light source, thereby constructing a three-dimensional model of the exhibition hall.

[0020] In the specific embodiment of the above steps, the geometric boundaries of the exhibition area 3 include the spatial position and size parameters of architectural elements such as walls, floors, and ceilings, and are used to accurately describe the physical space range of each exhibition area 3.

[0021] Exhibition area topology reflects the spatial adjacency and connectivity between different areas, including the location of connecting structures such as passages, corridors, and entrances and exits. For example, an exhibition area 3 might be directly connected to a passage, which in turn leads to another exhibition area 3. By collecting exhibition area topology, we can clearly demonstrate the spatial structure and coherence of the entire exhibition hall.

[0022] The light source distribution information includes the type of the top lighting equipment of each exhibition area 3 and its spatial arrangement.

[0023] The above data can be obtained through exhibition hall design drawings. By integrating and modeling the exhibition hall's multi-source spatial data, a three-dimensional exhibition hall model can be constructed that highly restores the actual spatial characteristics, providing solid data support and visualization foundation for subsequent intelligent layout of exhibits, lighting simulation analysis and display effect evaluation.

[0024] S2. Extract the exhibit display themes and their theme label hierarchy from the exhibition hall design documents to construct the exhibit theme knowledge graph and import it into the exhibition hall 3D model.

[0025] It's important to note that each exhibit in the exhibition hall is assigned a clear theme. These themes embody the essential attributes and display value of the exhibit, including its core content, cultural background, and technological features. Specifically, themes reveal key information such as the historical period, artistic style, scientific field, and functional purpose of the exhibit, thus constructing a systematic cognitive path and a clear framework for understanding for the audience.

[0026] Furthermore, exhibition themes are usually organized using a hierarchical labeling system, which reflects the hierarchical logical relationship between themes. Lower-level themes represent macro-exhibition directions or knowledge areas, while higher-level themes correspond to more specific subcategories or sub-categories.

[0027] Furthermore, the exhibition design document typically clearly documents the theme and labeling hierarchy for each exhibit. This is because the exhibition design document, as the foundational document for exhibition planning, contains all key information, from exhibit selection to spatial layout. The theme and labeling hierarchy are essential components for ensuring the completeness and accuracy of the design plan, helping designers, curators, and relevant stakeholders fully understand the value and positioning of each exhibit.

[0028] As an implementable method of the above solution, the construction of the exhibit theme knowledge graph is implemented as follows:

[0029] The display themes of each exhibit are extracted from the exhibition hall design documents, and then the exhibits with the same theme are classified into exhibit sets corresponding to each display theme.

[0030] For each exhibition theme, the exhibits are arranged in order from low to high levels according to the theme label level to establish a hierarchical relationship between the exhibits.

[0031] It should be understood that the low level mentioned above reflects coarse granularity, referring to macroscopicity, while the high level is highly fine granularity, referring to microscopicity.

[0032] See also Figure 2 As shown in the figure, the display themes and hierarchical association relationships of the exhibits are integrated into a directed acyclic graph, where the nodes represent themes or exhibits and the edges represent the label levels, thereby constructing an exhibit theme knowledge graph.

[0033] The present invention constructs an exhibit theme knowledge graph based on the exhibits' display themes and their hierarchical labels, which can intuitively display the classification and attribution relationships of exhibits under different hierarchical theme labels. This knowledge graph helps to clearly present the overall narrative framework of the exhibition content and reveal the logical connections and semantic levels between exhibits. Through this structured expression method, the audience can more easily understand the theme context of the exhibition, achieve representative exhibit recognition from a macro perspective, and gradually delve into the details of exhibits in specific categories or specific historical stages, thereby improving the cognitive efficiency of viewing the exhibition.

[0034] S3. Arrange exhibits in the three-dimensional model of the exhibition hall based on the spatial proximity relationship of exhibition area 3 and the exhibit theme knowledge map.

