Three-dimensional scene portrait design element importing, constructing and analyzing method

Abstract

The invention belongs to the field of three-dimensional scene construction and intelligent design, particularly relates to an exhibit layout and illumination design technology in an exhibition hall three-dimensional scene, and discloses a three-dimensional scene portrait design element import construction analysis method. A structured exhibit subject knowledge graph is established in a constructed three-dimensional exhibition hall model according to subject scores to which exhibits belong and hierarchical labels thereof, and on this basis, targeted layout of the exhibits in an exhibition hall is realized in combination with an exhibition area spatial proximity relationship, so that the exhibits with the same subject can be distributed adjacently or in an aggregated manner in a physical space; according to the method, logic coherence and theme consistency of exhibition content are effectively improved, people flow density dynamic simulation is carried out based on historical people flow distribution data of an exhibition area after exhibit layout is completed, and multiple illumination conditions are set in combination with a light source arranged above the exhibition area to carry out illumination rendering; in the rendering process, through simulating a user view angle and collecting visual effect data, an optimal illumination scheme is matched for scenes with different people flow 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, and specifically discloses a method for importing, constructing and analyzing three-dimensional scene portrait design elements. Background Art

[0002] With the continuous improvement of public cultural consumption awareness, exhibition halls, as important spatial carriers of information dissemination and cultural exchange, have become the core places for people to acquire knowledge, experience art and contact new technologies. The early design stage of exhibition hall construction is particularly critical. In recent years, driven by digital and intelligent technologies, the traditional exhibition hall design model is accelerating its transformation towards visualization, data-driven and intelligent decision-making. In this context, the three-dimensional scene construction design of exhibition halls based on three-dimensional modeling and spatial analysis has gradually become the main trend in modern exhibition hall planning and design. It is widely used in multiple design stages such as exhibit layout and exhibition area lighting, which significantly improves the functionality of exhibition halls and the quality of exhibition experience.

[0003] However, the existing three-dimensional scene construction design of exhibition halls usually relies on empirical arrangements in terms of exhibit layout, without fully considering the spatial proximity of the exhibition area and the theme relevance of the exhibits. This approach often leads to a disorganized distribution of exhibits and a break in the theme logic. For example, historical relics and scientific and technological exhibits are mixed in the same exhibition area, which destroys the coherence and theme consistency of the exhibition and affects the audience's understanding and immersion.

[0004] In addition, in the current three-dimensional scene construction of the exhibition hall, the lighting design mainly focuses on the presentation of the exhibits, which leads to the static setting of lighting parameters and fails to fully consider the impact of the dynamically changing crowd density on the lighting needs of the exhibition area. The visitor's visiting behavior in the exhibition hall has significant spatiotemporal flow characteristics, and the crowd density changes over time. The fixed lighting configuration is difficult to adapt to the visual perception needs in different situations. For example, in the case of high crowd density, the audience's sight is easily disturbed, and the recognition efficiency needs to be improved by enhancing the contrast between the exhibits and the background; while in the case of low crowd density, more emphasis is placed on visual comfort and detail expression. Therefore, the static lighting design cannot achieve fine-grained control of the display environment, which in turn affects the audience's visual experience quality and the best presentation effect of the 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 object of the present invention can be achieved through the following technical solutions: A method for importing, constructing, and analyzing design elements of a three-dimensional scene portrait, comprising the following steps: S1. Obtain the spatial structure data of the exhibition hall, specifically including the geometric boundaries of each exhibition area, the topological relationship of the exhibition areas, and the distribution positions of light sources, thereby constructing a three-dimensional model of the exhibition hall.

[0007] S2. Extract the exhibition themes of the exhibits and their theme label hierarchies from the exhibition hall design documents, thereby constructing a theme knowledge graph of the exhibits and importing it into the three-dimensional model of the exhibition hall.

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

[0009] S4. Extract the characteristics of the pedestrian flow density distribution of the exhibits in historical similar exhibition halls to divide the gradient-increasing pedestrian flow density. Accordingly, perform a dynamic simulation of the pedestrian flow density for the exhibition areas where the exhibits are arranged, and use the light sources arranged above the exhibition areas to set different lighting conditions for lighting rendering after the simulation.

