Exhibit display classification system based on 3D virtual visualization smart exhibition hall

Abstract

The present invention discloses an exhibit display classification system based on a three-dimensional virtual visualization smart exhibition hall, which relates to the technical field of smart exhibition halls and aims to solve the problem of insufficient construction effect when constructing a visualization model of an exhibit. The laser scanner of the present invention 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. By performing node calculations through a convolutional neural network, deep-level features in the three-dimensional model can be extracted, making the model more refined and realistic. By confirming the parameter position and overlapping and comparing the parameter curves, it can be ensured that the constructed three-dimensional model is highly consistent with the real exhibit in shape and structure. By confirming the values ​​of these blank parameters, 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.

Description

Technical Field

[0001] The present invention relates to the technical field of smart exhibition halls, and in particular to an exhibit display and 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] Chinese patent publication number CN111677986A discloses a smart exhibition hall display system based on 3D virtual visualization. The system primarily utilizes the coordination of a camera, 3D scanner, camera head, data storage module, character modeling module, computer, 3D virtual projection equipment, motor, and base. The system can decorate a character model with cheongsams of different styles, and then dynamically project the decorated character model in 3D using the 3D virtual projection equipment. The system also digitizes and decorates the character model based on existing cheongsam styles, achieving a customized effect. While the patent addresses the display issues, the following challenges remain in actual operation:

[0004] 1. The user's preference for exhibits is not confirmed based on the time the user browses each exhibit, resulting in the exhibit display system recommending exhibits that do not meet the user's preferences.

[0005] 2. Failure to recommend exhibits based on the user's interest in the exhibit type, resulting in a poor user experience.

[0006] 3. Failure to accurately compare the actual parameters of the exhibits with the 3D model, resulting in poor construction of the 3D model of the exhibits Summary of the Invention

[0007] The purpose of the present invention is to provide an exhibit display and 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 node calculation by convolutional neural network, deep-level features in the three-dimensional model can be extracted, making 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, deficiencies or errors in 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.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] The exhibit display and classification system based on the 3D virtual visualization smart exhibition hall includes:

[0010] Exhibit information acquisition unit, used for:

[0011] Confirm the basic information of the exhibits in the exhibition hall and uniquely code each exhibit and its basic information;

[0012] Exhibits 3D construction unit, used for:

[0013] Based on 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;

[0014] User login to the exhibition unit is used to:

[0015] The user enters the exhibition system through a mobile terminal. Before entering the exhibition system for the first time, the user fills in basic user information and selects user interests. The exhibition system automatically recommends corresponding exhibit models based on the user's interests.

[0016] Exhibit recommendation unit, used for:

[0017] 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.

[0018] Preferably, the exhibit information acquisition unit is further used to:

[0019] Retrieve basic information of exhibits from the database;

[0020] The basic information of the exhibits includes the name, size, material, author and author information;

[0021] 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.

[0022] Preferably, the exhibit information acquisition unit is further used to:

[0023] 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 exhibit's name, size, material, author, and complete author information;

[0024] When the basic information is complete, the complete basic information is used as the target basic information;

[0025] Retrieve the basic information corresponding to the last time the same exhibit was retrieved as reference information;

[0026] Comparing the target basic information with the reference basic information to determine whether the target basic information is consistent with the reference basic information;

[0027] When the target basic information and the reference basic information are consistent, a unique number is generated for the target basic information;

[0028] 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:

[0029]

[0030] Where 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 types contained in the basic information; p h Indicates the ratio and value of inconsistent information characters in the types contained in the basic information; h Indicates the weight and value corresponding to the information type contained in the basic information; max The weight value corresponding to the maximum ratio of inconsistent information characters appearing in the types contained in the basic information;

[0031] 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;

[0032] When the basic information difference evaluation parameter is lower than a preset parameter threshold, an information security detection is performed on the basic information of the exhibit.