[0035] Preferably, the specific implementation process of the above steps is: S31, based on the geometric boundaries of each exhibition area 3 in the three-dimensional model of the exhibition hall, select adjacent exhibition areas 3 through spatial adjacency analysis to form a set of spatially adjacent exhibition areas.

[0036] Further preferably, S31 is specifically implemented as follows: in the three-dimensional model of the exhibition hall, each exhibition area 3 is taken as a target exhibition area, and then the distance between the target exhibition area and other exhibition areas 3 is calculated based on the geometric boundary of the target exhibition area.

[0037] As an example of the above implementation, the operation of calculating the distance between the target exhibition area and the other exhibition areas 3 is as follows: extracting the boundary lines between the target exhibition area and the other exhibition areas 3.

[0038] Identify and capture the vertex set on the boundary line of the target exhibition area, and identify and capture the edge set on the boundary line of other exhibition areas 3.

[0039] For each vertex on the boundary line of the target exhibition area, calculate its vertical distance to each edge in the set of edges on the boundary lines of other exhibition areas 3. If the projection of the vertex on a certain edge falls within the range of the line segment, take its vertical distance; if the projection falls outside the line segment, take the minimum value of the distance to the two endpoints of the edge.

[0040] Finally, the minimum value is selected from all calculated distances as the distance between the target exhibition area and other exhibition areas 3.

[0041] By calculating the vertical distance from the vertex of the target exhibition area boundary to the boundaries of other exhibition areas 3, the above method can accurately quantify the minimum spatial interval between two exhibition areas 3. It is applicable to exhibition areas 3 of various complex shapes. Whether they are regular polygons or irregular shapes, the shortest distance can be found through computational geometry methods, which has strong versatility.

[0042] In the three-dimensional model of the exhibition hall, based on the topological relationship of the exhibition areas, it is identified whether the target exhibition area is connected to the other exhibition areas 3 by a channel or shares a boundary.

[0043] The spatial proximity determination rules are set as follows: a) the distance between the other exhibition areas 3 and the target exhibition area is less than or equal to a preset distance threshold.

[0044] b) Other exhibition areas 3 are connected to the target exhibition area by passages or share a common boundary.

[0045] It should be noted that Rule a takes into account the physical proximity of exhibition area 3. By setting a distance threshold, it is possible to scientifically define which exhibition areas 3 are physically adjacent, ensuring that the determination of the proximity relationship is scientific and operational.

[0046] Rule b considers the connectivity between exhibition areas 3, that is, whether there is a direct physical connection. Even if two exhibition areas 3 are not directly adjacent, they may still be perceived by the audience as closely related spatial units through clear channel guidance.

[0047] According to the above judgment rules, a set of 3 exhibition areas that meet any one of the rules is selected to form a set of spatially adjacent exhibition areas.

[0048] In the preceding example, assume the exhibition hall contains 10 exhibition areas 3, numbered A through J. Taking area A as the target, the shortest spatial distance between its geometric boundary and the other exhibition areas 3 is first calculated. Rule a is then used to filter out areas 3 whose distance from area A is less than or equal to the preset threshold. The resulting areas are C and D.

[0049] At the same time, by analyzing the topological relationship between A and other exhibition areas 3, it is determined whether there is a channel connection or boundary sharing. According to rule b, the exhibition area 3 that meets this condition is identified as F.

[0050] Finally, the target exhibition area A, exhibition areas C and D that meet rule a, and exhibition area F that meets rule b are combined to form a set of spatially adjacent exhibition areas, namely: {A, C, D, F}.

[0051] The above method of obtaining spatially adjacent exhibition areas not only considers the physical proximity, but also takes into account the functional connectivity, which can more comprehensively reflect the actual proximity status of the three exhibition areas.

[0052] S32: Count the number of exhibition areas 3 in each set of spatially adjacent exhibition areas, and match the number with the number of exhibits in the set of exhibits corresponding to each theme, thereby screening out themes that match each set of spatially adjacent exhibition areas.

