Exhibit display classification system based on three-dimensional virtual visualization intelligent exhibition hall

Abstract

The invention discloses an exhibit display classification system based on a three-dimensional virtual visual intelligent exhibition hall, relates to the technical field of intelligent exhibition halls, and aims to solve the problem that the construction effect is poor when a visual model of an exhibit is constructed. The laser scanner can provide high-precision measurement data, can capture details and precise sizes of exhibits, guarantees the accuracy of the three-dimensional model, carries out node calculation through the convolutional neural network, can extract deep features in the three-dimensional model, enables the model to be finer and more vivid, and improves the accuracy of the three-dimensional model. By means of parameter position confirmation and parameter curve overlapping comparison, it can be ensured that the constructed three-dimensional model is highly consistent with a real exhibit in shape and structure, defects or errors in model construction can be accurately positioned by confirming the values of the reserved white parameters, and when the integrity rate is not within the qualified range, the defects or errors in model construction can be accurately positioned. The parameters of the constructed three-dimensional model can be adjusted according to the blank leaving parameters.

Description

Technical Field

[0001] The present invention relates to the technical field of smart exhibition halls, and in particular to an exhibit display classification system based on a three-dimensional virtual visualization smart exhibition hall. Background Art

[0002] The smart exhibition hall uses interactive and intelligent combinations of video, sound, animation and other media.

[0003] The Chinese patent with publication number CN111677986A discloses a smart exhibition hall display system based on three-dimensional virtual visualization. It mainly cooperates with the designed camera, three-dimensional scanner, camera, data storage module, character modeling module, computer, three-dimensional virtual projection equipment, motor and base to decorate the character model with different styles of cheongsam, and dynamically project the decorated character model in three dimensions through the three-dimensional virtual projection equipment. According to the existing cheongsam styles, the character model is digitized and decorated to achieve a customized effect. Although the above patent solves the problem of exhibit display, the following problems still exist in actual operation: 1. The user's preference for exhibits is not confirmed based on the time the user spends browsing each exhibit, resulting in the exhibit display system recommending exhibits that do not meet the user's preferences.

[0004] 2. Failure to make corresponding exhibit recommendations based on the user’s interest in the exhibit type, resulting in a poor user experience.

[0005] 3. The actual parameters of the exhibits were not accurately compared with the 3D model, resulting in poor construction of the 3D model of the exhibits. Summary of the invention

[0006] The purpose of the present invention is to provide an exhibit display classification system based on a three-dimensional virtual visualization smart exhibition hall. The laser scanner can provide high-precision measurement data, can capture the details and precise dimensions of the exhibits, and ensure the accuracy of the three-dimensional model. Through the convolutional neural network for node calculation, the deep-level features in the three-dimensional model can be extracted to make the model more refined and realistic. Through parameter position confirmation and parameter curve overlap comparison, it can be ensured that the constructed three-dimensional model is highly consistent with the real exhibit in shape and structure. By confirming these blank parameter values, the deficiencies or errors in the model construction can be accurately located. When the completeness rate is not within the qualified range, the parameters of the constructed three-dimensional model can be adjusted according to the blank parameters, which can solve the problems in the prior art.

[0007] To achieve the above object, the present invention provides the following technical solutions: The exhibit display classification system based on 3D virtual visualization smart exhibition hall includes: Exhibit information acquisition unit, used for: Confirm the basic information of the exhibits in the exhibition hall and uniquely code each exhibit and its basic information; Exhibits 3D construction unit for: According to the basic information of the exhibits, a 3D model is constructed for each exhibit. After the 3D model of the exhibit is constructed, the parameters of the constructed 3D model are compared with the standard parameters of the exhibit, and the 3D model is adjusted according to the comparison results; User login to the exhibitor unit is used to: The user enters the exhibition system through a mobile terminal. Before the user enters the exhibition system for the first time, he / she fills in the basic information of the user and selects the user's interests. The exhibition system automatically recommends the corresponding exhibit model according to the user's interests. Exhibit recommendation unit, used for: The exhibition system classifies the user's browsing habits and selected interests into favorite exhibits, and displays the favorite exhibits models according to the classification categories of the favorite exhibits.

[0008] Preferably, the exhibit information acquisition unit is further used to: Retrieve basic information of exhibits from the database; The basic information of the exhibits includes the name, size, material, author and author information of the exhibits; In addition, the basic information of each exhibit and the exhibit are stored in the database through a timestamp and a random number to generate a unique number.

[0009] Preferably, the exhibit information acquisition unit is further used to: After obtaining the basic information of the exhibit from the database, determining whether the basic information is complete; wherein the complete basic information refers to basic information including the name, size, material, author and complete information of the author of the exhibit; When the basic information is complete, the complete basic information is used as the target basic information; Retrieve the basic information corresponding to the last time the same exhibit was retrieved as reference basic information; Compare the target basic information with the reference basic information to determine whether the target basic information is consistent with the reference basic information; When the target basic information and the reference basic information are consistent, a unique number is generated for the target basic information; When the target basic information and the reference basic information are inconsistent, the target basic information and the reference basic information are used to obtain a basic information difference evaluation parameter, wherein the basic information difference evaluation parameter is obtained by the following formula: ; Among them, Y represents the basic information difference evaluation parameter; n represents the information type contained in the basic information. Since the basic information of the exhibits includes the name, size, material, author and author information of the exhibits, n=5; λ i represents the weight value corresponding to the i-th basic information type; p i represents the ratio of inconsistent information characters contained in the data information corresponding to the i-th basic information type; p max Indicates the maximum ratio of inconsistent information characters in the type contained in the basic information; p h Indicates the ratio and value of inconsistent information characters in the type contained in the basic information; h Indicates the weight and value corresponding to the information type contained in the basic information; max Indicates the weight value corresponding to the maximum ratio of inconsistent information characters appearing in the types included in the basic information; When the basic information difference evaluation parameter is not lower than a preset parameter threshold, a unique number is generated for the target basic information; When the basic information difference evaluation parameter is lower than a preset parameter threshold, information security detection is performed on the basic information of the exhibit.