[0033] Preferably, when the basic information difference evaluation parameter is lower than a preset parameter threshold, an information security check is performed on the basic information of the exhibit, including:

[0034] Retrieve the basic information of the exhibits and the time points for retrieving any discrepancies in the basic information;

[0035] Obtain basic information of the retrieved exhibits at each time point;

[0036] The basic information of the exhibit retrieved at each time point is compared with the basic information entered for the first time to obtain an information security evaluation parameter, wherein the information security evaluation parameter is obtained by the following formula:

[0037]

[0038] Where S represents the information security evaluation parameter corresponding to the basic information of the exhibits retrieved 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 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 entered for the first time; p ymax represents the maximum ratio of inconsistent information characters in the inconsistent information characters contained in the comparison between the i-th basic information type and 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 after comparing the basic information of the exhibit retrieved at each time node 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 ratio of inconsistent information characters 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;

[0039] 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 point;

[0040] When the security detection parameter of the basic information is lower than the preset parameter threshold, an information security alarm is issued;

[0041] When the security detection parameter of the basic information is not lower than a preset parameter threshold, the exhibit is marked.

[0042] 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 point, including:

[0043] Retrieving information security evaluation parameters corresponding to the basic information of the exhibit retrieved at each time point;

[0044] The interception rate of access data for retrieving basic information of exhibits;

[0045] 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. The security detection parameters are obtained by the following formula:

[0046]

[0047] 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 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 exhibit obtained during the i-th basic information retrieval.

[0048] Preferably, the three-dimensional exhibit construction unit includes:

[0049] 3D model building modules for:

[0050] 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;

[0051] Import the exhibit's 3D parameters into the 3D model to construct the 3D model;

[0052] After the 3D model of the exhibit is built, 3D model training is carried out;

[0053] The 3D model training involves confirming the data of each model node of the 3D model and performing node calculation on each model node through a convolutional neural network.

[0054] After node calculation, the node parameter value of each node of the three-dimensional model is obtained;

[0055] The node parameter values ​​are the parameters of the constructed three-dimensional model.

[0056] Preferably, the three-dimensional exhibit construction unit further includes:

[0057] Model parameter comparison module, used for:

[0058] Confirm the position of the constructed 3D model parameters with the 3D parameters of the exhibit;

[0059] The parameter position is the position where the nodes in the constructed 3D model and the scanned 3D model of the exhibit are consistent;

[0060] Perform parameter curve overlap comparison on the parameters of nodes with consistent parameter positions;

[0061] After the parameter curves are overlapped and compared, the non-overlapping area of ​​the nodes is obtained;

[0062] And confirm the blank parameter value of the non-overlapping area;

[0063] The completeness rate of the constructed 3D model is determined based on the blank parameter value;

[0064] When the completeness rate is not within the qualified range, the parameters of the constructed 3D model are adjusted according to the blank parameters;

[0065] 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 exhibit corresponding to the 3D model.

[0066] Preferably, the user logging into the exhibition unit includes:

[0067] User login module, used for:

[0068] The user enters the exhibition system on the mobile terminal. When the user enters the exhibition system for the first time, he / she fills in the user's basic information according to the prompts of the exhibition system;

[0069] Basic information includes the user's name, age, gender, mobile phone number, and address;

[0070] After the basic information is filled in, the user's face is detected, wherein the user's face image data is collected using the camera of the mobile terminal and the face image data is pre-processed;

[0071] After the image data preprocessing is completed, the face in the image data is marked with features, and the feature marking is to mark the positions of the facial features in the image;

[0072] After the image data feature annotation is completed, the image data is rotated, scaled, and cropped to obtain a data set of the image data;

[0073] Use the MTCNN face detection algorithm model to train the face model on the dataset, and optimize and adjust the face model parameters while training the face model;

[0074] The DeepFace learning model is used to select the representation features of the face model and extract the feature vector of the selected representation features;

[0075] Finally, the feature vector is compared with the face model for similarity, and the face model is evaluated based on the similarity comparison results;

[0076] 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;

[0077] If the face model evaluation fails, continue with face detection;

[0078] After facial recognition is completed, the exhibition system lists different types of exhibits, and users can select exhibits based on their interests;

[0079] Among them, the types of exhibits are listed according to the types of exhibits participating in the exhibition.

