A video content playback control method and system for multimedia display cabinets

Abstract

The invention discloses a video content playback control method and system for multimedia showcases, and relates to the technical field of multimedia showcase control. The method and system search a museum collection database, extract original data of a specified field by using a standardized API interface, and after feature extraction, process the constructed equipment collection data set by using a Z-score standardization method to generate a classification data group, a chronological data group, a usage data group, and a historical playback quantity data group of standardized collections. Subsequently, by combining feature extraction with a machine learning algorithm, a collection playback plan sequence XH is generated for the collection heat index Xrd of each collection obtained, and corresponding collection multimedia video content is played according to the plan. Finally, a high-definition camera is used to monitor the crowd density of a showcase area in real time, and after comparison, it is determined whether an adjustment instruction needs to be issued to adjust the playback sequence and guide the audience diversion.

Description

Technical Field

[0001] The present invention relates to the technical field of multimedia showcase control, and in particular to a method and system for controlling video content playback in multimedia showcases. Background Art

[0002] The multimedia display cabinet is an innovative product that combines modern technology with traditional display cabinets. It aims to enhance the interactivity and viewing experience of cultural relics display while meeting the safety needs of cultural relics storage. This display cabinet combines high-definition OLED display technology, capacitive touch technology, and advanced interactive experience design. It not only supports users to click, view, zoom, and rotate information related to cultural relics, but also allows users to deeply explore the stories behind the cultural relics through video playback, making the cultural relics display more vivid and attractive.

[0003] However, in the process of use, existing multimedia showcases often expose two prominent problems: First, the phenomenon of audiences gathering in hot areas. Since the display content of the showcases has not been dynamically regulated, the fixed hot content often attracts a large number of audiences to gather in the same area, resulting in excessive crowd density, which not only affects the audience's viewing experience, but also may cause safety hazards; second, the decline in user retention rate caused by content homogeneity. Over time, the content displayed in the showcases lacks dynamic updates and personalized recommendations, and the audience gradually loses interest after repeated viewing. These problems highlight the need for a more intelligent content playback control method, which can achieve on-demand content playback and regional crowd diversion by dynamically adjusting the playback order, real-time monitoring of crowd status, and intelligent algorithms that combine the popularity of collections with audience preferences, thereby optimizing the use efficiency of multimedia showcases and improving user experience. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a method and system for controlling video content playback in a multimedia showcase, which solves the problems in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a video content playback control method for a multimedia showcase, comprising the following steps; S1. By searching the collection database in the museum, the original data of the specified field is obtained, and the obtained original data is screened and filtered. After feature extraction, the equipment collection data set X is constructed; S2, based on the constructed equipment collection data set X, and combined with the Z-score standardization processing method, obtain the standardized collection classification data group M1, the standardized collection age data group M2, the standardized collection usage data group M3 and the standardized collection historical playback quantity group M4; S3, based on the constructed standardized collection classification data group M1, the standardized collection age data group M2, the standardized collection usage data group M3 and the standardized collection historical playback quantity group M4, after feature extraction and combined with machine learning calculation, obtain several collection heat indexes Xrd; S4, based on obtaining a number of collection heat indexes Xrd, and according to the collection heat mapping relationship between the heat coefficient Xrd of each collection and the collection heat of the corresponding collection code, obtaining a collection play plan sequence XH, and playing the corresponding collection multimedia video according to the collection play plan sequence XH; S5. Based on the playback process of the current multimedia showcase according to the collection playback plan sequence XH, the crowd flow status of the multimedia showcase area is monitored in real time to determine the crowd congestion level of the current multimedia showcase area, and corresponding adjustment level instructions are issued and executed.

[0006] Preferably, the specific steps of S1 include: S11. Based on the collection database that the museum has as stipulated in the Collection Regulations, the API interface of the collection database is adapted to a unified interface format through a standardized API interface adaptation layer, wherein the API interface adaptation layer is used to parse and process the protocol differences of different APIs, and perform data format conversion and field mapping; S12. Based on the API interface adaptation layer, a search request is made to the collection database to obtain the original data of the specified field, and the obtained original data is screened and filtered. After feature extraction, the equipment collection data set X is constructed. The specific steps are as follows: S13, screening and filtering the acquired raw data includes: removing records with incomplete fields in the raw data; identifying logically contradictory records, and performing data consistency verification in combination with a data verification algorithm; deleting collection records that are not within the current multimedia showcase video playback range, and performing dynamic comparison based on the display list in the playback settings; S14. According to the historical exhibition records and audience behavior feedback in the equipment collection data set X, and in combination with feature extraction technology, key fields are extracted from the screened and filtered original data to construct the equipment collection data set X. The equipment collection data set X includes a collection classification data group X1, a collection age data group X2, a collection usage data group X3, and a collection historical playback quantity data group X4.

[0007] Preferably, the specific steps of S2 include: S21, based on the constructed equipment collection data set X, and in combination with the Z-score standardization processing method, data standardization processing is performed on the collection classification data group X1, the collection age data group X2, the collection usage data group X3, and the collection historical playback quantity data group X4 in the equipment collection data set X. The specific steps are as follows: S211, the collection classification data group X1 includes the classification information heat coefficient x1 of each collection, and after processing with a statistical mean value algorithm, the mean value of the classification information heat coefficient in the collection classification data group X1 is obtained. , compare the classification information heat coefficient x1 of each collection in the collection classification data set X1 with the mean of the classification information heat coefficient Compare and analyze the classification information heat coefficient x1 and the mean classification information heat coefficient of each collection The degree of deviation is calculated by fitting the standardized classification information heat coefficient m1 of each collection to construct the standardized collection classification data set M1.