[0010] S5. During the lighting rendering process, select a number of virtual observation points based on the viewing activity areas of the exhibition areas to simulate the user's perspective and collect visual effect data. Determine the lighting conditions suitable for different pedestrian flow densities based on the visual effect data corresponding to different lighting conditions and different observation points in the exhibition areas under different pedestrian flow densities.

[0011] Combining all the above technical solutions, the positive effects of the present invention are as follows: 1. By establishing a structured theme knowledge graph of the exhibits based on the exhibition themes of the exhibits and their label hierarchies in the constructed three-dimensional exhibition hall model, and combining the spatial proximity relationship of the exhibition areas on this basis, the present invention realizes the targeted arrangement of the exhibits in the exhibition hall, enabling the exhibits with the same theme to be adjacent or aggregated in the physical space, effectively improving the logical coherence and theme consistency of the exhibition content, and enhancing the cognitive continuity and immersive experience of the audience during the visit.

[0012] 2. After the arrangement of the exhibits is completed, the present invention performs a dynamic simulation of the pedestrian flow density based on the historical pedestrian flow distribution data of the exhibition areas, and combines the light sources arranged above the exhibition areas to set a variety of lighting conditions for lighting rendering. During the rendering process, by simulating the user's perspective and collecting visual effect data, the present invention matches the optimal lighting scheme for different pedestrian flow density scenarios, realizes the refined and adaptive control of the display lighting, effectively improves the display effect and visual comfort of the exhibits in multiple scenarios, and enhances the intelligent level and energy efficiency management ability of the exhibition hall lighting system. Description of the Drawings

[0013] The present invention is further described with reference to the accompanying drawings, but the embodiments in the drawings do not constitute any limitation to the present invention. For those of ordinary skill in the art, other drawings can be obtained according to the following drawings without creative efforts.

[0014] Figure 1 This is the flowchart of the method implementation steps of the present invention.

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

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

[0017] Reference numerals: 1 - main entrance of the exhibition hall, 2 - ground central axis, 3 - exhibition area, 4 - positioning triangle. Detailed implementation manners

[0018] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

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

[0020] In the specific embodiments of the above steps, the geometric boundaries of the exhibition area 3 cover the spatial positions and dimensional parameters of building elements such as walls, floors, and ceilings, and are used to accurately describe the physical space range of each exhibition area 3.

[0021] The topological relationship of the exhibition areas reflects the spatial adjacency and connectivity between different regions, including the position information of connection structures such as channels, corridors, and entrances and exits. For example, an exhibition area 3 may be directly connected to a channel, and this channel leads to another exhibition area 3. By collecting the topological relationship of the exhibition areas, the internal spatial structure and its coherence of the entire exhibition hall can be clearly represented.

[0022] The light source distribution information includes the types and spatial arrangements of the lighting devices on the top of each exhibition area 3.

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

[0024] S2. Extract the exhibition themes of exhibits and their hierarchical theme tags from the exhibition hall design documents, construct an exhibit theme knowledge graph based on this, and import it into the 3D model of the exhibition hall.

[0025] It should be added that each exhibit in the exhibition hall belongs to a clear exhibition theme, and these themes reflect the essential attributes and exhibition values of the exhibits, including their core content, cultural background, technical features, etc. Specifically, the theme can reveal key information such as the historical period, artistic style, scientific field, and functional use of the exhibit, and build a systematic cognitive path and clear understanding framework for the audience.

[0026] Furthermore, exhibition themes are usually organized in a hierarchical tag system, which reflects the hierarchical logical relationship between themes. Low-level themes represent macroscopic exhibition directions or knowledge fields, while high-level themes correspond to more specific subclasses or detailed content.

[0027] It is further supplemented that the exhibition themes and hierarchical theme tags of each exhibit in the exhibition hall design documents are usually clearly recorded. This is because the exhibition hall design documents, as the basic documents for exhibition hall planning, contain all key information from exhibit selection to space layout. The exhibition themes and tag hierarchies of the exhibits are necessary components to ensure the integrity and accuracy of the design scheme, and help designers, curators, and relevant stakeholders comprehensively understand the value and positioning of each exhibit.