[0010] Preferably, when the basic information difference evaluation parameter is lower than a preset parameter threshold, information security detection is performed on the basic information of the exhibit, including: Retrieve the basic information of the exhibits and the time point for retrieving all the information; Obtain basic information of the retrieved exhibits at each time point; The basic information of the exhibit retrieved at each time node is compared with the basic information of the exhibit entered for the first time to obtain information security evaluation parameters, wherein the information security evaluation parameters are obtained by the following formula: ; Where S represents the information security evaluation parameter corresponding to the basic information of the retrieved exhibits at each time node; Y x represents the difference evaluation parameter corresponding to the basic information of the exhibit retrieved at each time node; n represents the type of information contained in the basic information. Since the basic information of the exhibit includes the name, size, material, author and author information of the exhibit, n=5; λ i represents the weight value corresponding to the i-th basic information type; p xi It represents the ratio of inconsistent information characters contained in the i-th basic information type after comparing it with the corresponding basic information type in the basic information of the exhibit when the information is first entered; p ymaxrepresents the maximum ratio of inconsistent information characters in the inconsistent information characters contained in the i-th basic information type after comparing it with the corresponding basic information type in the basic information of the exhibit when the information is first entered; p y Indicates the ratio and value of inconsistent information characters contained in the basic information of the retrieved exhibit at each time node after comparing it with the corresponding basic information type in the basic information entered for the first time; λ h Indicates the weight and value corresponding to the information type contained in the basic information; ymax The weight value corresponding to the maximum value of the ratio of inconsistent information characters in the inconsistent information characters contained in the i-th basic information type after comparing it with the corresponding basic information type in the basic information of the exhibit when the information is first entered; The security detection parameters of the basic information of the exhibits are obtained by using the information security evaluation parameters corresponding to the basic information of the exhibits retrieved at each time node; When the security detection parameter of the basic information is lower than the preset parameter threshold, an information security alarm is issued; When the security detection parameter of the basic information is not lower than a preset parameter threshold, the exhibit is marked.

[0011] Preferably, the security detection parameters of the basic information of the exhibits are obtained by using the information security evaluation parameters corresponding to the basic information of the exhibits retrieved at each time node, including: Retrieving information security evaluation parameters corresponding to the basic information of the exhibit retrieved at each time point; The interception rate of access data for retrieving basic information of exhibits; The security detection parameters are obtained by using the information security evaluation parameters corresponding to the basic information of the exhibits retrieved at each time node and the interception rate of the access data of the basic information of the exhibits, wherein the security detection parameters are obtained by the following formula: ; Where W represents the safety detection parameter; P z represents the interception rate of access data of basic information of exhibits; m represents the number of times the basic information of exhibits is retrieved; S i represents the information security evaluation parameter corresponding to the i-th basic information retrieval; Y xi It represents the difference evaluation parameter corresponding to the basic information of the exhibits obtained when the basic information is retrieved for the i-th time.

[0012] Preferably, the exhibit three-dimensional construction unit includes: 3D model building modules for: Confirm the exhibit parameters, wherein the exhibit parameters are scanned by a laser scanner, and the three-dimensional parameters of the exhibit are obtained after the scanning is completed; Import the exhibit's 3D parameters into the 3D model to build the 3D model; After the 3D model of the exhibit is built, 3D model training is carried out; The three-dimensional model training is to confirm the data of each model node of the three-dimensional model and perform node calculation on each model node through a convolutional neural network; After node calculation, the node parameter value of each node of the three-dimensional model is obtained; The node parameter values ​​are the parameters of the constructed 3D model.

[0013] Preferably, the exhibit three-dimensional construction unit further includes: Model parameter comparison module, used for: Confirm the parameter positions of the constructed 3D model parameters and the 3D parameters of the exhibits; The parameter position is the position where the nodes in the constructed three-dimensional model and the scanned three-dimensional model of the exhibit coincide with each other; Perform parameter curve overlap comparison on the parameters of nodes with consistent parameter positions; After the parameter curves are overlapped and compared, the non-overlapping area of ​​the nodes is obtained; And confirm the blank parameter value of the non-overlapping area; The completeness rate of the constructed 3D model is determined according to the blank parameter value; When the completeness rate is not within the qualified range, the parameters of the constructed three-dimensional model are adjusted according to the blank parameters; The 3D model data that has been adjusted and constructed within the qualified range is imported into the exhibition system, and each 3D model in the exhibition system is annotated with basic information of the exhibits corresponding to the 3D model.

[0014] Preferably, the user logs in to the exhibition unit, including: User login module, used to: The user enters the exhibition system on the mobile terminal. When the user enters the exhibition system for the first time, the user fills in the basic information of the user according to the prompt of the exhibition system; Basic information includes the user’s name, age, gender, mobile phone number, and address; After the basic information is filled in, the user's face detection is performed, wherein the user's face image data is collected using the camera of the mobile terminal, and the face image data is pre-processed; After the image data preprocessing is completed, the face in the image data is feature-annotated, and the feature annotation is to mark the positions of the facial features in the image; After the image data feature annotation is completed, the image data is rotated, scaled, and cropped, and the image data is rotated, scaled, and cropped to obtain a data set of the image data; Use the MTCNN face detection algorithm model to train the face model of the data set, and optimize and adjust the face model parameters during the face model training; The DeepFace learning model is used to select the representation features of the face model, and the selected representation features are used to extract feature vectors; Finally, the feature vector is compared with the face model for similarity, and the face model is evaluated based on the similarity comparison results; After the face model is evaluated as qualified, the user's face recognition module is obtained. After the user logs into the system, the user is identified and logged in according to the face recognition model; If the face model evaluation fails, face detection will continue; After facial recognition is completed, the exhibition system lists different types of exhibits, and users can select exhibits according to their interests; Among them, the types of exhibits are listed according to the types of exhibits participating in the exhibition.

