A video tag sharing and multiplexing method, device, electronic device and medium

Abstract

The present application discloses a method, apparatus, electronic device and medium for sharing and reusing video tags. The present application relates to the technical field of video processing, and includes: obtaining urban video image information, dividing the urban video image information to obtain a plurality of sub-image information; determining a similar region according to the sub-image information and preset standard image information; determining the similarity of each similar region; if the similarity is greater than a preset similarity, determining the landform feature and objective environment feature of the similar region; determining shared tag information according to the landform feature and the objective environment feature; and determining video tag information based on the shared tag information. The present application can improve the accuracy of sharing and reusing video tags.

Description

Technical Field

[0001] This application relates to the field of video processing technologies, and in particular, to a method, apparatus, electronic device, and medium for sharing and reusing video tags. Background Art

[0002] With the accelerating advancement of the construction of smart cities, video surveillance systems are an important component. However, since there are a large number of video resources in a video aggregation platform, there are thousands of video streams at the small scale and hundreds of thousands of video streams at the large scale, and the video points are scattered in different locations, resulting in huge video data and increased difficulty in analysis work. Therefore, the management and utilization of massive video information have become a key issue.

[0003] Traditional video tag processing methods mainly involve real-time analysis of a single video stream by staff, designing fixed templates, and using the fixed templates to perform tagging processing on the video.

[0004] However, traditional video tag sharing and reuse methods are prone to human interference when facing large-scale, multi-source heterogeneous video data, resulting in inaccurate video tags and low efficiency. Summary of the Invention

[0005] In order to improve the accuracy of video tag sharing and reuse, this application provides a method, apparatus, electronic device, and medium for sharing and reusing video tags.

[0006] In a first aspect, this application provides a method for sharing and reusing video tags, adopting the following technical solution:

[0007] A method for sharing and reusing video tags includes:

[0008] Obtain urban video image information, divide the urban video image information to obtain a plurality of sub-image information;

[0009] Determine similar regions according to the sub-image information and preset standard image information;

[0010] Determine the similarity of each similar region;

[0011] If the similarity is greater than a preset similarity, determine the geomorphic features and objective environmental features of the similar region;

[0012] Determine shared tag information according to the geomorphic features and the objective environmental features;

[0013] Determine video tag information based on the shared tag information.

[0014] By adopting the above technical solution, after obtaining the urban video image information, the urban video image information is divided to obtain a plurality of sub-image information, thereby improving the accuracy of image analysis; then, the sub-image information is compared with the preset standard image information to determine the similar regions; thereafter, the similarity of the similar regions corresponding to the sub-image information and the preset standard image information is determined; the similarity is compared with the preset similarity. If the similarity is greater than the preset similarity, it indicates that the coincidence degree of the sub-image information and the preset standard image information is relatively high at this time. Then, the geomorphic features and objective environment features corresponding to the similar regions are determined; the geomorphic features and the objective environment features are analyzed to determine the shared tag information; then, according to the shared tag information, the video tag information is determined, thereby improving the accuracy of video tag sharing and reuse.

[0015] In one possible implementation manner, the dividing the urban video image information to obtain a plurality of sub-image information includes:

[0016] According to the urban video image information, video element information is determined;

[0017] According to the video element information, element classification is determined;

[0018] Based on the element classification, an image division criterion is determined;

[0019] Based on the image division criterion, the plurality of sub-image information is obtained.

[0020] In one possible implementation manner, the determining the similar regions according to the sub-image information and the preset standard image information includes:

[0021] Feature extraction is performed on the sub-image information to determine first feature information;

[0022] Feature extraction is performed on the preset standard image information to determine second feature information;

[0023] According to the sub-image information and the preset standard image information, first edge information and second edge information are determined;

[0024] The similarity value between the first feature information and the second feature information is calculated;

[0025] If the similarity value is greater than the preset similarity value, the coincidence degree between the first edge information and the second edge information is determined;

[0026] If the coincidence degree is greater than the preset coincidence degree, the similar regions are determined.

[0027] In one possible implementation manner, the determining the geomorphic features and objective environment features of the similar regions includes:

[0028] Determine the urban geomorphic image according to the urban video image information;

[0029] Determine the geomorphic features based on the urban geomorphic image;

[0030] Obtain the urban environmental information;

[0031] Determine the environmental elements according to the urban environmental information;

[0032] Determine the objective environmental features based on the environmental elements.

[0033] In a possible implementation manner, before determining the shared tag information, it further includes:

[0034] Obtain the urban attribute information and the scene information;

[0035] Determine the classification criteria according to the urban attribute information and the scene information;

[0036] Determine the thematic tag information according to the classification criteria;

[0037] Determine the tag tree based on the thematic tag information;

[0038] Establish a preset shared tag library according to the tag tree.