[0028] As a way to implement the above solution, the construction of the exhibit theme knowledge graph is implemented as follows:

[0029] Extract the exhibition themes of each exhibit from the exhibition hall design documents, and then classify the exhibits with the same theme to form an exhibit set corresponding to each exhibition theme.

[0030] For the exhibit set under each exhibition theme, arrange the exhibits in an orderly manner from low-level to high-level according to their tag hierarchies based on the theme tag hierarchy to establish a hierarchical association relationship between the exhibits.

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

[0032] See Figure 2 As shown, integrate the exhibition themes of the exhibits and the hierarchical association relationship into a directed acyclic graph, where the nodes represent themes or exhibits, and the edges represent the tag hierarchy, thus constructing an exhibit theme knowledge graph.

[0033] By constructing an exhibit theme knowledge graph based on the display theme of the exhibits and their hierarchical tags, the present invention can intuitively display the classification and attribution relationships of the exhibits under different hierarchical theme tags. This knowledge graph helps to clearly present the overall narrative framework of the exhibition content, revealing the logical associations and semantic levels among the exhibits. Through this structured expression, the audience can more conveniently understand the theme context of the exhibition, achieve a representative exhibit cognition at the macroscopic level, and gradually delve into the details of the exhibits in specific categories or specific historical periods, thereby improving the cognitive efficiency of visiting the exhibition.

[0034] S3. Based on the spatial proximity relationship of Exhibition Area 3 and the exhibit theme knowledge graph, arrange the exhibits in the three-dimensional model of the exhibition hall.

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

[0036] Further preferably, the specific implementation of S31 is as follows: In the three-dimensional model of the exhibition hall, take each Exhibition Area 3 as the target exhibition area, and then calculate the distance between it and other Exhibition Areas 3 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 other Exhibition Areas 3 is as follows: Extract the boundary lines of the target exhibition area and other Exhibition Areas 3.

[0038] Identify and capture the set of vertices on the boundary line of the target exhibition area, and at the same time identify and capture the set of edges on the boundary line of other Exhibition Areas 3.

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

[0040] Finally, select the minimum value from all the calculated distances as the distance between the target exhibition area and other Exhibition Areas 3.

[0041] The above calculation of the perpendicular distance from the boundary vertices of the target exhibition area to the boundaries of other Exhibition Areas 3 can accurately quantify the minimum spatial interval between two Exhibition Areas 3. It is applicable to various Exhibition Areas 3 with complex shapes, whether regular polygons or irregular shapes, and the shortest distance can be found through computational geometry methods, with strong versatility.

[0042] In the three-dimensional model of the exhibition hall, based on the topological relationship of the exhibition areas, identify whether there is a passage connection or a shared boundary between the target exhibition area and the remaining Exhibition Areas 3.

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

[0044] b) There is a passage connecting or a shared boundary between the other exhibition area 3 and the target exhibition area.

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

[0046] Rule b takes into account 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, through clear passage guidance, they may still be perceived by the audience as closely related spatial units.

[0047] Based on the above determination rules, the set of exhibition areas 3 that meet any one of the rules is selected to form the set of spatially adjacent exhibition areas.

[0048] In the above operation example, it is assumed that there are 10 exhibition areas 3 in the exhibition hall, numbered A to J in sequence. Taking A as the target exhibition area as an example, first calculate the shortest spatial distance between its geometric boundary and other exhibition areas 3. According to rule a, the exhibition areas 3 whose distance from A is less than or equal to the preset threshold are selected, and the results are C and D.

[0049] At the same time, by analyzing the topological relationship between A and other exhibition areas 3, it is judged whether there is a situation of passage 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, the exhibition areas C and D that meet rule a, and the exhibition area F that meets rule b are combined to form a set of spatially adjacent exhibition areas, that is: {A, C, D, F}.

[0051] The above method for obtaining spatially adjacent exhibition areas not only considers the degree of physical proximity but also takes into account the functional connectivity, and can more comprehensively reflect the true adjacent state between exhibition areas 3.