[0053] Exemplarily, the specific operations of the above matching implementation are as follows: all spatially adjacent exhibition area sets are arranged in descending order according to the number of exhibition areas 3 they contain, to form an exhibition area set priority sequence.

[0054] At the same time, all classified exhibition themes are sorted in descending order according to the number of exhibits in their corresponding exhibit sets to generate a theme priority sequence.

[0055] The current highest-ranked topic is taken out from the topic priority sequence in turn, and matched with each unmatched exhibition area set in the exhibition area set priority sequence.

[0056] For each match, the difference between the number of exhibits under the theme and the number of exhibition areas 3 in the target exhibition area set is calculated.

[0057] Among all unmatched exhibition area sets, the set with the smallest difference is selected for pairing to ensure the optimal match between the theme scale and space capacity.

[0058] After each matching is completed, the theme and the corresponding exhibition area set are removed from their respective priority sequences as matched objects.

[0059] Continue to take the next theme from the theme priority sequence and repeat the above matching process until all themes or all exhibition area sets are matched, or only themes / sets that cannot meet the minimum matching conditions remain.

[0060] It is important to understand that by comparing the quantity requirements of exhibits under different themes with the physical capacity that can be provided by a collection of spatially adjacent exhibition areas, and finding the best match, it is possible to ensure that the spatial unit formed by each collection of spatially adjacent exhibition areas will neither appear crowded due to too many exhibits nor waste space resources due to too few exhibits.

[0061] S33. In the three-dimensional model of the exhibition hall, a ground central axis 2 is constructed with the main entrance 1 of the exhibition hall as the starting point, and the distance from the ground center point of each exhibition area in the set of spatially adjacent exhibition areas to the entrance and its vertical distance relative to the central axis are obtained respectively.

[0062] It's important to note that the central axis begins at the exhibition hall's main entrance. This entrance, as the primary gateway for visitors, typically plays a central role in the exhibition space's layout. A continuous path extending from the main entrance along the geometric center of the exhibition hall's interior forms the ground central axis 2, which traverses the hall's key display areas. During construction, the ground central axis 2 can be constructed based on the exhibition hall's design drawings.

[0063] S34, see Figure 3 As shown, based on the above two distances, the center point of the exhibition area ground, the main entrance position and the projection point of the center point of the exhibition area ground on the central axis form a positioning triangle 4, and the perimeter of the triangle is calculated as the exposure potential of the exhibition area 3 in the exhibition hall.

[0064] It should be understood that it is difficult to fully evaluate the visibility and accessibility of the exhibition area in the exhibition hall by relying solely on the straight-line distance from the center point of the exhibition area to the main entrance. To this end, the present invention introduces the ground central axis 2 as a spatial reference benchmark, further establishes the spatial correlation between the exhibition area 3 and the central axis, and quantifies its centrality or marginality in the overall spatial layout by calculating the vertical distance of the center point of the exhibition area ground relative to the central axis. On this basis, the perimeter of the positioning triangle 4 constructed by combining the straight-line distance and vertical distance from the exhibition area 3 to the entrance can be used as an important indicator to measure the exposure potential of the exhibition area 3 in the exhibition hall. Specifically, the shorter the distance from the exhibition area 3 to the entrance and the smaller its vertical distance relative to the central axis, that is, the smaller the perimeter of the positioning triangle 4, the closer the exhibition area 3 is to the core display area of ​​the exhibition hall, and has higher spatial accessibility and visual guidance advantages. Therefore, it is easier to be noticed by the audience and has stronger exposure potential and display priority.

[0065] S35. Map the exposure potential of each exhibition area 3 in the set of spatially adjacent exhibition areas with the hierarchical association relationship between the corresponding matching themes and their subordinate exhibits in the exhibit theme knowledge graph to obtain the exhibits mapped to each exhibition area 3 in the set of spatially adjacent exhibition areas.