[0008] Preferably, the specific step S21 further includes: S212: The collection age data group X2 includes the historical age heat coefficient x2 of each collection, and after processing with a statistical mean value algorithm, the mean value of the historical age heat coefficient in the collection age data group X2 is obtained. , compare the historical age heat coefficient x2 of each collection in the collection age data group X2 with the mean of the historical age heat coefficient Compare and analyze the historical age heat coefficient x2 and the mean historical age heat coefficient of each collection The degree of deviation is calculated by fitting the standardized historical age heat coefficient m2 of each collection to construct the standardized collection age data group M2.

[0009] Preferably, the specific step S21 further includes: S213: The collection use data group X3 includes the functional use heat coefficient x3 of each collection, and after processing with a statistical mean value algorithm, the mean value of the functional use heat coefficient in the collection use data group X3 is obtained. , compare the functional use heat coefficient x3 of each collection in the collection use data set X3 with the mean functional use heat coefficient Compare and analyze the functional use heat coefficient x3 and the mean functional use heat coefficient of each collection The degree of deviation is calculated by fitting the standardized functional use heat coefficient m3 of each collection to construct the standardized collection use data set M3.

[0010] Preferably, the specific step S21 further includes: S214: The collection history play quantity data set X4 includes the video play quantity x4 of each collection, and after processing with a statistical mean value algorithm, the mean value of the video play quantity in the collection history play quantity data set X4 is obtained. , the video play count x4 of each collection in the collection history play count data set X4 and the mean video play count Compare and analyze the number of video plays x4 and the average number of video plays for each collection The degree of deviation is obtained by fitting the standardized video playback quantity m4 of each collection to construct the standardized collection historical playback quantity group M4.

[0011] Preferably, the specific steps of S3 include: S31, based on the constructed standardized collection classification data group M1, the standardized collection age data group M2, the standardized collection usage data group M3 and the standardized collection historical playback quantity group M4, after feature extraction and combined with machine learning calculation, obtain several collection heat indexes Xrd, one of which is: the collection heat index Xrd of the i-th collection i , which is obtained by the following formula:

[0012] In the formula, It is expressed as the standardized classification information heat coefficient of the i-th collection, Expressed as the standardized historical age heat coefficient of the i-th collection, It is expressed as the standardized functional use heat coefficient of the i-th collection, It is represented as the normalized number of video plays of the i-th collection, , , and are all expressed as weight values.

[0013] Preferably, the specific steps of S4 include: S41. According to the coding information marked by each collection, feature extraction is performed on the coding information of the collection in the equipment collection data set X to obtain the collection code Ccp of each collection. Based on obtaining a number of collection heat indexes Xrd, and according to the collection heat mapping relationship between the heat coefficient Xrd of each collection and the corresponding collection code Ccp, a collection heat coefficient mapping sequence XL is constructed in the form of ; S42, sorting the heat indexes Xrd of several collections in reverse order from high to low, while retaining the corresponding collection codes Ccp, and obtaining the collection heat sorting sequence XP arranged by heat priority after sorting, in the form of ; S43, according to the sorting results, extract the corresponding collection codes Ccp in turn, and obtain the collection playback plan sequence XH in the form of , the collection playback plan sequence XH is sent to the video playback platform of the multimedia showcase, and the corresponding collection multimedia video is played according to the collection playback plan sequence.

[0014] Preferably, the specific steps of S5 include: S51, based on the playback process of the current multimedia showcase according to the collection playback plan sequence, the crowd flow state in the multimedia showcase area is monitored in real time by a high-definition camera to obtain the crowd flow density Dmd; S52, presetting a crowd density threshold P, and comparing the obtained crowd density Dmd with the preset crowd density threshold P to determine the crowd congestion level of the current multimedia showcase area, and issuing and executing a corresponding adjustment level instruction. The specific process is as follows: If the crowd density Dmd≥the crowd density threshold P, it means that the multimedia showcase is currently playing according to the playing plan, and the crowd flow in the multimedia showcase area is in a crowded state, and at this time, a first-level adjustment instruction is sent out; If the crowd density Dmd is less than the crowd density threshold P, it means that the multimedia showcase is currently playing according to the play plan, and the crowd flow in the multimedia showcase area is not in a crowded state, and at this time, a secondary adjustment instruction is sent out; S521. According to the received primary adjustment instruction and secondary adjustment instruction, the following contents are specifically executed: When receiving the first-level adjustment instruction, the execution content is to display "The current number of viewers is crowded. For a better viewing experience, please move to other ordinary showcases to watch" in the form of text on the multimedia showcase panel; at the same time, the current playback order according to the collection playback plan sequence is changed to reverse playback to reduce the popularity of the collection multimedia video currently being played, until the flow of people in the multimedia showcase area is not in a crowded state, then adjust to play the collection multimedia video according to the playback plan; When receiving the secondary adjustment instruction, the execution content is to continue to monitor the flow of people in the current multimedia display cabinet area, and play the collection multimedia video according to the playback plan.