[0052] S32. Count the number of exhibition areas 3 in each set of spatially adjacent exhibition areas, and match this number with the number of exhibits in the exhibit sets corresponding to each theme, thereby screening out the theme matched by each set of spatially adjacent exhibition areas.

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

[0054] Meanwhile, all the classified display themes are sorted in descending order according to the number of exhibits in their corresponding exhibit sets, generating a theme priority sequence.

[0055] Successively take out the currently highest-ranked theme from the theme priority sequence and match it with each unmatched exhibition area set in the exhibition area set priority sequence.

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

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

[0058] After each match, remove the theme and the corresponding exhibition area set as the matched objects from their respective priority sequences.

[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 there are only themes / sets that cannot meet the minimum matching conditions left.

[0060] It should be understood that by comparing the number requirements of exhibits under different themes with the physical capacity that the spatially adjacent exhibition area sets can provide, and finding the best match, it can be ensured that each spatial unit composed of spatially adjacent exhibition area sets will neither be crowded due to too many exhibits nor waste space resources due to too few exhibits.

[0061] S33. In the 3D model of the exhibition hall, construct the ground central axis 2 starting from the main entrance 1 of the exhibition hall, and respectively obtain the distance from the ground center point of each exhibition area in the spatially adjacent exhibition area set to the entrance and its vertical distance relative to the central axis.

[0062] It should be pointed out that the central axis is set starting from the main entrance of the exhibition hall. As the main passage for the audience to enter the exhibition hall, it usually plays a core guiding role in the exhibition space layout. Extending along the geometric center of the internal space of the exhibition hall from the main entrance, the continuous path formed on the ground constitutes the ground central axis 2, which can run through the key display areas of the exhibition hall. In the actual construction process, the ground central axis 2 can be constructed according to the design drawings of the exhibition hall.

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

[0064] It should be understood that relying solely on the straight-line distance from the center point of the exhibition area floor to the main entrance makes it difficult to comprehensively evaluate its visibility and accessibility in the exhibition hall. Therefore, the present invention introduces the ground central axis 2 as a spatial reference benchmark, further establishes the spatial correlation relationship 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 floor relative to the central axis. On this basis, the perimeter of the positioning triangle 4 constructed by combining the straight-line distance and the 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, when the distance from the exhibition area 3 to the entrance is shorter and its vertical distance relative to the central axis is also smaller, that is, the perimeter of the positioning triangle 4 is smaller, the exhibition area 3 is closer to the core exhibition area of the exhibition hall, has higher spatial accessibility and visual guidance advantages, and is therefore more likely to be noticed by the audience, with 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 to the hierarchical association relationship between the corresponding matching themes and the exhibits under them in the exhibit theme knowledge graph, and obtain the exhibits mapped by each exhibition area 3 in the set of spatially adjacent exhibition areas.

[0066] In a preferred implementation of the above operation, the specific mapping between the exhibition area 3 and the exhibits adopts a mapping strategy where high exposure potential corresponds to low-level exhibits, that is, the exhibition area 3 with higher exposure potential is preferentially used to display macroscopic representative exhibits, while the exhibition area 3 with relatively lower exposure potential is used to display more specific and sub-level exhibits.

[0067] Through this strategy, it is ensured that the most visually appealing and symbolic exhibits are arranged at key positions in the audience flow line, thereby realizing the natural unfolding process of the exhibition content from the whole to the part and from the general to the specific. This not only achieves the optimal allocation between spatial resources and the value of the 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 and improving the overall exhibition experience and cultural dissemination effect.

[0068] S36. Perform digital modeling on the exhibits involved in the exhibition hall to generate exhibit modeling bodies that are consistent with their actual shapes and sizes, realizing the reproduction of the exhibits, and then deploy the exhibit modeling bodies to the corresponding exhibition areas 3 in the three-dimensional model of the exhibition hall according to the mapping relationship between the exhibition areas 3 and the exhibits.