[0015] Preferably, the user login exhibition unit further includes: User interest exhibit recommendation module, used for: After the user has checked the exhibits of interest, he / she will re-enter the exhibition system; When the user re-enters the exhibition system, he / she needs to enter his / her name and password for password verification and login. After the password verification is passed, he / she can enter the exhibition system. After entering, the exhibition system recommends exhibits based on the exhibits of interest selected by the user; In addition, the exhibition system records the browsing habits of users based on the browsing time of each exhibit.

[0016] Preferably, the exhibit recommendation unit includes: User preference exhibit confirmation module is used to: Obtain the user's browsing habit data and confirm the browsing time of each exhibit based on the browsing habit; Confirm the user's preference for each exhibit based on browsing time; Favorite exhibits classification module, used for: Confirm the user's preference and determine the type of exhibits the user prefers based on the user's preference; After confirming the type of exhibits that the user likes, the exhibition system automatically recommends exhibits of the same type; And classify the exhibits according to the types of users' preferences.

[0017] Compared with the prior art, the present invention has the following beneficial effects: 1. The exhibit display classification system based on the three-dimensional virtual visualization smart exhibition hall provided by the present invention can provide high-precision measurement data with a laser scanner, which can capture the details and precise dimensions of the exhibits, ensuring the accuracy of the three-dimensional model. Through node calculation using a convolutional neural network, deep features in the three-dimensional model can be extracted to make the model more refined and realistic. Through parameter position confirmation and parameter curve overlap comparison, it can be ensured that the constructed three-dimensional model is highly consistent with the real exhibit in shape and structure.

[0018] 2. The exhibit display classification system based on the three-dimensional virtual visualization smart exhibition hall provided by the present invention lists different exhibits according to the exhibit types, allowing users to check according to their interests, so that users can find exhibits of interest more quickly, enhancing the user's sense of participation and interactivity. By recording the user's browsing habits, the system can better understand the user's interests and preferences, thereby providing users with more accurate and relevant exhibit recommendations. This helps to increase user participation and satisfaction.

[0019] 3. The exhibit display classification system based on the three-dimensional virtual visualization smart exhibition hall provided by the present invention can stimulate the interest of users and increase the time they spend on the exhibition system by recording the browsing habits of users and recommending exhibits accordingly. By analyzing the browsing habits and preferences of users, exhibitors can understand which exhibits are more popular and which exhibits may need to be improved or adjusted, thereby improving the attractiveness of exhibits and the effect of visits. By introducing face recognition technology, the system can verify the identity of users and ensure that only legitimate users can access the system. This biometric technology is more difficult to forge or crack than traditional password or verification code verification methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a schematic diagram of an exhibit display module in a smart exhibition hall of the present invention; Figure 2 It is a schematic diagram of the flow chart of the smart exhibition hall exhibit display method of the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0022] In order to solve the problem in the prior art that the actual parameters of the exhibits are not accurately compared with the 3D model when the exhibits are constructed in 3D, which leads to poor construction effect of the 3D model of the exhibits, please refer to Figure 1-Figure 2, this embodiment provides the following technical solutions: The exhibit display classification system based on 3D virtual visualization smart exhibition hall includes: Exhibit information acquisition unit, used for: Confirm the basic information of the exhibits in the exhibition hall and uniquely code each exhibit and its basic information; Exhibits 3D construction unit for: According to the basic information of the exhibits, a 3D model is constructed for each exhibit. After the 3D model of the exhibit is constructed, the parameters of the constructed 3D model are compared with the standard parameters of the exhibit, and the 3D model is adjusted according to the comparison results; User login to the exhibitor unit is used to: The user enters the exhibition system through a mobile terminal. Before the user enters the exhibition system for the first time, he / she fills in the basic information of the user and selects the user's interests. The exhibition system automatically recommends the corresponding exhibit model according to the user's interests. Exhibit recommendation unit, used for: The exhibition system classifies the user's browsing habits and selected interests into favorite exhibits, and displays the favorite exhibits models according to the classification categories of the favorite exhibits.

[0023] Specifically, the exhibit information acquisition unit can ensure that each exhibit has a unique identifier, and the exhibit 3D construction unit can confirm the parameter position and overlap the parameter curve to ensure that the constructed 3D model is highly consistent with the real exhibit in shape and structure. This precision guarantee is particularly important for exhibits such as historical relics and artworks that need to be accurately restored. The user login exhibit unit provides personalized recommendations, records browsing habits, and password verification login, which improves user participation and loyalty, optimizes exhibit display, and analyzes user browsing habits and preferences through the exhibit recommendation unit, which can create a more intimate and personalized service experience for users.

[0024] The exhibit information acquisition unit is also used for: Retrieve basic information of exhibits from the database; The basic information of the exhibits includes the name, size, material, author and author information of the exhibits; In addition, the basic information of each exhibit and the exhibit are stored in the database through a timestamp and a random number to generate a unique number.

[0025] Specifically, since the combination of timestamp and random number is unique, the generated number is also unique, which can ensure that each exhibit has a unique identifier, which is convenient for management and tracking. The timestamp records the specific time when the exhibit information is stored in the database, which can easily trace the exhibit's storage time, modification time and other information, which is helpful for the historical management and version control of the exhibits. The introduction of random numbers can increase the complexity and randomness of the numbering, reduce the risk of being guessed or forged, and improve the security of the exhibit information.