[0015] A video content playback control system for multimedia display cabinets, including a data extraction module, a standardization module, a collection heat analysis module, a planned playback module and a crowd flow adjustment module; The data extraction module is used to search the collection database in the museum to obtain the original data of the specified field, screen and filter the obtained original data, and construct the equipment collection data set X after feature extraction; The standardization module is based on the constructed equipment collection data set X and combined with the Z-score standardization processing method to obtain the standardized collection classification data group M1, the standardized collection age data group M2, the standardized collection usage data group M3 and the standardized collection historical playback quantity group M4; The collection heat analysis module is based on the constructed standardized collection classification data group M1, the standardized collection age data group M2, the standardized collection usage data group M3 and the standardized collection historical playback quantity group M4, and after feature extraction and combined with machine learning calculation, obtains several collection heat indexes Xrd; The planned playback module obtains a plurality of collection heat indexes Xrd, and obtains a collection playback plan sequence XH according to a mapping relationship between the heat coefficient Xrd of each collection and the collection heat of the corresponding collection code, and plays the corresponding collection multimedia video according to the collection playback plan sequence XH; The crowd adjustment module monitors the crowd status of the multimedia showcase area in real time based on the playback process of the current multimedia showcase according to the collection playback plan sequence XH, so as to determine the crowd congestion level of the current multimedia showcase area, and issues and executes corresponding adjustment level instructions.

[0016] The present invention provides a method and system for controlling video content playback in a multimedia showcase, which has the following beneficial effects: (1) The video content playback control method and system for multimedia display cabinets optimizes the playback experience and management efficiency of multimedia display cabinets by introducing intelligent content regulation and real-time crowd monitoring mechanism. First, based on the museum's collection database, the standardized collection data is obtained and screened through the API interface, and the Z-score standardization algorithm and machine learning model are combined to dynamically calculate the heat index Xrd of each collection, and generate an optimized collection playback plan sequence XH. This on-demand playback mechanism can ensure that hot collections in the display cabinet are displayed first, while taking into account the exposure rate of unpopular collections, thereby improving the diversity and viewing value of the display cabinet content, and solving the problem of low user retention rate caused by the homogeneity of existing display cabinet content. Secondly, a real-time crowd monitoring function is introduced, combined with a high-definition camera and a crowd density calculation module, to dynamically analyze the viewing density of people in the display cabinet area. When the crowd density Dmd in the display case area is equal to or greater than the crowd density threshold P, a first-level adjustment instruction is issued to divert the audience by displaying text prompts. At the same time, the playback plan is adjusted to reduce the popularity of the currently played video hot content to prevent audiences from crowding. Compared with the traditional fixed playback mode and manual intervention, the current multimedia display case video content playback control not only optimizes management efficiency but also improves the audience's visiting experience and ensures the safety of the exhibition site. In addition, the highly automated characteristics reduce the frequency and complexity of manual operations, providing the museum with an intelligent, dynamic and personalized exhibition management solution. In general, by dynamically adjusting the playback order, real-time monitoring of crowd status, and combining the popularity of the collection with the audience's preferences, the intelligent algorithm can achieve on-demand playback of content and regional crowd diversion, thereby optimizing the use efficiency of multimedia display cases and improving user experience.

[0017] (2) Through the collection popularity analysis and playback plan generation mechanism, it is possible to generate a playback plan sequence with popularity priority based on the multi-dimensional data of the collection's classification, age, purpose and historical playback records, combined with Z-score standardization and intelligent sorting algorithms. This dynamic content regulation strategy can not only give priority to displaying content that attracts high attention from the audience, but also increase the exposure of unpopular collections by playing videos of low-popular collections, thereby balancing the display effect of the display cabinet content. Compared with the traditional fixed content playback mode, dynamic regulation has greatly improved the personalization and diversity of multimedia display cabinet content, enabling multimedia display cabinets to continue to attract audiences and improve the problem of low subsequent user retention rate.

[0018] (3) By introducing a crowd monitoring and adjustment process based on high-definition cameras and passenger flow statistics, the crowd density Dmd in the multimedia display case area can be obtained in real time, and the degree of crowding of the audience can be judged by the preset crowd density threshold P. When the crowd in the multimedia display case area is crowded, the first-level adjustment instruction is issued to guide the audience to other areas. At the same time, the current playback plan is dynamically adjusted to reduce the popularity of hot content and alleviate the phenomenon of audience crowding. This intelligent diversion mechanism effectively avoids safety hazards, improves the balance of crowd distribution in the display case area, and provides a more comfortable visiting environment for the audience. Compared with the traditional manual intervention mode, it significantly improves the management efficiency of the museum's multimedia display case and the intelligent level of video content playback. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A schematic diagram of a flow chart of a video content playback control method for a multimedia showcase according to the present invention; Figure 2 The present invention is a block diagram of a video content playback control system for multimedia showcases. DETAILED DESCRIPTION

[0020] 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.

[0021] Example 1 See also Figure 1 , the present invention provides a video content playback control method for multimedia showcases, comprising the following steps; S1. By searching the collection database in the museum, the original data of the specified field is obtained, and the obtained original data is screened and filtered. After feature extraction, the equipment collection data set X is constructed; S2, based on the constructed equipment collection data set X, and combined with the Z-score standardization processing method, obtain the standardized collection classification data group M1, the standardized collection age data group M2, the standardized collection usage data group M3 and the standardized collection historical playback quantity group M4; S3, based on the constructed standardized collection classification data group M1, the standardized collection age data group M2, the standardized collection usage data group M3 and the standardized collection historical playback quantity group M4, after feature extraction and combined with machine learning calculation, obtain several collection heat indexes Xrd; S4, based on obtaining a number of collection heat indexes Xrd, and according to the collection heat mapping relationship between the heat coefficient Xrd of each collection and the collection heat of the corresponding collection code, obtaining a collection play plan sequence XH, and playing the corresponding collection multimedia video according to the collection play plan sequence XH; S5. Based on the playback process of the current multimedia showcase according to the collection playback plan sequence XH, the crowd flow status of the multimedia showcase area is monitored in real time to determine the crowd congestion level of the current multimedia showcase area, and corresponding adjustment level instructions are issued and executed.