[0080] Preferably, the user login exhibition unit further includes:

[0081] User-interested exhibit recommendation module, used for:

[0082] After the user has selected the exhibits of interest, he / she re-enters the exhibition system;

[0083] Among them, when the user re-enters the exhibition system, he / she enters his / her name and password for password verification and logs in. After the password verification is passed, he / she enters the exhibition system;

[0084] After entering, the exhibition system recommends exhibits based on the exhibits of interest selected by the user;

[0085] In addition, the exhibition system records the browsing habits of users based on the browsing time of each exhibit.

[0086] Preferably, the exhibit recommendation unit includes:

[0087] User preference exhibit confirmation module is used to:

[0088] Obtain the user's browsing habit data and confirm the browsing time of each exhibit based on the browsing habit;

[0089] Confirm the user's preference for each exhibit based on browsing time;

[0090] Favorite exhibits classification module, used for:

[0091] Determine the user's preference and determine the type of exhibits the user prefers based on the user's preference;

[0092] After confirming the type of exhibits the user prefers, the exhibition system automatically recommends exhibits of the same type;

[0093] And classify the exhibits according to the user's preferences.

[0094] Compared with the prior art, the present invention has the following beneficial effects:

[0095] 1. The exhibit display and classification system based on a 3D virtual visualization smart exhibition hall provided by the present invention uses a laser scanner to provide high-precision measurement data, which can capture the details and precise dimensions of the exhibits, ensuring the accuracy of the 3D model. Node calculations using a convolutional neural network can extract deep-level features from the 3D model, making the model more refined and realistic. Parameter position confirmation and parameter curve overlap comparison can ensure that the constructed 3D model is highly consistent with the actual exhibit in shape and structure.

[0096] 2. The exhibit display and classification system based on the 3D virtual visualization smart exhibition hall provided by this invention lists different exhibits according to their types, allowing users to select exhibits based on their interests, enabling users to find exhibits of interest more quickly, enhancing user participation and interactivity. By recording users' browsing habits, the system can better understand their interests and preferences, thereby providing users with more accurate and relevant exhibit recommendations. This helps to increase user participation and satisfaction.

[0097] 3. The exhibit display and classification system based on a 3D virtual visualization smart exhibition hall provided by this invention records users' browsing habits and recommends exhibits accordingly. This system can stimulate users' interest and increase their time spent on the exhibition system. By analyzing users' browsing habits and preferences, exhibitors can understand which exhibits are most popular and which exhibits may need improvement or adjustment, thereby improving the attractiveness of exhibits and the effectiveness of visitors. By incorporating facial recognition technology, the system can verify user identities, ensuring that only legitimate users can access the system. This biometric identification technology is much more difficult to forge or crack than traditional password or verification code authentication methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0098] Figure 1 This is a schematic diagram of the smart exhibition hall exhibit display module of the present invention;

[0099] Figure 2 Schematic diagram of the process of displaying exhibits in a smart exhibition hall according to the present invention. DETAILED DESCRIPTION

[0100] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0101] 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 during the 3D construction of the exhibits, which leads to poor 3D model construction effect of the exhibits, please refer to Figure 1-Figure 2 , this embodiment provides the following technical solutions:

[0102] The exhibit display and classification system based on the 3D virtual visualization smart exhibition hall includes:

[0103] Exhibit information acquisition unit, used for:

[0104] Confirm the basic information of the exhibits in the exhibition hall and uniquely code each exhibit and its basic information;

[0105] Exhibits 3D construction unit, used for:

[0106] Based on 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;

[0107] User login to the exhibition unit is used to:

[0108] The user enters the exhibition system through a mobile terminal. Before entering the exhibition system for the first time, the user fills in basic user information and selects user interests. The exhibition system automatically recommends corresponding exhibit models based on the user's interests.

[0109] Exhibit recommendation unit, used for:

[0110] 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.