[0066] In the preferred implementation of the above operation, the specific mapping of exhibition area 3 and exhibits adopts a mapping strategy of high exposure potential corresponding to low-level exhibits, that is, the exhibition area 3 with higher exposure potential is used first to display macro-representative exhibits, while the exhibition area 3 with relatively low exposure potential is used to display more specific and subdivided exhibits.

[0067] This strategy ensures that the most visually appealing and symbolically significant exhibits are placed at key locations along the visitor's movement path, enabling the exhibition content to unfold naturally from the overall to the specific, and from the general to the specific. This not only achieves an optimal allocation between spatial resources and the value of exhibits, but also effectively enhances the narrative logic and educational guidance of the exhibition content, enabling the audience to gradually understand the exhibition theme during the visit, thereby enhancing the overall exhibition experience and cultural communication effect.

[0068] S36. Digitally model the exhibits involved in the exhibition hall to generate exhibit model bodies that are consistent with their actual shapes and sizes, thereby achieving the reproduction of the exhibits. Then, in the three-dimensional model of the exhibition hall, the exhibit model bodies are arranged in the corresponding exhibition area 3 according to the mapping relationship between the exhibition area 3 and the exhibits.

[0069] The present invention establishes a structured exhibit theme knowledge graph based on the theme classification and hierarchical labels of the exhibits in the constructed three-dimensional exhibition hall model, and on this basis combines the spatial proximity relationship of the exhibition area to realize the targeted layout of exhibits in the exhibition hall, so that exhibits with the same theme can be adjacent or clustered in physical space, effectively improving the logical coherence and thematic consistency of the exhibition content, and enhancing the audience's cognitive continuity and immersive experience during the visit.

[0070] S4. Extract the crowd density distribution characteristics of exhibits in similar exhibition halls in the past and divide them into gradient-increasing crowd density. Based on this, perform dynamic crowd density simulation for each exhibition area 3. After the simulation, use the light sources distributed in the exhibition area 3 to set different lighting conditions for lighting rendering.

[0071] In an optional implementation of the above scheme, the crowd density distribution characteristics of exhibits in historical similar exhibition halls are extracted to divide the gradient increasing crowd density as follows: the maximum and minimum crowd density of each exhibit is extracted from the historical exhibition records of similar exhibition halls.

[0072] It should be pointed out that the historical similar exhibition halls mentioned above refer to physical exhibition halls that are highly similar in terms of exhibition type, spatial layout, exhibit attributes and target audience.

[0073] During implementation, visual sensors, such as infrared cameras, can be deployed within exhibition area 3, where the exhibits are located, to continuously monitor and capture images of visitor distribution during the exhibition. Visitor counts are calculated based on the captured images, and the visitor density is calculated based on the spatial volume of exhibition area 3.

[0074] By continuously monitoring the changes in crowd density throughout the entire exhibition cycle, the maximum and minimum crowd density corresponding to each exhibit can be extracted. The maximum crowd density reflects the highest crowd gathering intensity experienced by the exhibit during the exhibition, and the minimum crowd density reflects the lowest crowd density of the exhibit during relatively unpopular periods.

[0075] The above-mentioned maximum values ​​constitute the upper and lower limits of the actual crowd flow behavior in historical exhibitions, which helps to construct a reasonable crowd flow simulation range.

[0076] Cluster analysis was performed on the maximum visitor flow density and minimum visitor flow density corresponding to the same exhibits in multiple historical similar exhibition halls to determine the historical maximum visitor flow density tendency value and the historical minimum visitor flow density tendency value of each exhibit.

[0077] It should be understood that cluster analysis uses a clustering algorithm to identify data clusters with similar characteristics in a data set. The above solution is applied to form a numerical data set with the maximum visitor flow density of the same exhibits in multiple historical similar exhibition halls. The data set is then processed using a clustering algorithm to identify data clusters with similar density distribution characteristics.

[0078] Furthermore, by statistically analyzing the number of samples in each cluster, the cluster with the largest number of samples was selected as the main crowd density distribution range of the exhibit in the historical scenario, and the mean of all samples in the cluster was calculated as the historical maximum crowd density tendency value of the exhibit.