[0022] In this embodiment, through the intelligent control of video content playback in the multimedia showcase, the intelligent level of showcase content playback and the comfort of audience experience can be effectively improved; first, with the help of in-depth analysis and standardized processing of the collection database X, key data can be accurately screened and extracted, and the collection heat index Xrd with multi-dimensional weights of classification, age, purpose, and historical playback can be dynamically generated to achieve on-demand recommendation and playback plan optimization; secondly, by constructing a playback plan sequence XH based on the collection heat index Xrd, hot collections preferred by the audience can be played first, and low-heat content can be reasonably inserted to improve the exposure rate and exhibition diversity of unpopular collections; in addition, real-time crowd monitoring and dynamic adjustment functions are introduced. When the showcase area is crowded, adjustment instructions can be quickly issued to reduce the attractiveness of the hot area by prompting the audience to divert or adjust the playback order, effectively alleviating the crowding phenomenon and ensuring safety; in general, by dynamically adjusting the playback order, real-time monitoring of the crowd status, and combining the collection heat and the audience preference of the intelligent algorithm, the on-demand playback of content and the regional crowd diversion can be achieved, thereby optimizing the use efficiency of the multimedia showcase and improving the user experience.

[0023] Example 2 Please refer to Figure 1 , specifically: S1 specific steps include: S11. Based on the collection database that the museum has as stipulated in the Collection Regulations, the API interface of the collection database is adapted to a unified interface format through a standardized API interface adaptation layer, wherein the API interface adaptation layer is used to parse and process the protocol differences of different APIs, and perform data format conversion and field mapping; the Collection Regulations specifically stipulate that the Museum Grading and Evaluation Standards (2021 Edition) stipulate that the collection regulations must have a collection database, and the number must reach 300, and the safety regulations stipulate that the reference population must be scientifically monitored; S12. Based on the API interface adaptation layer, a search request is made to the collection database to obtain the original data of the specified field, and the obtained original data is screened and filtered. After feature extraction, the equipment collection data set X is constructed. The specific steps are as follows: S13. Screening and filtering the acquired raw data includes: removing records with incomplete fields in the raw data (entries with missing classification and use information); identifying logically contradictory records (inconsistent age and classification and repeated marking of use fields), and performing data consistency verification in combination with data verification algorithms (rule verification and cross-field comparison); deleting collection records that are not within the current multimedia showcase video playback range, and performing dynamic comparison based on the display list in the playback settings; S14. According to the historical exhibition records and audience behavior feedback in the equipment collection data set X, and in combination with feature extraction technology, key fields are extracted from the screened and filtered original data to construct the equipment collection data set X. The equipment collection data set X includes a collection classification data group X1, a collection age data group X2, a collection usage data group X3, and a collection historical playback quantity data group X4.

[0024] In this embodiment, through step S1, efficient docking and data extraction of the museum collection database X are achieved to ensure the standardization and accuracy of data processing. Through the standardized API interface adaptation layer, data of different protocols and formats can be parsed and processed, and field mapping and format conversion can be automatically completed to meet the specification requirements of the "Museum Grading and Evaluation Standards" (2021 Edition), laying the foundation for subsequent intelligent display. At the same time, the original data is screened and filtered in combination with the data verification algorithm to eliminate invalid records with incomplete field filling, logical contradictions or not in the current playback range, thereby improving the integrity and consistency of the data. In addition, through the in-depth analysis of historical exhibition records and audience behavior feedback by feature extraction technology, a multidimensional data group of classification, age, purpose and historical playback quantity can be accurately constructed. This full-process screening and dynamic construction mechanism not only ensures the high-quality input of the equipment collection data set X, but also has the ability to dynamically optimize the playback content, providing solid data support for intelligent and personalized video playback control, and improving the efficiency and scientificity of museum showcase content management and display.

[0025] Example 3 Please refer to Figure 1 , specifically: S2 specific steps include: S21, based on the constructed equipment collection data set X, and in combination with the Z-score standardization processing method, data standardization processing is performed on the collection classification data group X1, the collection age data group X2, the collection usage data group X3, and the collection historical playback quantity data group X4 in the equipment collection data set X. The specific steps are as follows: S211, the collection classification data group X1 includes the classification information heat coefficient x1 of each collection, and after processing with a statistical mean value algorithm, the mean value of the classification information heat coefficient in the collection classification data group X1 is obtained. , compare the classification information heat coefficient x1 of each collection in the collection classification data set X1 with the mean of the classification information heat coefficient Compare and analyze the classification information heat coefficient x1 and the mean classification information heat coefficient of each collection The degree of deviation is obtained by fitting the standardized classification information heat coefficient m1 of each collection, which is obtained by the following formula:

[0026] In the formula, It is expressed as the classification information heat coefficient of the i-th collection, It is represented by the standard deviation of the classification information heat coefficient in the collection classification data set X1, i = 1, 2, 3, ..., n, n represents the number of collections; According to the standardized classification information heat coefficient m1 of each collection, a standardized collection classification data group M1 is constructed.

[0027] Specifically, the specific steps of S21 also include: S212: The collection age data group X2 includes the historical age heat coefficient x2 of each collection, and after processing with a statistical mean value algorithm, the mean value of the historical age heat coefficient in the collection age data group X2 is obtained. , compare the historical age heat coefficient x2 of each collection in the collection age data group X2 with the mean of the historical age heat coefficient Compare and analyze the historical age heat coefficient x2 and the mean historical age heat coefficient of each collection The degree of deviation is used to fit the standardized historical age heat coefficient m2 of each collection, which is obtained by the following formula:

[0028] In the formula, Expressed as the historical age heat coefficient of the i-th collection, It is represented by the standard deviation of the heat coefficient of the historical era in the collection age data group X2, i = 1, 2, 3, ..., n, n represents the number of collections; According to the standardized historical age heat coefficient m2 of each collection, a standardized collection age data group M2 is constructed.