[0026] Specifically, the exhibit information acquisition unit is further used to: After obtaining the basic information of the exhibit from the database, determining whether the basic information is complete; wherein the complete basic information refers to basic information including the name, size, material, author and complete author information of the exhibit; When the basic information is complete, the complete basic information is used as the target basic information; Retrieve the basic information corresponding to the last time the same exhibit was retrieved as reference basic information; Compare the target basic information with the reference basic information to determine whether the target basic information is consistent with the reference basic information; When the target basic information and the reference basic information are consistent, a unique number is generated for the target basic information; When the target basic information and the reference basic information are inconsistent, the target basic information and the reference basic information are used to obtain a basic information difference evaluation parameter, wherein the basic information difference evaluation parameter is obtained by the following formula: ; Among them, Y represents the basic information difference evaluation parameter; n represents the information type contained in the basic information. Since the basic information of the exhibits includes the name, size, material, author and author information of the exhibits, n=5; λ i represents the weight value corresponding to the i-th basic information type; p i represents the ratio of inconsistent information characters contained in the data information corresponding to the i-th basic information type; p max Indicates the maximum ratio of inconsistent information characters in the type contained in the basic information; p h Indicates the ratio and value of inconsistent information characters in the type contained in the basic information; h Indicates the weight and value corresponding to the information type contained in the basic information; max Indicates the weight value corresponding to the maximum ratio of inconsistent information characters appearing in the types included in the basic information; When the basic information difference evaluation parameter is not lower than a preset parameter threshold, a unique number is generated for the target basic information; When the basic information difference evaluation parameter is lower than a preset parameter threshold, information security detection is performed on the basic information of the exhibit.

[0027] The technical effects of the above technical solution are as follows: First, the solution ensures the integrity of the basic information of the exhibits. By judging whether the basic information of the exhibits obtained from the database contains complete information such as name, size, material, author and author information, the basic data quality of subsequent operations is ensured.

[0028] After confirming that the basic information is complete, the plan retrieves the basic information corresponding to the last time the same exhibit was retrieved (reference basic information) and compares it with the current basic information (target basic information) to determine whether it needs to be updated. This comparison mechanism helps to discover and correct information changes in a timely manner, ensuring the accuracy and timeliness of exhibit information.

[0029] When the target basic information is consistent with the reference basic information or the difference evaluation parameter is not lower than the preset threshold, the system will generate a unique number for the target basic information. This helps to uniquely identify the exhibits and facilitate subsequent tracking, query and management.

[0030] The scheme introduces a difference evaluation parameter (Y) as a quantitative indicator to judge the degree of information difference. By calculating the inconsistent information character ratio and corresponding weight of each type of basic information, the degree of information change can be more accurately evaluated, providing a decision basis for whether to generate a unique number.

[0031] When the difference evaluation parameter is lower than the preset threshold, the system will trigger information security detection. This means that the basic information of the exhibit may have major changes or potential security risks, and further inspection and confirmation are required to ensure the security and reliability of the exhibit information.

[0032] In summary, this technical solution realizes comprehensive management and effective monitoring of exhibit information through a series of information management, comparison, update and detection measures, thereby improving the accuracy and security of exhibit information.

[0033] Specifically, when the basic information difference evaluation parameter is lower than a preset parameter threshold, information security detection is performed on the basic information of the exhibit, including: Retrieve the basic information of the exhibits and the time point for retrieving all the information; Obtain basic information of the retrieved exhibits at each time point; The basic information of the exhibit retrieved at each time node is compared with the basic information of the exhibit entered for the first time to obtain information security evaluation parameters, wherein the information security evaluation parameters are obtained by the following formula: ; Where S represents the information security evaluation parameter corresponding to the basic information of the retrieved exhibits at each time node; Y x represents the difference evaluation parameter corresponding to the basic information of the exhibit retrieved at each time node; n represents the type of information contained in the basic information. Since the basic information of the exhibit includes the name, size, material, author and author information of the exhibit, n=5; λ i represents the weight value corresponding to the i-th basic information type; p xi It represents the ratio of inconsistent information characters contained in the i-th basic information type after comparing it with the corresponding basic information type in the basic information of the exhibit when the information is first entered; p ymax represents the maximum ratio of inconsistent information characters in the inconsistent information characters contained in the i-th basic information type after comparing it with the corresponding basic information type in the basic information of the exhibit when the information is first entered; p y Indicates the ratio and value of inconsistent information characters contained in the basic information of the retrieved exhibit at each time node after comparing it with the corresponding basic information type in the basic information entered for the first time; λ h Indicates the weight and value corresponding to the information type contained in the basic information; ymax The weight value corresponding to the maximum value of the ratio of inconsistent information characters in the inconsistent information characters contained in the i-th basic information type after comparing it with the corresponding basic information type in the basic information of the exhibit when the information is first entered; The security detection parameters of the basic information of the exhibits are obtained by using the information security evaluation parameters corresponding to the basic information of the exhibits retrieved at each time node; When the security detection parameter of the basic information is lower than the preset parameter threshold, an information security alarm is issued; When the security detection parameter of the basic information is not lower than a preset parameter threshold, the exhibit is marked.

[0034] The technical effect of the above technical solution is: the technical solution retrieves all the information retrieval time nodes of the basic information of the exhibits, and compares the information of each time node with the basic information of the exhibits when the information is first entered, thereby achieving a comprehensive and historical security detection of the exhibits information. This helps to discover any potential information tampering or errors, and ensure the integrity and accuracy of the exhibits information.

[0035] By introducing information security evaluation parameters (S) and difference evaluation parameters (Yx), combined with the weight values ​​of each basic information type (λi) and the ratio of inconsistent information characters (pxi), this technical solution can accurately evaluate the security status of exhibit information at each time point. This quantitative evaluation method helps managers to more accurately judge the security level of information and take corresponding measures.

[0036] When the security detection parameters of the basic information of the exhibits are lower than the preset parameter threshold, the system will trigger an information security alarm. This timely alarm mechanism helps managers quickly discover potential information security issues and take corresponding countermeasures to avoid risks such as information leakage and tampering.