[0079] Similarly, for the minimum visitor flow density of exhibits in similar exhibition halls in history, the same cluster analysis process is used to extract the corresponding historical minimum visitor flow density tendency value.

[0080] This clustering analysis of historical crowd density trends effectively avoids the anomalies introduced by selecting a single historical value. In actual exhibitions, some extremely high or low crowd density values ​​are often caused by temporary factors and are not universal or representative. Clustering methods can identify and eliminate these outliers, thereby extracting more statistically consistent data clusters and improving the robustness and credibility of the analysis results. Furthermore, the trend values ​​derived from clustering more closely resemble the typical performance of exhibits in conventional exhibition environments, reflecting the actual crowd flow characteristics in most scenarios and making them suitable for simulation.

[0081] The allowed crowd density of each exhibition area 3 is extracted from the exhibition hall design file.

[0082] It should be noted that the above-mentioned allowable crowd density is a physical constraint, which is the upper limit of safe crowd flow set in the exhibition hall design based on parameters such as building codes, fire protection requirements, space size, and ventilation conditions.

[0083] The historical maximum crowd density tendency value of each exhibit is compared with the allowed crowd density of exhibition area 3 where the corresponding exhibit is arranged in the current exhibition hall. If the historical maximum crowd density tendency value of the exhibit is less than the allowed crowd density of exhibition area 3, the crowd density tendency value is used as the upper limit of the crowd density that can be achieved in exhibition area 3 in the simulation; otherwise, the allowed crowd density of exhibition area 3 is used as the upper limit of the crowd density.

[0084] Combining the historical minimum crowd density tendency value of the exhibits with the aforementioned upper limit crowd density, a crowd density simulation range for the exhibition area is constructed.

[0085] It should be explained that after obtaining the historical maximum and minimum crowd density data of the exhibits, they were not directly used as the value range for the crowd density simulation of the exhibition area. Instead, they were further combined with the physical constraint condition of the allowable crowd density of exhibition area 3. The purpose of this design is to ensure the feasibility and safety of the constructed crowd density simulation range in actual application.

[0086] The crowd density simulation interval of the exhibition area is sampled according to the preset step length to generate a number of crowd density values, which are arranged in ascending order to form a gradient increasing crowd density sequence.

[0087] Each crowd density value in the gradient-increasing crowd density sequence formed above is regarded as a crowd scene, which can cover dynamic crowd scenes from deserted to peak, and is convenient for crowd simulation in the three-dimensional model of the exhibition hall.

[0088] In a further optional implementation of the above scheme, after simulation, different lighting conditions are set using the light sources distributed in exhibition area 3 for lighting rendering. Refer to the following process: according to the type of light source arranged above exhibition area 3, the light intensity output range and light color output range supported by the light source are determined.

[0089] In the above optional implementation example, the light source type can be LED spotlights, track lights, floodlights, etc. The light intensity output range and light color output range supported by the light source can be obtained from the instructions based on the physical properties and technical parameters of the light source.

[0090] Node division is performed within the range of light intensity and light color output to generate several discrete value sets. A set of lighting condition combinations is constructed by combining different light intensity nodes and light color nodes. Each combination represents a specific display lighting solution.

[0091] In the three-dimensional model of the exhibition hall, after each gradient-increasing crowd density simulation is completed, the light source arranged above the exhibition area 3 is used to sequentially apply the above-mentioned lighting condition combination set for lighting rendering.

[0092] S5. During the lighting rendering process, several virtual observation points are selected based on the exhibition activity area of ​​exhibition area 3 to simulate the user's perspective to collect visual effect data. Based on the visual effect data of different lighting conditions and different observation points corresponding to different crowd densities in exhibition area 3, the lighting conditions suitable for different crowd densities are determined.

[0093] In the manner in which the above scheme can be implemented, selecting several virtual observation points based on the viewing activity area of ​​exhibition area 3 includes the following: determining the viewing activity area of ​​each exhibition area 3 in the three-dimensional model of the exhibition hall, and extracting the visitor's visible boundary line therefrom.