[0029] Specifically, the specific steps of S21 also include: S213: The collection use data group X3 includes the functional use heat coefficient x3 of each collection, and after processing with a statistical mean value algorithm, the mean value of the functional use heat coefficient in the collection use data group X3 is obtained. , compare the functional use heat coefficient x3 of each collection in the collection use data set X3 with the mean functional use heat coefficient Compare and analyze the functional use heat coefficient x3 and the mean functional use heat coefficient of each collection The degree of deviation is fitted to obtain the standardized functional use heat coefficient m3 of each collection, which is obtained by the following formula:

[0030] In the formula, It is expressed as the functional use heat coefficient of the i-th collection, It is represented by the standard deviation of the functional use heat coefficient in the collection use data set X3, i = 1, 2, 3, ..., n, n represents the number of collections; According to the standardized functional use heat coefficient m3 of each collection, a standardized collection use data group M3 is constructed.

[0031] Specifically, the specific steps of S21 also include: S214: The collection history play quantity data set X4 includes the video play quantity x4 of each collection, and after processing with a statistical mean value algorithm, the mean value of the video play quantity in the collection history play quantity data set X4 is obtained. , the video play count x4 of each collection in the collection history play count data set X4 and the mean video play count Compare and analyze the video playback times x4 and the average video playback times of each collection The degree of deviation is fitted to obtain the standardized video playback number m4 of each collection, which is obtained by the following formula:

[0032] In the formula, It is represented by the number of video plays of the i-th collection, It is represented by the standard deviation of the number of video plays x4 in the collection history play count data set X4, i = 1, 2, 3, ..., n, n represents the number of collections; According to the standardized video play quantity m4 of each collection, a standardized collection historical play quantity group M4 is constructed.

[0033] It should be noted that based on the historical exhibition records and audience behavior feedback in the equipment collection data set X, the playback time, audience stay time and interactive behavior indicators of the historical exhibition data are integrated to analyze and extract the preference degree of the three attributes of the collection's classification, age and use, and respectively form a collection's classification information heat comparison table, a historical age heat comparison table and a functional use heat comparison table; by comparing the three attributes of the collection's classification, age and use with the corresponding heat comparison tables, the classification information heat coefficient x1, the historical age heat coefficient x2 and the functional use heat coefficient x3 of the corresponding collection are respectively obtained; The classification information heat coefficient x1 reflects the audience preference for different collection categories (such as stoneware, pottery and jade) in historical exhibitions. For example, if the visit rate and interaction frequency of stoneware collections are high, the classification information heat coefficient x1 will be increased accordingly; The historical age heat coefficient x2 of the collection is derived from the historical background of the collection. Generally, the more important the historical nodes and the more culturally significant the collections are (such as Tang Dynasty porcelain and Han Dynasty jade), the more attention the audience will pay to the collections during the exhibition, and the corresponding historical age heat coefficient x2 will increase accordingly. The functional use heat coefficient x3 is generated by analyzing the functional display of the collection in the exhibition (such as the ritual cultural value of ritual vessels and the practical interpretation of daily utensils), and can reflect the audience's interest in collections with different uses.

[0034] In this embodiment, the multi-dimensional standardization processing of the equipment collection data set X improves the accuracy and comparability of the collection heat calculation. Based on the Z-score standardization method, the collection's classification information heat coefficient x1, historical age heat coefficient x2, functional use heat coefficient x3 and video playback quantity x4 are dimensionlessly converted to construct corresponding standardized data. This process analyzes historical exhibition records and audience behavior feedback, and comprehensively considers the audience's playback time, stay time and interactive behavior indicators to dynamically generate a classification information heat comparison table, a historical age heat comparison table and a functional use heat comparison table. Through comparison and matching, the heat characteristics of each collection in the three dimensions of classification, age and use can be accurately extracted. This comprehensive multi-dimensional data standardization not only eliminates the dimensional differences between attributes, but also improves the scientific nature of the calculation of the heat coefficient, providing high-quality data support for the subsequent generation of personalized playback plans.

[0035] Example 4 Please refer to Figure 1 , specifically: S3 specific steps include: S31, based on the constructed standardized collection classification data group M1, the standardized collection age data group M2, the standardized collection usage data group M3 and the standardized collection historical playback quantity group M4, after feature extraction and combined with machine learning calculation, obtain several collection heat indexes Xrd, one of which is: the collection heat index Xrd of the i-th collection i , which is obtained by the following formula:

[0036] In the formula, It is expressed as the standardized classification information heat coefficient of the i-th collection, Expressed as the standardized historical age heat coefficient of the i-th collection, It is expressed as the standardized functional use heat coefficient of the i-th collection, It is represented as the normalized number of video plays of the i-th collection, , , and are all expressed as weight values.

[0037] In this embodiment, the standardized data and the machine learning calculation model are used to generate the collection heat index Xrd of each collection; the collection heat index Xrd integrates the standardized results of the collection's classification information heat, historical age heat, functional use heat and historical playback quantity, and combines it with weight distribution to reflect the comprehensive appeal of each collection in the audience's preference. This process not only realizes the scientific integration of multi-dimensional attributes, but also conducts in-depth analysis of audience behavior preferences through machine learning algorithms, and dynamically adjusts weights to optimize the accuracy and practicality of heat calculation. Compared with the traditional fixed sorting mode, the generation of the collection heat index Xrd can more comprehensively reflect the actual popularity of the collection, and provides a scientific basis for the intelligent sorting of playback plans.