[0111] Specifically, the exhibit information acquisition unit ensures that each exhibit has a unique identifier. The exhibit 3D construction unit confirms parameter positions and overlaps parameter curves to ensure that the constructed 3D model is highly consistent with the actual exhibit in shape and structure. This precision assurance is particularly important for exhibits such as historical relics and artworks that require precise restoration. The exhibitor unit provides personalized recommendations, records browsing habits, and requires password verification for login, increasing user engagement and loyalty while optimizing exhibit display. The exhibitor recommendation unit analyzes user browsing habits and preferences, creating a more intimate and personalized service experience for users.

[0112] The exhibit information acquisition unit is also used to:

[0113] Retrieve basic information of exhibits from the database;

[0114] The basic information of the exhibits includes the name, size, material, author and author information;

[0115] 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.

[0116] 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 guessing or forgery, and improve the security of exhibit information.

[0117] Specifically, the exhibit information acquisition unit is further used to:

[0118] 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 exhibit's name, size, material, author, and complete author information;

[0119] When the basic information is complete, the complete basic information is used as the target basic information;

[0120] Retrieve the basic information corresponding to the last time the same exhibit was retrieved as reference information;

[0121] Comparing the target basic information with the reference basic information to determine whether the target basic information is consistent with the reference basic information;

[0122] When the target basic information and the reference basic information are consistent, a unique number is generated for the target basic information;

[0123] 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:

[0124]

[0125] Where 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 irepresents 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 types contained in the basic information; p h Indicates the ratio and value of inconsistent information characters in the types contained in the basic information; h Indicates the weight and value corresponding to the information type contained in the basic information; max The weight value corresponding to the maximum ratio of inconsistent information characters appearing in the types contained in the basic information;

[0126] 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;

[0127] When the basic information difference evaluation parameter is lower than a preset parameter threshold, an information security detection is performed on the basic information of the exhibit.

[0128] 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 determining 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.

[0129] 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 an update is needed. This comparison mechanism helps to promptly detect and correct information changes, ensuring the accuracy and timeliness of exhibit information.

[0130] When the target basic information is consistent with the reference basic information or the difference evaluation parameters are 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 facilitates subsequent tracking, query and management.

[0131] The scheme introduces a difference evaluation parameter (Y) as a quantitative indicator to judge the degree of information difference. By calculating the ratio of inconsistent characters in each type of basic information and the corresponding weight, the degree of information change can be more accurately assessed, providing a basis for decision-making on whether to generate a unique number.

[0132] When the difference evaluation parameter falls below the preset threshold, the system triggers an information security check. This indicates that there may be significant changes to the basic information of the exhibit or potential security risks, requiring further inspection and confirmation to ensure the security and reliability of the exhibit information.

[0133] In summary, this technical solution achieves 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.

[0134] 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:

[0135] Retrieve the basic information of the exhibits and the time points for retrieving any discrepancies in the basic information;

[0136] Obtain basic information of the retrieved exhibits at each time point;

[0137] The basic information of the exhibit retrieved at each time point is compared with the basic information entered for the first time to obtain an information security evaluation parameter, wherein the information security evaluation parameter is obtained by the following formula:

[0138]

[0139] Where S represents the information security evaluation parameter corresponding to the basic information of the exhibits retrieved 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 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 entered for the first time; p ymax represents the maximum ratio of inconsistent information characters in the inconsistent information characters contained in the comparison between the i-th basic information type and 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 after comparing the basic information of the exhibit retrieved at each time node 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 ratio of inconsistent information characters 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;

[0140] 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 point;

[0141] When the security detection parameter of the basic information is lower than the preset parameter threshold, an information security alarm is issued;

[0142] When the security detection parameter of the basic information is not lower than a preset parameter threshold, the exhibit is marked.

[0143] The technical effect of the above technical solution is that it retrieves all the time points of the basic information of the exhibits and compares the information at each time point with the basic information when the exhibits were first entered, thereby achieving comprehensive and historical security testing of the exhibit information. This helps to detect any potential information tampering or errors, and ensures the integrity and accuracy of the exhibit information.