[0069] In the present invention, a structured exhibit theme knowledge graph is established in the constructed 3D exhibition hall model according to the themes and their hierarchical tags to which the exhibits belong. On this basis, combined with the spatial proximity relationship of the exhibition areas, targeted layout of the exhibits in the exhibition hall is realized, so that the exhibits with the same theme can be adjacent or aggregated in the physical space, effectively improving the logical coherence and theme consistency of the exhibition content, and enhancing the cognitive continuity and immersive experience of the audience during the visit.

[0070] S4. Extract the characteristics of the crowd flow density distribution of the exhibits in historical similar exhibition halls, divide the gradient-increasing crowd flow density, and accordingly perform dynamic simulation of the crowd flow density 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 alternative implementation of the above solution, the implementation of extracting the characteristics of the crowd flow density distribution of the exhibits in historical similar exhibition halls and dividing the gradient-increasing crowd flow density is as follows: extract the maximum and minimum crowd flow densities of each exhibit from the viewing records of historical similar exhibition halls.

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

[0073] In the specific implementation process, visual sensors such as infrared cameras can be arranged in the exhibition area 3 where the exhibits are located to continuously monitor and collect images of the audience distribution during the exhibition. Based on the collected images, the number of visitors is counted, and combined with the spatial volume of the exhibition area 3, the crowd flow density during the visit is calculated.

[0074] Through continuous monitoring of the changes in the crowd flow density during the entire exhibition period, the maximum crowd flow density and the minimum crowd flow density corresponding to each exhibit can be extracted. Among them, the maximum crowd flow density reflects the highest intensity of crowd gathering experienced by the exhibit during the exhibition, and the minimum crowd flow density reflects the lowest crowd density during relatively unpopular periods of the exhibit.

[0075] The above maximum and minimum values constitute the upper and lower limit references for the actual crowd flow behavior of the exhibits in historical exhibitions, which helps to construct a reasonable crowd flow simulation interval.

[0076] Perform cluster analysis on the maximum crowd flow density and the minimum crowd flow density corresponding to the same exhibit in multiple historical similar exhibition halls respectively to determine the historical maximum crowd flow density tendency value and the historical minimum crowd flow density tendency value of each exhibit.

[0077] It should be understood that cluster analysis uses clustering algorithms to identify clusters of data with similar characteristics in a dataset. Applying this to the above solution, the maximum viewing flow density of the same exhibits in multiple historical similar exhibition halls forms a numerical dataset. Subsequently, a clustering algorithm is used to process this dataset to identify clusters of data with similar density distribution characteristics.

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

[0079] Similarly, for the minimum viewing flow density of the exhibit in historical similar exhibition halls, the same clustering analysis process is used to extract its corresponding historical minimum flow density tendency value.

[0080] On the one hand, the above-mentioned historical flow density tendency obtained through cluster analysis can effectively avoid abnormal interference caused by selecting a single historical value. In the actual exhibition process, some extremely high or low flow density values are often caused by temporary factors and do not have universality and representativeness. The clustering method can identify and eliminate these outlier samples, thereby extracting more statistically consistent clusters and improving the robustness and credibility of the analysis results. On the other hand, the tendency value obtained by clustering is closer to the typical performance of the exhibit in a regular exhibition environment, reflecting its true flow characteristics in most scenarios and being suitable for simulation.

[0081] Extract the allowable carrying flow density of each exhibition area 3 from the exhibition hall design document.

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

[0083] Compare the historical maximum flow density tendency value of each exhibit with the allowable carrying flow density of the exhibition area 3 where the corresponding exhibit is arranged in the current exhibition hall. If the historical maximum flow density tendency value of the exhibit is less than the allowable carrying flow density of the exhibition area 3, then use the flow density tendency value as the upper limit flow density that can be achieved in the simulation of this exhibition area 3. Otherwise, use the allowable carrying flow density of the exhibition area 3 as the upper limit flow density.

[0084] Combine the historical minimum flow density tendency value of the exhibit with the aforementioned upper limit flow density to construct the flow density simulation interval of the exhibition area.