[0038] Example 5 Please refer to Figure 1 , specifically: S4 specific steps include: S41. According to the coding information marked by each collection, feature extraction is performed on the coding information of the collection in the equipment collection data set X to obtain the collection code Ccp of each collection. Based on obtaining a number of collection heat indexes Xrd, and according to the collection heat mapping relationship between the heat coefficient Xrd of each collection and the corresponding collection code Ccp, a collection heat coefficient mapping sequence XL is constructed in the form of ; S42, sorting the heat indexes Xrd of several collections in reverse order from high to low, while retaining the corresponding collection codes Ccp, and obtaining the collection heat sorting sequence XP arranged by heat priority after sorting, in the form of ; S43, according to the sorting results, extract the corresponding collection codes Ccp in turn, and obtain the collection playback plan sequence XH in the form of , the collection playback plan sequence XH is sent to the video playback platform of the multimedia showcase, and the corresponding collection multimedia video is played according to the collection playback plan sequence.

[0039] In this embodiment, through the analysis process of S4, intelligent sorting and scheduling of the playback plan based on the collection heat index Xrd is realized. First, by extracting the collection code Ccp in the device collection data set X and constructing the collection heat coefficient mapping sequence XL, the accurate association between the collection heat index Xrd and the collection code Ccp is realized. Then, by sorting the collection heat index Xrd from high to low, a collection heat sorting sequence XP arranged by priority is generated to ensure that the collection content with high heat is displayed first. Finally, a collection playback plan sequence XH is generated according to the heat sorting result, and it is sent to the video playback platform of the multimedia showcase to achieve precise control of on-demand playback. Compared with the traditional static or fixed playback order mode, dynamic content scheduling is realized based on heat sorting, so that hot collections get more display opportunities, ensuring the diversity and attractiveness of the showcase content display, which not only improves the management efficiency of the multimedia showcase content and the audience satisfaction, but also enhances the flexibility and personalization of the exhibition content, providing the audience with a more attractive dynamic viewing experience.

[0040] Example 6 Please refer to Figure 1 Specifically: S5 includes the following steps: S51, based on the playback process of the current multimedia showcase according to the collection playback plan sequence, the crowd flow state in the multimedia showcase area is monitored in real time by a high-definition camera to obtain the crowd flow density Dmd; S52, presetting a crowd density threshold P, and comparing the obtained crowd density Dmd with the preset crowd density threshold P to determine the crowd congestion level of the current multimedia showcase area, and issuing and executing a corresponding adjustment level instruction. The specific process is as follows: If the crowd density Dmd≥the crowd density threshold P, it means that the multimedia showcase is currently playing according to the playing plan, and the crowd flow in the multimedia showcase area is in a crowded state, and at this time, a first-level adjustment instruction is sent out; If the crowd density Dmd is less than the crowd density threshold P, it means that the multimedia showcase is currently playing according to the play plan, and the crowd flow in the multimedia showcase area is not in a crowded state, and at this time, a secondary adjustment instruction is sent out; S521. According to the received primary adjustment instruction and secondary adjustment instruction, the following contents are specifically executed: When receiving the first-level adjustment instruction, the execution content is to display "The current number of viewers is crowded. For a better viewing experience, please move to other ordinary showcases to watch" in the form of text on the multimedia showcase panel; at the same time, the current playback order according to the collection playback plan sequence is changed to reverse playback to reduce the popularity of the collection multimedia video currently being played, until the flow of people in the multimedia showcase area is not in a crowded state, then adjust to play the collection multimedia video according to the playback plan; When receiving the secondary adjustment instruction, the execution content is to continue to monitor the flow of people in the current multimedia display cabinet area, and play the collection multimedia video according to the playback plan.

[0041] In this embodiment, through step S5, the dynamic adjustment function of the showcase area based on real-time crowd flow monitoring is realized, and a safe and efficient audience diversion and management mechanism is provided for the multimedia showcase. By using a high-definition camera to monitor the crowd density Dmd in the showcase area in real time and compare it with the preset crowd density threshold P, it can quickly determine whether the showcase is in a crowded state and issue a corresponding adjustment level instruction. When the crowd density Dmd is greater than or equal to the crowd density threshold P, the audience is guided to other areas by issuing a first-level adjustment instruction, and the playback plan is dynamically adjusted to reverse playback to reduce the attractiveness of the current showcase hot content and effectively alleviate the crowded state; when the crowd density Dmd is less than the crowd density threshold P, the normal playback is maintained through the second-level adjustment instruction and the regional status is continuously monitored. This method not only optimizes the audience distribution at the exhibition site and prevents the audience from crowding in the hot area, but also maintains the audience's continuous interest by flexibly adjusting the playback content, ensuring the display effect and regional safety of the showcase. Compared with the traditional static management mode, it realizes automatic and intelligent dynamic adjustment, improves the exhibition management efficiency and the audience's viewing experience, and provides an important guarantee for the efficient operation of the multimedia showcase in a complex visiting environment.