[0144] By introducing an information security evaluation parameter (S) and a variance evaluation parameter (Yx), combined with the weights of each basic information type (λi) and the ratio of inconsistent information characters (pxi), this technical solution can accurately assess the security status of exhibit information at various time points. This quantitative assessment method helps managers more accurately determine the security level of information and take appropriate measures.

[0145] When the security detection parameters of an exhibit's basic information fall below a preset threshold, the system triggers an information security alarm. This timely alarm mechanism helps managers quickly identify potential information security issues and take appropriate countermeasures, thereby avoiding risks such as information leakage and tampering.

[0146] If the safety detection parameters of basic information are above the preset threshold, the system will mark the exhibit. This flexible management method helps managers categorize exhibits, taking standard management measures for exhibits with good safety conditions and more stringent management measures for exhibits with potential risks.

[0147] By automating information security testing and assessment, this technical solution significantly improves the efficiency of exhibit information management. Instead of manually checking the information of each exhibit, managers can rely on the system to complete these tasks automatically, saving significant manpower and time costs.

[0148] In summary, this technical solution achieves comprehensive monitoring and management of exhibit information through comprehensive information security testing, accurate information security assessment, timely information security alarm and flexible exhibit management, effectively improving the security and management efficiency of exhibit information.

[0149] 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 point, including:

[0150] Retrieving information security evaluation parameters corresponding to the basic information of the exhibit retrieved at each time point;

[0151] The interception rate of access data for retrieving basic information of exhibits;

[0152] 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. The security detection parameters are obtained by the following formula:

[0153]

[0154] 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 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 exhibit obtained during the i-th basic information retrieval.

[0155] The technical effect of the above technical solution is that by combining the information security evaluation parameter (Si) corresponding to the basic information of the exhibit retrieved at each time point and the interception rate (Pz) of the access data of the basic information of the exhibit, the technical solution can provide a comprehensive security detection parameter (W). This comprehensive evaluation method considers 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 exhibit.

[0156] The security detection parameter (W) is calculated based on real-time access to basic exhibit information and the interception rate of access data. Therefore, it can reflect the security status of exhibit information in real time. This real-time nature helps managers promptly identify and address potential security issues.

[0157] 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 thus take targeted measures to improve them.

[0158] By monitoring the interception rate (Pz) of access data for basic exhibit information, this technical solution effectively prevents unauthorized access and potential information leaks. An increase in the interception rate enhances the system's ability to respond to potential security threats, further ensuring the security of exhibit information.

[0159] Based on 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 adopted to improve management efficiency.

[0160] 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.

[0161] Exhibits three-dimensional construction unit, including:

[0162] 3D model building modules for:

[0163] 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;

[0164] Import the exhibit's 3D parameters into the 3D model to construct the 3D model;

[0165] After the 3D model of the exhibit is built, 3D model training is carried out;

[0166] The 3D model training involves confirming the data of each model node of the 3D model and performing node calculation on each model node through a convolutional neural network.

[0167] After node calculation, the node parameter value of each node of the three-dimensional model is obtained;

[0168] The node parameter values ​​are the parameters of the constructed three-dimensional model.

[0169] Model parameter comparison module, used for:

[0170] Confirm the position of the constructed 3D model parameters with the 3D parameters of the exhibit;

[0171] The parameter position is the position where the nodes in the constructed 3D model and the scanned 3D model of the exhibit are consistent;

[0172] Perform parameter curve overlap comparison on the parameters of nodes with consistent parameter positions;

[0173] After the parameter curves are overlapped and compared, the non-overlapping area of ​​the nodes is obtained;

[0174] And confirm the blank parameter value of the non-overlapping area;

[0175] The completeness rate of the constructed 3D model is determined based on the blank parameter value;

[0176] When the completeness rate is not within the qualified range, the parameters of the constructed 3D model are adjusted according to the blank parameters;

[0177] 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 exhibit corresponding to the 3D model.