[0094] It should be pointed out that the above-mentioned visitor visual boundary line is usually the side of exhibition area 3 facing the audience's passage path, or the effective viewing field boundary set according to the exhibit layout. Specifically, the exhibition activity area of ​​exhibition area 3 and its corresponding visual boundary line extraction can be obtained based on the exhibition hall design drawings.

[0095] Taking the location of the exhibits in exhibition area 3 as the visual focus center, radial rays are projected from this center along the horizontal direction toward the visitor's visible boundary line at preset angle intervals. The intersection of each ray and the visible boundary line is defined as a virtual observation point.

[0096] The above selection of several virtual observation points from the visitor's visible boundary line can effectively simulate the audience's real perspective of viewing exhibits at different directions and distances, providing a spatial sampling basis for subsequent exhibition effect evaluation.

[0097] The above-mentioned display effect data includes exhibit visibility and color rendering index. Exhibit visibility measures whether the audience can see the details of the exhibits clearly and without interference under specific lighting conditions. Exhibit visibility mainly refers to the light intensity of the light source in exhibition area 3. The color rendering index reflects the ability of the light source to reproduce the true color of the object, mainly focusing on the color characteristics of light.

[0098] For example, the exhibit visibility acquisition process: ray tracing is used to perform lighting simulation in a three-dimensional exhibition hall simulation environment to generate high-precision rendering images, and the brightness distribution and contrast of the exhibit area are obtained through image processing to represent the exhibit visibility level.

[0099] For example, the display index acquisition process is: after defining the spectral power distribution characteristics of the light source in a simulation environment, calling the built-in light color analysis calculation of the rendering engine or lighting simulation software to output the corresponding color rendering index.

[0100] It should be pointed out that the above-mentioned color rendering index collection process belongs to the existing technology, and the relevant technical details are not repeated here.

[0101] In a further implementation of the above scheme, the lighting conditions suitable for different crowd densities are determined as follows: under the same crowd density, the visual effect data of all virtual observation points are extracted for each lighting condition and compared with the preset visual presentation quality standard, and the proportion of the number of observation points that meet the visual quality requirements to the total number of observation points is counted and recorded as the effective visual proportion.

[0102] The effective visual ratios of exhibition area 3 under different lighting conditions at the same crowd density are compared, and the lighting condition and crowd density corresponding to the maximum effective visual ratio are selected to form an adaptive mapping.

[0103] After completing the layout of the exhibits, the present invention performs a dynamic simulation of the crowd density based on the historical crowd distribution data of exhibition area 3, and sets a variety of lighting conditions in combination with the light source arranged above exhibition area 3 for lighting rendering. During the rendering process, the user's perspective is simulated and visual effect data is collected to match the optimal lighting scheme for different crowd density scenes, thereby realizing refined and adaptive control of the display lighting, effectively improving the display effect and visual comfort of the exhibits in multiple scenarios, and at the same time enhancing the intelligence level and energy efficiency management capabilities of the exhibition hall lighting system.

[0104] In the improved implementation of the above scheme, S5 also includes determining the best viewing position for visitors. For details, please refer to the following content: under each specific crowd density and adaptive lighting conditions, the visual effect data of all virtual observation points are compared to identify the virtual observation point with the best visual effect, and the observation point is determined as the best viewing position under the corresponding crowd density.

[0105] The present invention helps to improve the overall viewing experience and optimize the exhibition hall layout design by determining the best viewing position at a given crowd density, which can provide the audience with the best visual experience.