[0085] It should be explained that after obtaining the historical maximum and minimum crowd density data of the exhibits, they are not directly used as the value range for the crowd density simulation of the exhibition area. Instead, they are 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 practical applications.

[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, and they 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 taken 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 may be an LED spotlight, a track light, a floodlight, etc. The light intensity output range and the light color output range supported by the light source may be obtained from the instructions for use 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 light condition combination set is constructed by combining different light intensity nodes and light color nodes. Each combination represents a specific display lighting scheme.

[0091] 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 3 are used to sequentially apply the above-mentioned lighting condition combination set for lighting rendering.

[0092] S5. In the lighting rendering process, a number of 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, and the lighting conditions suitable for different crowd densities are determined based on the visual effect data of different observation points corresponding to different lighting conditions under different crowd densities in exhibition area 3.

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

[0094] It should be noted that the above-mentioned visible boundary line for tourists is usually on the side of Exhibition Area 3 facing the audience's passage path, or the effective viewing field boundary set according to the layout of exhibits. Specifically, the viewing activity area of Exhibition Area 3 and its corresponding visible boundary line can be obtained based on the exhibition hall design drawings.

[0095] Taking the layout position of the exhibits in Exhibition Area 3 as the visual focus center, starting from this center, radial rays are projected along the horizontal direction at preset angular intervals towards the visible boundary line for tourists. The intersection point of each ray and the visible boundary line is defined as a virtual observation point.

[0096] Selecting several virtual observation points from the visible boundary line for tourists above can effectively simulate the real viewing angles of the audience at different positions and distances, providing a spatial sampling basis for the subsequent evaluation of the display effect.

[0097] The above-mentioned display effect data includes the visibility of exhibits and the color rendering index. Among them, the visibility of exhibits measures whether the audience can clearly and without interference see the details of the exhibits under specific lighting conditions. The visibility of exhibits mainly targets the illumination intensity of the light sources in Exhibition Area 3, and the color rendering index reflects the ability of the light source to reproduce the true color of objects, mainly targeting the color characteristics of light.

[0098] For example, the process of collecting the visibility of exhibits: In the 3D exhibition hall simulation environment, ray tracing is used for lighting simulation to generate high-precision rendered images, and the brightness distribution and contrast of the exhibit area are obtained through image processing to characterize the visibility level of the exhibits.

[0099] For example, the process of collecting the color rendering index is: After defining the spectral power distribution characteristics of the light source in the simulation environment, the built-in light color analysis of the rendering engine or lighting simulation software is called to calculate and output the corresponding color rendering index.

[0100] It should be noted that the above process of collecting the color rendering index belongs to the prior art, and the relevant technical details will not be elaborated.

[0101] In a further realizable manner of the above solution, the lighting conditions adapted to different pedestrian flow densities are determined as follows: Under the same pedestrian flow density, for each lighting condition, the visual effect data of all virtual observation points are extracted and compared with the preset visual presentation quality standard, and the proportion of the number of observation points that meet the visual quality requirements in the total number of observation points is counted, denoted as the effective visual proportion.

[0102] The effective visual proportions of Exhibition Area 3 corresponding to each lighting condition under the same pedestrian flow density are compared, and the lighting condition corresponding to the maximum effective visual proportion is selected to form an adaptation mapping with the pedestrian flow density.

[0103] After the exhibition exhibits are arranged, the present invention conducts dynamic simulation of the crowd density based on the historical crowd distribution data of Exhibition Area 3, and sets a variety of lighting conditions for lighting rendering in combination with the light sources arranged above Exhibition Area 3. During the rendering process, by simulating the user's perspective and collecting visual effect data, an optimal lighting scheme is matched for different crowd density scenarios, realizing the 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 intelligent level and energy efficiency management ability of the exhibition hall lighting system.

[0104] In the improved implementation of the above solution, S5 further includes determining the best viewing position for visitors, specifically as follows: Under each specific crowd density and adapted lighting conditions, the visual effect data of all virtual observation points are compared to identify the virtual observation point with the optimal visual effect, and this observation point is determined as the best viewing position under the corresponding crowd density.