[0178] Specifically, the 3D model construction module uses a laser scanner to confirm the exhibit parameters and construct a 3D model, which is then trained. This technology offers the advantages of high precision, non-contact, automation, data reusability, and parametric modeling, providing strong support for the digital preservation, display, and research of exhibits. The laser scanner provides highly accurate measurement data, capturing the details and precise dimensions of the exhibits, ensuring the accuracy of the 3D model. The scanned 3D data can be reused multiple times, not only for 3D model construction, but also for various application scenarios such as virtual reality, augmented reality, and online exhibitions. Node calculations using convolutional neural networks extract deep features from the 3D model, making it more refined and realistic. This technology improves the model's expressiveness and generalization capabilities, making the constructed 3D model closer to the actual exhibit's form. Node parameter values ​​serve as parameters for the constructed 3D model, making the model more flexible and editable. By adjusting parameter values, the model's shape and details can be easily modified, facilitating subsequent model optimization and application. The model parameter comparison module verifies the position of the constructed 3D model parameters against the exhibit's 3D parameters and compares parameter curve overlap. This, along with subsequent confirmation of blank parameter values ​​and completeness assessment, offers advantages such as high precision, accurate problem location, assessable completeness, model optimization, convenient information integration, and strong flexibility and scalability, providing effective technical support for the digital display of exhibits. Parameter position confirmation and parameter curve overlap comparison ensure that the constructed 3D model is highly consistent with the actual exhibit in shape and structure. This precision assurance is particularly important for exhibits such as historical relics and artworks that require precise restoration. The non-overlapping areas of nodes obtained after parameter curve overlap comparison, known as blank areas, are potential problem areas in model construction. By confirming these blank parameter values, deficiencies or errors in model construction can be accurately located. Determining the completeness of the constructed 3D model based on the blank parameter values ​​provides a method for quantitatively assessing model quality. This evaluation method can help determine whether the model meets exhibition requirements and provides a basis for subsequent model adjustments. If the completeness rate is not within the qualified range, the parameters of the constructed 3D model can be adjusted based on the blanking parameters. This targeted optimization method can improve model quality, ensuring that the 3D model in the exhibition system can accurately and completely display the exhibits. The 3D model data that has been adjusted and is within the qualified range is imported into the exhibition system, and the basic information of the exhibits corresponding to the 3D model is annotated in the system, achieving effective integration of model and exhibit information and improving the exhibition experience.

[0179] In order to solve the problem in the prior art that when users browse exhibits on mobile terminals, no corresponding exhibit recommendations are made based on 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:

[0180] User login exhibition unit, including:

[0181] User login module, used for:

[0182] The user enters the exhibition system on the mobile terminal. When the user enters the exhibition system for the first time, he / she fills in the user's basic information according to the prompts of the exhibition system;

[0183] Basic information includes the user's name, age, gender, mobile phone number, and address;

[0184] After the basic information is filled in, the user's face is detected, wherein the user's face image data is collected using the camera of the mobile terminal and the face image data is pre-processed;

[0185] After the image data preprocessing is completed, the face in the image data is marked with features, and the feature marking is to mark the positions of the facial features in the image;

[0186] After the image data feature annotation is completed, the image data is rotated, scaled, and cropped to obtain a data set of the image data;

[0187] Use the MTCNN face detection algorithm model to train the face model on the dataset, and optimize and adjust the face model parameters while training the face model;

[0188] The DeepFace learning model is used to select the representation features of the face model and extract the feature vector of the selected representation features;

[0189] Finally, the feature vector is compared with the face model for similarity, and the face model is evaluated based on the similarity comparison results;

[0190] 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;

[0191] If the face model evaluation fails, continue with face detection;

[0192] After facial recognition is completed, the exhibition system lists different types of exhibits, and users can select exhibits based on their interests;

[0193] Among them, the types of exhibits are listed according to the types of exhibits participating in the exhibition.