[0037] When the safety detection parameters of basic information are not lower than the preset parameter threshold, the system will mark the exhibits. This flexible management method helps managers to classify exhibits, take conventional management measures for exhibits with good safety conditions, and take more stringent management measures for exhibits with potential risks.

[0038] Through automated information security detection and assessment, this technical solution can significantly improve the efficiency of exhibit information management. Managers do not need to manually check the information of each exhibit, but can rely on the system to automatically complete these tasks, thus saving a lot of manpower and time costs.

[0039] In summary, this technical solution realizes comprehensive monitoring and management of exhibit information through comprehensive information security detection, accurate information security assessment, timely information security alarm and flexible exhibit management, effectively improving the security of exhibit information and the efficiency of management.

[0040] Specifically, the security detection parameters of the basic information of the exhibits are obtained by using the information security evaluation parameters corresponding to the basic information of the exhibits retrieved at each time node, including: Retrieving information security evaluation parameters corresponding to the basic information of the exhibit retrieved at each time point; The interception rate of access data for retrieving basic information of exhibits; The security detection parameters are obtained by using the information security evaluation parameters corresponding to the basic information of the exhibits retrieved at each time node and the interception rate of the access data of the basic information of the exhibits, wherein the security detection parameters are obtained by the following formula: ; Where W represents the safety detection parameter; P z represents the interception rate of access data of basic information of exhibits; m represents the number of times the basic information of exhibits is retrieved; S i represents the information security evaluation parameter corresponding to the i-th basic information retrieval; Yxi It represents the difference evaluation parameter corresponding to the basic information of the exhibits obtained when the basic information is retrieved for the i-th time.

[0041] The technical effect of the above technical solution is: by combining the information security evaluation parameter (Si) corresponding to the basic information of the exhibits retrieved at each time node and the interception rate (Pz) of the access data of the basic information of the exhibits, the technical solution can provide a comprehensive security detection parameter (W). This comprehensive evaluation method takes into account the integrity of the information itself and the security of the access behavior, thereby more comprehensively evaluating the security status of the basic information of the exhibits.

[0042] The security detection parameter (W) is calculated based on the real-time basic information of the exhibits and the real-time access data interception rate, so it can reflect the security status of the exhibits in real time. This real-time nature helps managers to discover and deal with potential security issues in a timely manner.

[0043] By using the corresponding information security evaluation parameters (Si) and difference evaluation parameters (Yxi) retrieved each time basic information is retrieved, managers can accurately locate which time nodes have information security risks, and take targeted measures to improve them.

[0044] By monitoring the interception rate (Pz) of access data of basic information of exhibits, this technical solution can effectively prevent unauthorized access and potential information leakage. The increase in interception rate means that the system's ability to respond to potential security threats is enhanced, further ensuring the security of exhibit information.

[0045] According to the safety detection parameter (W), managers can flexibly adjust the management strategy of exhibit information. For exhibits with lower safety detection parameters, monitoring and protection measures can be strengthened; for exhibits with higher safety detection parameters, conventional management measures can be taken to improve management efficiency.

[0046] In summary, this technical solution significantly improves the security of exhibit information and provides strong technical support for managers by comprehensively evaluating information security, reflecting security status in real time, accurately locating security risks, effectively preventing information leakage, and optimizing management strategies.

[0047] Exhibits three-dimensional construction unit, including: 3D model building modules for: Confirm the exhibit parameters, wherein the exhibit parameters are scanned by a laser scanner, and the three-dimensional parameters of the exhibit are obtained after the scanning is completed; Import the exhibit's 3D parameters into the 3D model to build the 3D model; After the 3D model of the exhibit is built, 3D model training is carried out; The three-dimensional model training is to confirm the data of each model node of the three-dimensional model and perform node calculation on each model node through a convolutional neural network; After node calculation, the node parameter value of each node of the three-dimensional model is obtained; The node parameter values ​​are the parameters of the constructed 3D model.

[0048] Model parameter comparison module, used for: Confirm the parameter positions of the constructed 3D model parameters and the 3D parameters of the exhibits; The parameter position is the position where the nodes in the constructed three-dimensional model and the scanned three-dimensional model of the exhibit coincide with each other; Perform parameter curve overlap comparison on the parameters of nodes with consistent parameter positions; After the parameter curves are overlapped and compared, the non-overlapping area of ​​the nodes is obtained; And confirm the blank parameter value of the non-overlapping area; The completeness rate of the constructed 3D model is determined according to the blank parameter value; When the completeness rate is not within the qualified range, the parameters of the constructed three-dimensional model are adjusted according to the blank parameters; The 3D model data that has been adjusted and constructed within the qualified range is imported into the exhibition system, and each 3D model in the exhibition system is annotated with basic information of the exhibits corresponding to the 3D model.

[0049] Specifically, the 3D model construction module uses a laser scanner to confirm the exhibit parameters and construct a 3D model, and then conducts 3D model training. It has the advantages of high precision, non-contact, automation, data reusability, and parametric modeling, providing strong support for the digital protection, display, and research of exhibits. Among them, the laser scanner can provide high-precision measurement data, which can capture the details and precise dimensions of the exhibits, ensuring the accuracy of the 3D model. The scanned 3D data can be used multiple times, not only for the construction of 3D models, but also for virtual reality, augmented reality, online exhibitions and other application scenarios. Through convolutional neural network node calculation, deep features in the 3D model can be extracted to make the model more refined and realistic. This technology can improve the expression and generalization capabilities of the model, making the constructed 3D model closer to the form of the real exhibits. The node parameter values ​​are used as parameters of the constructed 3D model, making the model more flexible and editable. By adjusting the parameter values, the shape and details of the model can be easily modified, which provides convenience for subsequent model optimization and application. Through the model parameter comparison module, the constructed 3D model parameters are confirmed and the parameter curve overlaps with the 3D parameters of the exhibits, as well as the subsequent blank parameter value confirmation and completeness judgment. It has the advantages of high precision, accurate problem location, evaluable completeness, model optimization, convenient information integration, and strong flexibility and scalability, providing effective technical support for the digital display of exhibits. Among them, through parameter position confirmation and parameter curve overlap comparison, it can ensure that the constructed 3D model is highly consistent with the real exhibits in shape and structure. This kind of precision guarantee is particularly important for exhibits such as historical relics and artworks that need to be accurately restored. The non-overlapping area of ​​the nodes obtained after the parameter curve overlap comparison, that is, the blank area, is a possible problem area in model construction. By confirming these blank parameter values, the deficiencies or errors in model construction can be accurately located. The completeness rate of the constructed 3D model can be judged according to the blank parameter value, providing a method for quantitatively evaluating the quality of the model. This evaluation method can help determine whether the model meets the exhibition requirements and provide a basis for subsequent model adjustments. When the completeness rate is not within the qualified range, the parameters of the constructed 3D model can be adjusted according to the blank parameters. This targeted optimization method can improve the quality of the model, ensure that the 3D model in the exhibition system can accurately and completely display the exhibits, import the 3D model data that has been adjusted and constructed within the qualified range into the exhibition system, and annotate the basic information of the exhibits corresponding to the 3D model in the system, realizing the effective integration of model and exhibit information and improving the exhibition experience.