[0106] The above embodiments may be implemented in whole or in part through software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0107] Those skilled in the art will appreciate that the algorithmic steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0108] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0109] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0110] Finally, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for importing, constructing and analyzing three-dimensional scene portrait design elements, characterized in that: The following steps are involved: S1. Obtain the exhibition hall's spatial structure data, including the geometric boundaries of each exhibition area, the topological relationship between the exhibition areas, and the distribution of light sources, and construct a three-dimensional model of the exhibition hall; S2. Extract the exhibit themes and their label hierarchy from the exhibition hall design documents, construct an exhibit theme knowledge graph, and import it into the exhibition hall 3D model; S3. Arrange exhibits in the 3D model of the exhibition hall based on the spatial proximity of exhibition areas and the knowledge graph of exhibit themes; S4. Extract the crowd density distribution characteristics of exhibits in similar exhibition halls from history and divide them into gradient-increasing crowd density. Based on this, perform a dynamic crowd density simulation of the exhibition area where the exhibits are arranged. After the simulation, use the light source arranged above the exhibition area to set different lighting conditions for lighting rendering; The method of extracting the crowd density distribution characteristics of exhibits in similar exhibition halls in the past and dividing the crowd density into gradient increasing crowd density is implemented as follows: Extract the maximum and minimum visitor density of each exhibit from the historical visitor records of similar exhibition halls; Cluster analysis was performed on the maximum and minimum visitor flow densities corresponding to the same exhibits in multiple similar exhibition halls to determine the historical maximum and minimum visitor flow density tendency values ​​for each exhibit; Extract the allowed crowd density of each exhibition area from the exhibition hall design documents; Compare the historical maximum crowd density tendency value of each exhibit with the permitted crowd density of the corresponding exhibit layout in the current exhibition hall. If the historical maximum crowd density tendency value of the exhibit is lower than the permitted crowd density of the exhibition area, the historical maximum crowd density tendency value will be used as the upper limit of the crowd density that can be achieved in the simulation. Otherwise, the permitted crowd density of the exhibition area will be used as the upper limit of the crowd density. Combine the historical minimum crowd density tendency value of the exhibit with the aforementioned upper limit of crowd density to construct a crowd density simulation range for the exhibition area; The crowd density simulation interval of the exhibition area is sampled according to the preset step length to generate a number of crowd density values, and then arranged in ascending order to form a gradient increasing crowd density sequence; S5. During the lighting rendering process, several virtual observation points are selected based on the exhibition area's viewing activity area to simulate the user's perspective to collect visual effect data. Based on the different lighting conditions corresponding to different crowd densities in the exhibition area and the visual effect data at different observation points, the lighting conditions suitable for different crowd densities are determined.

2. The method for importing, constructing and analyzing three-dimensional scene portrait design elements according to claim 1, characterized in that: The construction of the exhibit theme knowledge graph is implemented as follows: Extract the display theme of each exhibit from the exhibition hall design file, and then classify the exhibits with the same theme into a set of exhibits corresponding to each display theme; For each exhibition theme, the exhibits are arranged in order from low to high levels according to the theme label level to establish a hierarchical relationship between the exhibits; The display themes and hierarchical association relationships of the exhibits are integrated into a directed acyclic graph, where nodes represent themes or exhibits and edges represent label levels, thereby constructing an exhibit theme knowledge graph.

3. The method for importing, constructing and analyzing three-dimensional scene portrait design elements according to claim 2, characterized in that: The specific implementation process of S3 is as follows: S31. Selecting adjacent exhibition areas based on the geometric boundaries of each exhibition area in the three-dimensional model of the exhibition hall through spatial adjacency analysis to form a set of spatially adjacent exhibition areas; S32, counting the number of exhibition areas in each spatially adjacent exhibition area set, and matching this number with the number of exhibits in the exhibit set corresponding to each theme, thereby screening out the theme that matches each spatially adjacent exhibition area set; S33. Construct a ground central axis in the three-dimensional model of the exhibition hall with the main entrance of the exhibition hall as the starting point, and obtain the distance from the ground center point of each exhibition area in the set of spatially adjacent exhibition areas to the entrance and its vertical distance relative to the central axis; S34. Based on the two distances, a positioning triangle is formed by combining the center point of the exhibition area, the main entrance, and the projection of the center point of the exhibition area on the central axis. The perimeter of the triangle is calculated as the exposure potential of the exhibition area in the exhibition hall. S35. Mapping the exposure potential of each exhibition area in the set of spatially adjacent exhibition areas with the hierarchical association relationship between the corresponding matching themes and their subordinate exhibits in the exhibit theme knowledge graph to obtain the exhibits mapped to each exhibition area in the set of spatially adjacent exhibition areas; S36. Digitally model all exhibits in the exhibition hall to generate exhibit model bodies that are consistent with their actual shapes and sizes, and then arrange the exhibit model bodies in corresponding exhibition areas in the three-dimensional model of the exhibition hall according to the mapping relationship between the exhibition areas and the exhibits.