[0194] User-interested exhibit recommendation module, used for:

[0195] After the user has selected the exhibits of interest, he / she re-enters the exhibition system;

[0196] Among them, when the user re-enters the exhibition system, he / she enters his / her name and password for password verification and logs in. After the password verification is passed, he / she enters the exhibition system;

[0197] After entering, the exhibition system recommends exhibits based on the exhibits of interest selected by the user;

[0198] In addition, the exhibition system records the browsing habits of users based on the browsing time of each exhibit.

[0199] Specifically, the user login module collects basic user information, provides a personalized experience, and displays exhibits by category, thereby enhancing the user's exhibition experience and interactivity. When a user first enters the exhibition system, they are prompted to fill in basic information. This helps the system better understand the user's basic characteristics and preferences, thereby providing more personalized exhibit recommendations and services. Collecting basic user information provides the exhibition system with valuable data resources. This data can be used to analyze user interests and behavioral patterns to optimize exhibit display, enhance user experience, and improve exhibition effectiveness. The exhibition system lists different exhibits based on the type of exhibits being exhibited, allowing users to select exhibits based on their interests. This categorized display method improves user selection efficiency, allowing users to find exhibits of interest more quickly and allowing users to select exhibits based on their interests, thereby enhancing user engagement and interactivity. The user interest exhibit recommendation module provides personalized recommendations, records browsing habits, and password-based login, which improves user engagement 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 tracking user browsing habits, the system creates a more personalized and attentive service experience for users. This helps strengthen user trust and loyalty to the exhibition system, encouraging repeat visits and sharing. By analyzing users' browsing habits and exhibits of interest, exhibitors can understand which exhibits are most popular and optimize the display and layout of their exhibits. Password-based login ensures that only authorized users can access the exhibition system, enhancing system security and data protection. The system incorporates facial recognition technology to verify user identity, ensuring only legitimate users can access the system. This biometric technology is more difficult to forge or crack than traditional password or verification code authentication methods, thereby enhancing system security. When users first enter the system, they only need to enter basic information and undergo a facial recognition scan. Afterwards, they can quickly log in through facial recognition. This method eliminates the need to remember passwords or receive verification codes, making the login process more convenient and efficient. Based on facial recognition and basic information collection, the system can further analyze user preferences and behavior patterns to provide users with more personalized exhibit recommendations. This personalized service can improve user satisfaction and engagement.

[0200] In order to solve the problem in the prior art that the user's preference for an exhibit is not determined 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:

[0201] Recommended exhibit units include:

[0202] User preference exhibit confirmation module is used to:

[0203] Obtain the user's browsing habit data and confirm the browsing time of each exhibit based on the browsing habit;

[0204] Confirm the user's preference for each exhibit based on browsing time;

[0205] 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.

[0206] Favorite exhibits classification module, used for:

[0207] Determine the user's preference and determine the type of exhibits the user prefers based on the user's preference;

[0208] After confirming the type of exhibits the user prefers, the exhibition system automatically recommends exhibits of the same type;

[0209] And classify the exhibits according to the user's preferences.

[0210] Specifically, by recording users' browsing habits and recommending exhibits accordingly, the system can stimulate user interest and increase the time they spend on the exhibition system. This leads to more frequent user interaction with the system, thereby increasing user engagement and activity. By analyzing users' browsing habits and preferences, exhibitors can understand which exhibits are most popular and which may need improvement or adjustment, thereby increasing the attractiveness of exhibits and the effectiveness of visitors. By providing personalized recommendations and recording users' browsing habits, the system can create a more attentive and personalized service experience for users. This personalized service experience helps to strengthen user trust and loyalty to the exhibition system, encouraging repeat visits and sharing.