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

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

[0107] Those of ordinary skill in the art can realize that the algorithm steps of each example described in combination with the embodiments disclosed in this article can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0108] In addition, in each embodiment of the present application, the various functional modules can be integrated in a processing module, or each module can exist physically alone, or two or more modules can be integrated in one module.

[0109] The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in this application, and all should be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

[0110] Finally, the above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for importing, constructing and analyzing design elements of a three-dimensional scene portrait, characterized in that, It includes the following steps: S1. Obtain the spatial structure data of the exhibition hall, specifically including the geometric boundaries of each exhibition area, the topological relationship of the exhibition areas, and the distribution positions of light sources, and thus construct a three-dimensional model of the exhibition hall; S2. Extract the exhibition themes of the exhibits and their theme label hierarchies from the exhibition hall design documents, construct a knowledge graph of exhibit themes based on this, and import it into the three-dimensional model of the exhibition hall; S3. Arrange the 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 exhibit themes; S4. Extract the characteristics of the pedestrian flow density distribution of the exhibits in historical similar exhibition halls to divide the gradient-increasing pedestrian flow density, and accordingly conduct a dynamic simulation of the pedestrian flow density for the exhibition areas where the exhibits are arranged, and perform light rendering by setting different lighting conditions using the light sources arranged above the exhibition areas after the simulation; S5. During the light rendering process, select several virtual observation points based on the viewing activity areas of the exhibition areas to simulate the user's perspective and collect visual effect data, and determine the lighting conditions adapted to different pedestrian flow densities based on the visual effect data corresponding to different lighting conditions and different observation points in the exhibition areas under different pedestrian flow densities.

2. The three-dimensional scene portrait design element import, construction and analysis method according to claim 1, characterized in that: The implementation of constructing the knowledge graph of exhibit themes is as follows: Extract the exhibition themes of each exhibit from the exhibition hall design documents, and then classify the exhibits with the same theme to form an exhibit set corresponding to each exhibition theme; For the exhibit set under each exhibition theme, arrange the exhibits in an orderly manner from low level to high level according to the theme label hierarchy to establish a hierarchical association relationship between the exhibits; Integrate the exhibition themes of the exhibits and the hierarchical association relationship into a directed acyclic graph, where the nodes represent themes or exhibits, and the edges represent label hierarchies, thus constructing a knowledge graph of exhibit themes.

3. The three-dimensional scene portrait design element import, construction and analysis method according to claim 2, wherein: The specific implementation process of S3 is as follows: S31. Based on the geometric boundaries of each exhibition area in the three-dimensional model of the exhibition hall, select adjacent exhibition areas through spatial adjacency analysis to form a set of spatially adjacent exhibition areas; S32. Count the number of exhibition areas in each set of spatially adjacent exhibition areas, and match this number with the number of exhibits in the exhibit set corresponding to each theme, thereby screening out the themes matched by each set of spatially adjacent exhibition areas; S33. Build a ground central axis in the three-dimensional model of the exhibition hall starting from the main entrance of the exhibition hall, and respectively 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 above two distances, form a positioning triangle with the ground center point of the exhibition area, the position of the main entrance, and the projection point of the ground center point of the exhibition area on the central axis, and calculate the perimeter of the triangle as the exposure potential of the exhibition area in the exhibition hall; S35. Map the exposure potential of each exhibition area in the set of spatially adjacent exhibition areas to the hierarchical association relationship of the corresponding matched theme and its subordinate exhibits in the knowledge graph of exhibit themes to obtain the exhibits mapped to each exhibition area in the set of spatially adjacent exhibition areas; S36. Digitally model all the exhibits included in the exhibition hall to generate exhibit modeling bodies that are consistent with their actual shapes, sizes, etc., and then arrange the exhibit modeling bodies in the 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 three-dimensional scene portrait design element import, construction and analysis method according to claim 3, characterized in that: The specific content of S31 is as follows: In the three-dimensional model of the exhibition hall, take each exhibition area as the target exhibition area, and then calculate the distance between it and other exhibition areas based on the geometric boundary of the target exhibition area; In the 3D model of the exhibition hall, based on the topological relationship of the exhibition areas, identify whether there is a passage connection or a shared boundary between the target exhibition area and the other exhibition areas; Set the spatial proximity determination rules 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) There is a passage connection or a shared boundary between other exhibition areas and the target exhibition area; According to the above determination rules, screen out the exhibition area set that meets any one of the rules to form the spatial proximity exhibition area set.