4. The method for importing, constructing and analyzing three-dimensional scene portrait design elements according to claim 3, characterized in that: The specific contents of S31 are as follows: In the three-dimensional model of the exhibition hall, each exhibition area is regarded as a target exhibition area, and the distance between the target exhibition area and other exhibition areas is calculated based on the geometric boundary of the target exhibition area; In the three-dimensional model of the exhibition hall, based on the topological relationship of the exhibition areas, it is determined whether the target exhibition area is connected to other exhibition areas through a passage or has a shared boundary. The spatial proximity determination rules are set as follows: a) The distance between other exhibition areas and the target exhibition area is less than or equal to the preset distance threshold; b) Other exhibition areas are connected to the target exhibition area by passages or share a common boundary with the target exhibition area; According to the above judgment rules, a set of exhibition areas that meet any of the rules is selected to form a set of spatially adjacent exhibition areas.

5. The method for importing, constructing and analyzing three-dimensional scene portrait design elements according to claim 1, characterized in that: After the simulation, different lighting conditions are set using the light sources arranged above the exhibition area for lighting rendering. See the following process: Determine the light intensity output range and light color output range supported by the light source based on the type of light source arranged above the exhibition area; Node division is performed within the range of light intensity and light color output to generate several discrete value sets, and a light condition combination set is constructed by combining different light intensity nodes and light color nodes; In the three-dimensional model of the exhibition hall, after each gradient-increasing crowd density simulation is completed, the light sources arranged above the exhibition area are used to apply the above-mentioned lighting condition combination set in sequence for lighting rendering.

6. The method for importing, constructing and analyzing three-dimensional scene portrait design elements according to claim 1, characterized in that: The selection of several virtual observation points based on the exhibition area's viewing activity area includes the following: Determine the viewing activity area of ​​each exhibition area in the three-dimensional model of the exhibition hall and extract the visitor's visible boundary line from it; Taking the location of the exhibits in the exhibition area as the visual focus center, radial rays are projected from the center horizontally toward the visitor's visible boundary line at preset angle intervals. The intersection of each ray and the visible boundary line is defined as a virtual observation point.

7. The method for importing, constructing and analyzing three-dimensional scene portrait design elements according to claim 1, characterized in that: The visual effect data includes exhibit visibility and color rendering index.

8. The method for importing, constructing and analyzing three-dimensional scene portrait design elements according to claim 1, characterized in that: The determination of the lighting conditions adapted to different crowd densities is implemented as follows: Under the same crowd density and for each lighting condition, the visual effect data of all virtual observation points are extracted and compared with the preset visual presentation quality standard. The proportion of observation points that meet the visual quality requirements to the total number of observation points is counted and recorded as the effective visual ratio. Compare the effective visual proportions of the exhibition area under different lighting conditions at the same crowd density, and select the lighting condition and crowd density corresponding to the maximum effective visual proportion to form an adaptive mapping.

9. The method for importing, constructing and analyzing three-dimensional scene portrait design elements according to claim 8, characterized in that: S5 also includes determining the best location for visitors to view the exhibition, including the following: Under each specific crowd density and adaptive lighting condition, the visual effect data of all virtual observation points are compared to identify the virtual observation point with the best visual effect, and this observation point is determined as the best viewing position under the corresponding crowd density.

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