[0042] Example 7 Please refer to Figure 1 and Figure 2 ,Specifically: A video content playback control system for multimedia display cabinets, including a data extraction module, a standardization module, a collection heat analysis module, a planned playback module and a crowd flow adjustment module; The data extraction module is used to search the collection database in the museum to obtain the original data of the specified field, screen and filter the obtained original data, and construct the equipment collection data set X after feature extraction; The standardization module is based on the constructed equipment collection data set X and combined with the Z-score standardization processing method to obtain the standardized collection classification data group M1, the standardized collection age data group M2, the standardized collection usage data group M3 and the standardized collection historical playback quantity group M4; The collection heat analysis module is based on the constructed standardized collection classification data group M1, the standardized collection age data group M2, the standardized collection usage data group M3 and the standardized collection historical playback quantity group M4, and after feature extraction and combined with machine learning calculation, obtains several collection heat indexes Xrd; The planned playback module obtains a plurality of collection heat indexes Xrd, and obtains a collection playback plan sequence XH according to a mapping relationship between the heat coefficient Xrd of each collection and the collection heat of the corresponding collection code, and plays the corresponding collection multimedia video according to the collection playback plan sequence XH; The crowd adjustment module monitors the crowd status of the multimedia showcase area in real time based on the playback process of the current multimedia showcase according to the collection playback plan sequence XH, so as to determine the crowd congestion level of the current multimedia showcase area, and issues and executes corresponding adjustment level instructions.

[0043] 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. A method for controlling video content playback in a multimedia showcase, characterized in that: The steps include: S1. By searching the collection database in the museum, the original data of the specified field is obtained, and the obtained original data is screened and filtered. After feature extraction, the equipment collection data set X is constructed; S2, based on the constructed equipment collection data set X, and combined with the Z-score standardization processing method, obtain the standardized collection classification data group M1, the standardized collection age data group M2, the standardized collection usage data group M3 and the standardized collection historical playback quantity group M4; S3, based on the constructed standardized collection classification data group M1, the standardized collection age data group M2, the standardized collection usage data group M3 and the standardized collection historical playback quantity group M4, after feature extraction and combined with machine learning calculation, obtain several collection heat indexes Xrd; S4, based on obtaining a number of collection heat indexes Xrd, and according to the collection heat mapping relationship between the heat coefficient Xrd of each collection and the collection heat of the corresponding collection code, obtaining a collection play plan sequence XH, and playing the corresponding collection multimedia video according to the collection play plan sequence XH; S5. Based on the playback process of the current multimedia showcase according to the collection playback plan sequence XH, the crowd flow status of the multimedia showcase area is monitored in real time to determine the crowd congestion level of the current multimedia showcase area, and corresponding adjustment level instructions are issued and executed.

2. The method for controlling video content playback in a multimedia showcase according to claim 1, characterized in that: The specific steps of S1 include: S11. Based on the collection database that the museum has as stipulated in the Collection Regulations, the API interface of the collection database is adapted to a unified interface format through a standardized API interface adaptation layer, wherein the API interface adaptation layer is used to parse and process the protocol differences of different APIs, and perform data format conversion and field mapping; S12. Based on the API interface adaptation layer, a search request is made to the collection database to obtain the original data of the specified field, and the obtained original data is screened and filtered. After feature extraction, the equipment collection data set X is constructed. The specific steps are as follows: S13, screening and filtering the acquired raw data includes: removing records with incomplete fields in the raw data; identifying logically contradictory records, and performing data consistency verification in combination with a data verification algorithm; deleting collection records that are not within the current multimedia showcase video playback range, and performing dynamic comparison based on the display list in the playback settings; S14. According to the historical exhibition records and audience behavior feedback in the equipment collection data set X, and in combination with feature extraction technology, key fields are extracted from the screened and filtered original data to construct the equipment collection data set X. The equipment collection data set X includes a collection classification data group X1, a collection age data group X2, a collection usage data group X3, and a collection historical playback quantity data group X4.

3. The method for controlling video content playback in a multimedia showcase according to claim 2, characterized in that: The specific steps of S2 include: S21, based on the constructed equipment collection data set X, and in combination with the Z-score standardization processing method, data standardization processing is performed on the collection classification data group X1, the collection age data group X2, the collection usage data group X3, and the collection historical playback quantity data group X4 in the equipment collection data set X. The specific steps are as follows: S211, the collection classification data group X1 includes the classification information heat coefficient x1 of each collection, and after processing with a statistical mean value algorithm, the mean value of the classification information heat coefficient in the collection classification data group X1 is obtained. , compare the classification information heat coefficient x1 of each collection in the collection classification data set X1 with the mean of the classification information heat coefficient Compare and analyze the classification information heat coefficient x1 and the mean classification information heat coefficient of each collection The degree of deviation is calculated by fitting the standardized classification information heat coefficient m1 of each collection to construct the standardized collection classification data set M1.

4. The method for controlling video content playback in a multimedia showcase according to claim 3, characterized in that: The specific steps of S21 also include: S212: The collection age data group X2 includes the historical age heat coefficient x2 of each collection, and after processing with a statistical mean value algorithm, the mean value of the historical age heat coefficient in the collection age data group X2 is obtained. , compare the historical age heat coefficient x2 of each collection in the collection age data group X2 with the mean of the historical age heat coefficient Compare and analyze the historical age heat coefficient x2 and the mean historical age heat coefficient of each collection The degree of deviation is calculated by fitting the standardized historical age heat coefficient m2 of each collection to construct the standardized collection age data group M2.

5. The method for controlling video content playback in a multimedia showcase according to claim 3, characterized in that: The specific steps of S21 also include: S213: The collection use data group X3 includes the functional use heat coefficient x3 of each collection, and after processing with a statistical mean value algorithm, the mean value of the functional use heat coefficient in the collection use data group X3 is obtained. , compare the functional use heat coefficient x3 of each collection in the collection use data set X3 with the mean functional use heat coefficient Compare and analyze the functional use heat coefficient x3 and the mean functional use heat coefficient of each collection The degree of deviation is calculated by fitting the standardized functional use heat coefficient m3 of each collection to construct the standardized collection use data set M3.