[0050] In order to solve the problem in the prior art that when a user views exhibits on a mobile terminal, no corresponding exhibit recommendation is made according to the user's interest in the exhibit type, resulting in a poor user experience, please refer to Figure 1-Figure 2, this embodiment provides the following technical solutions: User login exhibition unit, including: User login module, used to: The user enters the exhibition system on the mobile terminal. When the user enters the exhibition system for the first time, the user fills in the basic information of the user according to the prompt of the exhibition system; Basic information includes the user’s name, age, gender, mobile phone number, and address; After the basic information is filled in, the user's face detection is performed, wherein the user's face image data is collected using the camera of the mobile terminal, and the face image data is pre-processed; After the image data preprocessing is completed, the face in the image data is feature-annotated, and the feature annotation is to mark the positions of the facial features in the image; After the image data feature annotation is completed, the image data is rotated, scaled, and cropped, and the image data is rotated, scaled, and cropped to obtain a data set of the image data; Use the MTCNN face detection algorithm model to train the face model of the data set, and optimize and adjust the face model parameters during the face model training; The DeepFace learning model is used to select the representation features of the face model, and the selected representation features are used to extract feature vectors; Finally, the feature vector is compared with the face model for similarity, and the face model is evaluated based on the similarity comparison results; After the face model is evaluated as qualified, the user's face recognition module is obtained. After the user logs into the system, the user is identified and logged in according to the face recognition model; If the face model evaluation fails, face detection will continue; After facial recognition is completed, the exhibition system lists different types of exhibits, and users can select exhibits according to their interests; Among them, the types of exhibits are listed according to the types of exhibits participating in the exhibition.

[0051] User-interest exhibit recommendation module, used for: After the user has checked the exhibits of interest, he / she will re-enter the exhibition system; When the user re-enters the exhibition system, he / she needs to enter his / her name and password for password verification and login. After the password verification is passed, he / she can enter the exhibition system. After entering, the exhibition system recommends exhibits based on the exhibits of interest selected by the user; In addition, the exhibition system records the browsing habits of users based on the browsing time of each exhibit.

[0052] Specifically, the user login module collects basic user information, provides personalized experience, and displays exhibits by category, which improves the user's exhibition experience and interactivity. When a user enters the exhibition system for the first time, the user is prompted to fill in basic information, which helps the system better understand the user's basic characteristics and preferences, thereby providing users with more personalized exhibit recommendations and services. Collecting basic user information provides valuable data resources for the exhibition system. These data can be used to analyze user interests, behavior patterns, etc., in order to optimize exhibit display, improve user experience and exhibition effect. The exhibition system lists different exhibits according to the type of exhibits, allowing users to select according to their interests. This classified display method improves the user's selection efficiency, enables users to find exhibits of interest more quickly, allows users to select exhibits according to their interests, and enhances the user's sense of participation and interactivity. Through the user interest exhibit recommendation module, personalized recommendations are provided, browsing habits are recorded, and password verification login is performed, which improves user participation and loyalty, optimizes exhibit display, and enhances system security. By recording user browsing habits, the system can better understand user interests and preferences, thereby providing users with more accurate and relevant exhibit recommendations. This helps increase user engagement and satisfaction. By providing personalized recommendations and recording users' browsing habits, the system can create a more personalized and considerate service experience for users. This helps to enhance users' trust and loyalty to the exhibition system and promote users' revisit and sharing. By analyzing users' browsing habits and exhibits of interest, exhibitors can understand which exhibits are more popular, thereby optimizing the display and layout of exhibits. Password verification login can ensure that only authorized users can access the exhibition system, enhancing the security and data protection capabilities of the system. Among them, by introducing face recognition technology, the system can verify the identity of users and ensure that only legitimate users can access the system. Compared with traditional password or verification code verification methods, this biometric technology is more difficult to forge or crack, thereby improving the security of the system. When users enter the system for the first time, they only need to fill in basic information and perform a face detection, and then they can quickly log in through face recognition. This method saves the trouble of remembering passwords or receiving verification codes, making the login process more convenient and efficient. Based on face recognition and basic information collection, the system can further analyze user preferences and behavior patterns, thereby providing users with more personalized exhibit recommendations. This personalized service can improve user satisfaction and engagement.

[0053] In order to solve the problem in the prior art that the user's preference for an exhibit is not confirmed based on the user's browsing time for each exhibit, resulting in the exhibit display system recommending exhibits that do not meet the user's preferences, please refer to Figure 1-Figure 2 , this embodiment provides the following technical solutions: Recommended exhibits include: User preference exhibit confirmation module is used to: Obtain the user's browsing habit data and confirm the browsing time of each exhibit based on the browsing habit; Confirm the user's preference for each exhibit based on browsing time; Among them, the degree of preference is divided into recommended preference, general preference and no interest; when the browsing time is 1-30 seconds, the degree of preference is no interest; when the browsing time is 31-60 seconds, the degree of preference is general preference; when the browsing time is more than 60 seconds, the degree of preference is recommended preference.