5. A three-dimensional scene portrait design element import, construction and analysis method according to claim 1, characterized in that: The implementation of extracting the crowd flow density distribution characteristics of exhibits in historical similar exhibition halls and dividing them into gradient-increasing crowd flow densities is as follows: Extract the maximum and minimum viewing crowd flow densities of each exhibit from the viewing records of historical similar exhibition halls; Perform clustering analysis on the maximum viewing crowd flow densities and minimum viewing crowd flow densities corresponding to the same exhibit in multiple historical similar exhibition halls respectively to determine the historical maximum crowd flow density tendency value and historical minimum crowd flow density tendency value of each exhibit; Extract the allowable crowd flow density of each exhibition area from the exhibition hall design document; Compare the historical maximum crowd flow density tendency value of each exhibit with the allowable crowd flow density of the exhibition area where the corresponding exhibit is arranged in the current exhibition hall. If the historical maximum crowd flow density tendency value of the exhibit is less than the allowable crowd flow density of the exhibition area, use the crowd flow density tendency value as the upper limit crowd flow density that can be achieved in the simulation of this exhibition area. Otherwise, use the allowable crowd flow density of the exhibition area as the upper limit crowd flow density; Combine the historical minimum crowd flow density tendency value of the exhibit with the aforementioned upper limit crowd flow density to construct the crowd flow density simulation interval of the exhibition area; Sample the crowd flow density simulation interval of the exhibition area according to the preset step size to generate a number of crowd flow density values, and arrange them in ascending order to form a gradient-increasing crowd flow density sequence.

6. A method for importing, constructing, and analyzing design elements of a three-dimensional scene portrait according to claim 1, characterized in that: The following is the process for performing light rendering by setting different light conditions using the light sources arranged above the exhibition areas after the simulation: Determine the light intensity output range and light color output range supported by the light source according to the type of light source arranged above the exhibition area; Perform node division within the light intensity and light color output ranges to generate several discrete value sets, and construct a light condition combination set by combining different light intensity nodes and light color nodes; In the 3D model of the exhibition hall, when each gradient-increasing crowd flow density simulation is completed, use the light sources arranged above the exhibition areas to sequentially apply the above light condition combination set for light rendering.

7. A three-dimensional scene portrait design element import, construction and analysis method according to claim 1, characterized in that: The selection of several virtual observation points based on the viewing activity area of the exhibition area includes the following content: Determine the viewing activity area of each exhibition area in the 3D model of the exhibition hall, and extract the visible boundary line of tourists from it; Taking the layout position of the exhibit in the exhibition area as the visual focus center, project radial rays along the horizontal direction at preset angular intervals towards the visible boundary line of tourists. The intersection point of each ray and the visible boundary line is defined as a virtual observation point.

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

9. The three-dimensional scene portrait design element import, construction and analysis method according to claim 1, characterized in that: The implementation of determining the light conditions adapted to different crowd flow densities is as follows: Under the same crowd flow density, extract the visual effect data of all virtual observation points for each light condition and compare it with the preset visual presentation quality standard, and count the proportion of the number of observation points that meet the visual quality requirements in the total number of observation points, which is recorded as the effective visual ratio; Compare the effective visual occupancy ratios of the exhibition area under each lighting condition corresponding to the same crowd density, and select the lighting condition corresponding to the maximum effective visual occupancy ratio to form an adaptation mapping with the crowd density.

10. A method for importing, constructing, and analyzing design elements of a three-dimensional scene portrait according to claim 9, characterized in that: S5 also includes determining the best viewing positions for visitors, specifically including the following: Compare the visual effect data of all virtual observation points under each specific crowd density and adapted lighting condition, identify the virtual observation point with the optimal visual effect, and determine this observation point as the best viewing position corresponding to the crowd density.

Images