6. The method for controlling video content playback in a multimedia showcase according to claim 3, characterized in that: The specific steps of S21 also include: S214: The collection history play quantity data set X4 includes the video play quantity x4 of each collection, and after processing with a statistical mean value algorithm, the mean value of the video play quantity in the collection history play quantity data set X4 is obtained. , the video play count x4 of each collection in the collection history play count data set X4 and the mean video play count Compare and analyze the number of video plays x4 and the average number of video plays for each collection The degree of deviation is obtained by fitting the standardized video playback quantity m4 of each collection to construct the standardized collection historical playback quantity group M4.

7. The method for controlling video content playback in a multimedia showcase according to claim 6, characterized in that: The specific steps of S3 include: S31, based on the constructed standardized collection classification data group M1, the standardized collection age data group M2, the standardized collection usage data group M3 and the standardized collection historical playback quantity group M4, after feature extraction and combined with machine learning calculation, obtain several collection heat indexes Xrd, one of which is: the collection heat index Xrd of the i-th collection i , which is obtained by the following formula: In the formula, It is expressed as the standardized classification information heat coefficient of the i-th collection, Expressed as the standardized historical age heat coefficient of the i-th collection, It is expressed as the standardized functional use heat coefficient of the i-th collection, It is represented as the normalized number of video plays of the i-th collection, , , and are all expressed as weight values.

8. The method for controlling video content playback in a multimedia showcase according to claim 7, characterized in that: The specific steps of S4 include: S41. According to the coding information marked by each collection, feature extraction is performed on the coding information of the collection in the equipment collection data set X to obtain the collection code Ccp of each collection. Based on obtaining a number of collection heat indexes Xrd, and according to the collection heat mapping relationship between the heat coefficient Xrd of each collection and the corresponding collection code Ccp, a collection heat coefficient mapping sequence XL is constructed in the form of ; S42, sorting the heat indexes Xrd of several collections in reverse order from high to low, while retaining the corresponding collection codes Ccp, and obtaining the collection heat sorting sequence XP arranged by heat priority after sorting, in the form of ; S43, according to the sorting results, extract the corresponding collection codes Ccp in turn, and obtain the collection playback plan sequence XH in the form of , the collection playback plan sequence XH is sent to the video playback platform of the multimedia showcase, and the corresponding collection multimedia video is played according to the collection playback plan sequence.

9. The method for controlling video content playback in a multimedia showcase according to claim 8, characterized in that: The specific steps of S5 include: S51, based on the playback process of the current multimedia showcase according to the collection playback plan sequence, the crowd flow state in the multimedia showcase area is monitored in real time by a high-definition camera to obtain the crowd flow density Dmd; S52, presetting a crowd density threshold P, and comparing the obtained crowd density Dmd with the preset crowd density threshold P to determine the crowd congestion level of the current multimedia showcase area, and issuing and executing a corresponding adjustment level instruction. The specific process is as follows: If the crowd density Dmd≥the crowd density threshold P, it means that the multimedia showcase is currently playing according to the playing plan, and the crowd flow in the multimedia showcase area is in a crowded state, and at this time, a first-level adjustment instruction is sent out; If the crowd density Dmd is less than the crowd density threshold P, it means that the multimedia showcase is currently playing according to the play plan, and the crowd flow in the multimedia showcase area is not in a crowded state, and at this time, a secondary adjustment instruction is sent out; S521. According to the received primary adjustment instruction and secondary adjustment instruction, the following contents are specifically executed: When receiving the first-level adjustment instruction, the execution content is to display "The current number of viewers is crowded. For a better viewing experience, please move to other ordinary showcases to watch" in the form of text on the multimedia display cabinet panel; at the same time, the current playback order according to the collection playback plan sequence is changed to reverse playback to reduce the popularity of the collection multimedia video currently being played, until the flow of people in the multimedia display cabinet area is not in a crowded state, then adjust to play the collection multimedia video according to the playback plan; When receiving the secondary adjustment instruction, the execution content is to continue to monitor the flow of people in the current multimedia display cabinet area, and play the collection multimedia video according to the playback plan.

10. A video content playback control system for multimedia showcases, used to implement a video content playback control method for multimedia showcases as described in any one of claims 1 to 9, characterized in that: It includes data extraction module, standardization module, collection popularity analysis module, planned playback module and crowd flow adjustment module; The data extraction module is used to search the collection database in the museum to obtain the original data of the specified field, screen and filter the obtained original data, and construct the equipment collection data set X after feature extraction; The standardization module is based on the constructed equipment collection data set X and combined with the Z-score standardization processing method to obtain the standardized collection classification data group M1, the standardized collection age data group M2, the standardized collection usage data group M3 and the standardized collection historical playback quantity group M4; The collection heat analysis module is based on the constructed standardized collection classification data group M1, the standardized collection age data group M2, the standardized collection usage data group M3 and the standardized collection historical playback quantity group M4, and after feature extraction and combined with machine learning calculation, obtains several collection heat indexes Xrd; The planned playback module obtains a plurality of collection heat indexes Xrd, and obtains a collection playback plan sequence XH according to a mapping relationship between the heat coefficient Xrd of each collection and the collection heat of the corresponding collection code, and plays the corresponding collection multimedia video according to the collection playback plan sequence XH; The crowd adjustment module monitors the crowd status of the multimedia showcase area in real time based on the playback process of the current multimedia showcase according to the collection playback plan sequence XH, so as to determine the crowd congestion level of the current multimedia showcase area, and issues and executes corresponding adjustment level instructions.

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