[0054] Favorite exhibits classification module, used for: Confirm the user's preference and determine the type of exhibits the user prefers based on the user's preference; After confirming the type of exhibits that the user likes, the exhibition system automatically recommends exhibits of the same type; And classify the exhibits according to the types of users' preferences.

[0055] Specifically, by recording users' browsing habits and recommending exhibits accordingly, the system can stimulate users' interest and increase the time they spend on the exhibition system. Users will interact with the system more frequently, thereby increasing user participation and activity. By analyzing users' browsing habits and preferences, exhibitors can understand which exhibits are more popular and which exhibits may need to be improved or adjusted, thereby increasing the attractiveness of exhibits and the effect of visits. By providing personalized recommendations and recording users' browsing habits, the system can create a more intimate and personalized service experience for users. This personalized service experience helps to enhance users' trust and loyalty to the exhibition system and promote users to visit and share again.

[0056] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0057] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. Exhibit display classification system based on 3D virtual visualization smart exhibition hall, It is characterized in that include: Exhibit information acquisition unit, used for: Confirm the basic information of the exhibits in the exhibition hall and uniquely code each exhibit and its basic information; Exhibits 3D construction unit for: According to the basic information of the exhibits, a 3D model is constructed for each exhibit. After the 3D model of the exhibit is constructed, the parameters of the constructed 3D model are compared with the standard parameters of the exhibit, and the 3D model is adjusted according to the comparison results; User login to the exhibitor unit is used to: The user enters the exhibition system through a mobile terminal. Before the user enters the exhibition system for the first time, he / she fills in the basic information of the user and selects the user's interests. The exhibition system automatically recommends the corresponding exhibit model according to the user's interests. Exhibit recommendation unit, used for: The exhibition system classifies the user's browsing habits and selected interests into favorite exhibits, and displays favorite exhibit models according to the classification categories of the favorite exhibits.

2. The exhibit display classification system based on the three-dimensional virtual visualization smart exhibition hall according to claim 1, Features: The exhibit information acquisition unit is further used for: Retrieve basic information of exhibits from the database; The basic information of the exhibits includes the name, size, material, author and author information of the exhibits; In addition, the basic information of each exhibit and the exhibit are stored in the database through a timestamp and a random number to generate a unique number.

3. The exhibit display classification system based on the three-dimensional virtual visualization smart exhibition hall according to claim 2, Features: The exhibit information acquisition unit is further used for: After obtaining the basic information of the exhibit from the database, determining whether the basic information is complete; wherein the complete basic information refers to basic information including the name, size, material, author and complete information of the author of the exhibit; When the basic information is complete, the complete basic information is used as the target basic information; Retrieve the basic information corresponding to the last time the same exhibit was retrieved as reference basic information; Compare the target basic information with the reference basic information to determine whether the target basic information is consistent with the reference basic information; When the target basic information and the reference basic information are consistent, a unique number is generated for the target basic information; When the target basic information and the reference basic information are inconsistent, the target basic information and the reference basic information are used to obtain a basic information difference evaluation parameter, wherein the basic information difference evaluation parameter is obtained by the following formula: ； Among them, Y represents the basic information difference evaluation parameter; n represents the information type contained in the basic information. Since the basic information of the exhibits includes the name, size, material, author and author information of the exhibits, n=5; λ i represents the weight value corresponding to the i-th basic information type; p i represents the ratio of inconsistent information characters contained in the data information corresponding to the i-th basic information type; p max Indicates the maximum ratio of inconsistent information characters in the type contained in the basic information; p h Indicates the ratio and value of inconsistent information characters in the type contained in the basic information; h Indicates the weight and value corresponding to the information type contained in the basic information; max Indicates the weight value corresponding to the maximum ratio of inconsistent information characters appearing in the types included in the basic information; When the basic information difference evaluation parameter is not lower than a preset parameter threshold, a unique number is generated for the target basic information; When the basic information difference evaluation parameter is lower than a preset parameter threshold, information security detection is performed on the basic information of the exhibit.

4. The exhibit display classification system based on the three-dimensional virtual visualization smart exhibition hall according to claim 3, Features: When the basic information difference evaluation parameter is lower than the preset parameter threshold, information security detection is performed on the basic information of the exhibit, including: Retrieve the basic information of the exhibits and the time point for retrieving all the information; Obtain basic information of the retrieved exhibits at each time point; The basic information of the exhibit retrieved at each time node is compared with the basic information of the exhibit entered for the first time to obtain information security evaluation parameters, wherein the information security evaluation parameters are obtained by the following formula: ； Where S represents the information security evaluation parameter corresponding to the basic information of the retrieved exhibits at each time node; Y x represents the difference evaluation parameter corresponding to the basic information of the exhibit retrieved at each time node; n represents the type of information contained in the basic information. Since the basic information of the exhibit includes the name, size, material, author and author information of the exhibit, n=5; λ i represents the weight value corresponding to the i-th basic information type; p xi It represents the ratio of inconsistent information characters contained in the i-th basic information type after comparing it with the corresponding basic information type in the basic information of the exhibit when the information is first entered; p ymax represents the maximum ratio of inconsistent information characters in the inconsistent information characters contained in the i-th basic information type after comparing it with the corresponding basic information type in the basic information of the exhibit when the information is first entered; p y Indicates the ratio and value of inconsistent information characters contained in the basic information of the retrieved exhibit at each time node after comparing it with the corresponding basic information type in the basic information entered for the first time; λ h Indicates the weight and value corresponding to the information type contained in the basic information; ymax The weight value corresponding to the maximum value of the ratio of inconsistent information characters in the inconsistent information characters contained in the i-th basic information type after comparing it with the corresponding basic information type in the basic information of the exhibit when the information is first entered; The security detection parameters of the basic information of the exhibits are obtained by using the information security evaluation parameters corresponding to the basic information of the exhibits retrieved at each time node; When the security detection parameter of the basic information is lower than the preset parameter threshold, an information security alarm is issued; When the security detection parameter of the basic information is not lower than a preset parameter threshold, the exhibit is marked.