[0211] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0212] While 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 these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. The exhibit display classification system based on 3D virtual visualization smart exhibition hall is characterized by: 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, used for: Based on 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 exhibition unit is used to: The user enters the exhibition system through a mobile terminal. Before entering the exhibition system for the first time, the user fills in basic user information and selects user interests. The exhibition system automatically recommends corresponding exhibit models based on the user's interests. Exhibit recommendation unit, used for: The exhibition system categorizes the user's browsing habits and selected interests into favorite exhibits, and displays favorite exhibit models according to the categorized categories of the favorite exhibits; 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; 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; 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 exhibit's name, size, material, author, and complete author information; 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 information; Comparing 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 basic information difference evaluation parameters; The basic information difference evaluation parameter is obtained by the following formula: ； Where Y represents the basic information difference evaluation parameter; n represents the type of information 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 types contained in the basic information; p h Indicates the ratio and value of inconsistent information characters in the types contained in the basic information; h Indicates the weight and value corresponding to the information type contained in the basic information; max The weight value corresponding to the maximum ratio of inconsistent information characters appearing in the types contained in the basic information; 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 at which all information is retrieved; Obtain basic information of the retrieved exhibits at each time point; The basic information of the exhibit retrieved at each time point is compared with the basic information entered for the first time to obtain an information security evaluation parameter, wherein the information security evaluation parameter is obtained by the following formula: ； Where S represents the information security evaluation parameter corresponding to the basic information of the exhibits retrieved 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 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 entered for the first time; p ymax represents the maximum ratio of inconsistent information characters in the inconsistent information characters contained in the comparison between the i-th basic information type and 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 after comparing the basic information of the exhibit retrieved at each time node 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 represents the weight value corresponding to the maximum ratio of inconsistent information characters 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; Y represents the basic information difference evaluation parameter; 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 point; 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.

2. The exhibit display and classification system based on a three-dimensional virtual visualization smart exhibition hall according to claim 1 is characterized by: 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 point, 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. 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 basic information of exhibits is retrieved; S i Y represents the information security evaluation parameter obtained at the corresponding time node when the basic information is retrieved for the i-th time; xi It represents the difference evaluation parameter corresponding to the basic information of the exhibit obtained during the i-th basic information retrieval.

3. The exhibit display and classification system based on a three-dimensional virtual visualization smart exhibition hall according to claim 2 is characterized by: 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 construct the 3D model; After the 3D model of the exhibit is built, 3D model training is carried out; The 3D model training involves confirming the data of each model node of the 3D model and performing 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 three-dimensional model.

4. The exhibit display and classification system based on a three-dimensional virtual visualization smart exhibition hall according to claim 3 is characterized by: The three-dimensional exhibit construction unit further includes: Model parameter comparison module, used for: Confirm the position of the constructed 3D model parameters with the 3D parameters of the exhibit; The parameter position is the position where the nodes in the constructed 3D model and the scanned 3D model of the exhibit are consistent; 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 based on the blank parameter value; When the completeness rate is not within the qualified range, the parameters of the constructed 3D 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 exhibit corresponding to the 3D model.

5. The exhibit display and classification system based on a three-dimensional virtual visualization smart exhibition hall according to claim 4 is characterized by: 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, he / she fills in the user's basic information according to the prompts 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 is detected, 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 marked with features, and the feature marking 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 to obtain a data set of the image data; Use the MTCNN face detection algorithm model to train the face model on the dataset, and optimize and adjust the face model parameters while training the face model; The DeepFace learning model is used to select the representation features of the face model and extract the feature vector of the selected representation features; 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, continue with face detection; After facial recognition is completed, the exhibition system lists different types of exhibits, and users can select exhibits based on their interests; Among them, the types of exhibits are listed according to the types of exhibits participating in the exhibition.

6. The exhibit display and classification system based on a three-dimensional virtual visualization smart exhibition hall according to claim 5 is characterized by: The user login exhibition unit also includes: User interest exhibit recommendation module, used for: After the user has selected the exhibits of interest, he / she re-enters the exhibition system; Among them, when the user re-enters the exhibition system, he / she enters his / her name and password for password verification and logs in. After the password verification is passed, he / she enters 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.

7. The exhibit display and classification system based on a three-dimensional virtual visualization smart exhibition hall according to claim 6 is characterized by: 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: Determine 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 the user prefers, the exhibition system automatically recommends exhibits of the same type; And classify the exhibits according to the user's preferences.

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