5. The exhibit display classification system based on the three-dimensional virtual visualization smart exhibition hall according to claim 4, Features: The security detection parameters of the basic information of the exhibits are obtained by using the information security evaluation parameters corresponding to the basic information of the exhibits retrieved at each time node, including: Retrieving information security evaluation parameters corresponding to the basic information of the exhibit retrieved at each time point; The interception rate of access data for retrieving basic information of exhibits; The security detection parameters are obtained by using the information security evaluation parameters corresponding to the basic information of the exhibits retrieved at each time node and the interception rate of the access data of the basic information of the exhibits, wherein the security detection parameters are obtained by the following formula: ； Where W represents the safety detection parameter; P z represents the interception rate of access data of basic information of exhibits; m represents the number of times the basic information of exhibits is retrieved; S i represents the information security evaluation parameter corresponding to the i-th basic information retrieval; Y xi It represents the difference evaluation parameter corresponding to the basic information of the exhibits obtained when the basic information is retrieved for the i-th time.

6. The exhibit display classification system based on the three-dimensional virtual visualization smart exhibition hall according to claim 2, Features: The three-dimensional construction unit of the exhibit includes: 3D model building modules for: Confirm the exhibit parameters, wherein the exhibit parameters are scanned by a laser scanner, and the three-dimensional parameters of the exhibit are obtained after the scanning is completed; Import the exhibit's 3D parameters into the 3D model to build the 3D model; After the 3D model of the exhibit is built, 3D model training is carried out; The three-dimensional model training is to confirm the data of each model node of the three-dimensional model and perform node calculation on each model node through a convolutional neural network; After node calculation, the node parameter value of each node of the three-dimensional model is obtained; The node parameter values ​​are the parameters of the constructed 3D model.

7. The exhibit display classification system based on the three-dimensional virtual visualization smart exhibition hall according to claim 6, Features: The exhibit three-dimensional construction unit also includes: Model parameter comparison module, used for: Confirm the parameter positions of the constructed 3D model parameters and the 3D parameters of the exhibits; The parameter position is the position where the nodes in the constructed three-dimensional model and the scanned three-dimensional model of the exhibit coincide with each other; Perform parameter curve overlap comparison on the parameters of nodes with consistent parameter positions; After the parameter curves are overlapped and compared, the non-overlapping area of ​​the nodes is obtained; And confirm the blank parameter value of the non-overlapping area; The completeness rate of the constructed 3D model is determined according to the blank parameter value; When the completeness rate is not within the qualified range, the parameters of the constructed three-dimensional model are adjusted according to the blank parameters; The 3D model data that has been adjusted and constructed within the qualified range is imported into the exhibition system, and each 3D model in the exhibition system is annotated with basic information of the exhibits corresponding to the 3D model.

8. The exhibit display classification system based on the three-dimensional virtual visualization smart exhibition hall according to claim 7, Features: The user logs in to the exhibition unit, including: User login module, used for: The user enters the exhibition system on the mobile terminal. When the user enters the exhibition system for the first time, the user fills in the basic information of the user according to the prompt of the exhibition system; Basic information includes the user’s name, age, gender, mobile phone number, and address; After the basic information is filled in, the user's face detection is performed, wherein the user's face image data is collected using the camera of the mobile terminal, and the face image data is pre-processed; After the image data preprocessing is completed, the face in the image data is feature-annotated, and the feature annotation is to mark the positions of the facial features in the image; After the image data feature annotation is completed, the image data is rotated, scaled, and cropped, and the image data is rotated, scaled, and cropped to obtain a data set of the image data; Use the MTCNN face detection algorithm model to train the face model of the data set, and optimize and adjust the face model parameters during the face model training; The DeepFace learning model is used to select the representation features of the face model, and the selected representation features are used to extract feature vectors; Finally, the feature vector is compared with the face model for similarity, and the face model is evaluated based on the similarity comparison results; After the face model is evaluated as qualified, the user's face recognition module is obtained. After the user logs into the system, the user is identified and logged in according to the face recognition model; If the face model evaluation fails, face detection will continue; After facial recognition is completed, the exhibition system lists different types of exhibits, and users can select exhibits according to their interests; Among them, the types of exhibits are listed according to the types of exhibits participating in the exhibition.

9. The exhibit display classification system based on the three-dimensional virtual visualization smart exhibition hall according to claim 8, Features: The user login exhibition unit also includes: User interest exhibit recommendation module, used for: After the user has checked the exhibits of interest, he / she will re-enter the exhibition system; When the user re-enters the exhibition system, he / she needs to enter his / her name and password for password verification and login. After the password verification is passed, he / she can enter the exhibition system. After entering, the exhibition system recommends exhibits based on the exhibits of interest selected by the user; In addition, the exhibition system records the browsing habits of users based on the browsing time of each exhibit.

10. The exhibit display classification system based on the three-dimensional virtual visualization smart exhibition hall according to claim 9, Features: The exhibit recommendation unit includes: User preference exhibit confirmation module is used to: Obtain the user's browsing habit data and confirm the browsing time of each exhibit based on the browsing habit; Confirm the user's preference for each exhibit based on browsing time; Favorite exhibits classification module, used for: Confirm the user's preference and determine the type of exhibits the user prefers based on the user's preference; After confirming the type of exhibits that the user likes, the exhibition system automatically recommends exhibits of the same type; And classify the exhibits according to the types of users' preferences.

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