[0039] In a possible implementation manner, the determining the shared tag information according to the geomorphic features and the objective environmental features includes:

[0040] Obtain the urban coordinate information;

[0041] Determine the first keyword according to the geomorphic features and the urban coordinate information;

[0042] Determine the second keyword according to the objective environmental features;

[0043] Determine the common keyword according to the first keyword and the second keyword;

[0044] Determine the shared tag information based on the common keyword and the preset shared tag library.

[0045] In a possible implementation manner, the determining the video tag information based on the shared tag information includes:

[0046] Determine the tag theme and the tag category based on the shared tag information;

[0047] Determine the target shared tag according to the tag theme and the tag category;

[0048] Determine the first tag information according to the target shared tag;

[0049] Determine the accuracy corresponding to the first tag information;

[0050] If the accuracy is greater than the preset accuracy, determine the first tag information as the video tag information.

[0051] In a second aspect, the present application provides a video tag sharing and reuse device, adopting the following technical solution:

[0052] A video tag sharing and reuse device includes: a sub-image information determination module, a similar region determination module, a similarity determination module, a feature determination module, a shared tag information determination module, and a video tag information determination module, where

[0053] The sub-image information determination module is configured to obtain urban video image information, divide the urban video image information, and obtain a plurality of sub-image information;

[0054] The similar region determination module is configured to determine a similar region according to the sub-image information and preset standard image information;

[0055] The similarity determination module is configured to determine the similarity of each similar region;

[0056] The feature determination module is configured to determine the geomorphic feature and objective environment feature of the similar region if the similarity is greater than the preset similarity;

[0057] The shared tag information determination module is configured to determine shared tag information according to the geomorphic feature and the objective environment feature;

[0058] The video tag information determination module is configured to determine video tag information based on the shared tag information.

[0059] By adopting the above technical solution, after the sub-image information determination module obtains the urban video image information, it divides the urban video image information to obtain multiple sub-image information, thereby improving the accuracy of image analysis; then the similar region determination module compares the sub-image information with the preset standard image information to determine the similar region; after that, the similarity determination module determines the similarity of the similar region corresponding to the sub-image information and the preset standard image information; the feature determination module compares the similarity with the preset similarity. If the similarity is greater than the preset similarity, it indicates that the coincidence degree of the sub-image information and the preset standard image information is relatively high at this time, and then determines the geomorphic features and objective environment features corresponding to the similar region; the common label information determination module analyzes the geomorphic features and objective environment features to determine the common label information; then the video label information determination module determines the video label information according to the common label information, thereby improving the accuracy of video label sharing and reuse.

[0060] In a possible implementation manner, the sub-image information determination module includes: a video element information determination unit, an element classification determination unit, an image division standard determination unit, and a sub-image information determination unit, where

[0061] The video element information determination unit is configured to determine video element information according to the urban video image information;

[0062] The element classification determination unit is configured to determine element classification according to the video element information;

[0063] The image division standard determination unit is configured to determine an image division standard based on the element classification;

[0064] The sub-image information determination unit is configured to obtain the multiple sub-image information based on the image division standard.

[0065] In a possible implementation manner, the similar region determination module includes: a first feature information determination unit, a second feature information determination unit, an edge information determination unit, a similarity value determination unit, a coincidence degree determination unit, and a similar region determination unit, where

[0066] The first feature information determination unit is configured to perform feature extraction on the sub-image information to determine first feature information;

[0067] The second feature information determination unit is configured to perform feature extraction on the preset standard image information to determine second feature information;

[0068] The edge information determination unit is configured to determine first edge information and second edge information according to the sub-image information and the preset standard image information;

[0069] A similarity value determination unit, configured to calculate a similarity value between the first feature information and the second feature information;

[0070] A coincidence degree determination unit, configured to determine a coincidence degree between the first edge information and the second edge information if the similarity value is greater than a preset similarity value;

[0071] A similar region determination unit, configured to determine the similar region if the coincidence degree is greater than a preset coincidence degree.

[0072] In a possible implementation manner, the feature determination module includes: an urban landform image determination unit, a landform feature determination unit, an urban environment information acquisition unit, an environmental element determination unit, and an objective environment feature determination unit, where

[0073] The urban landform image determination unit is configured to determine an urban landform image according to the urban video image information;

[0074] The landform feature determination unit is configured to determine the landform feature based on the urban landform image;

[0075] The urban environment information acquisition unit is configured to acquire urban environment information;

[0076] The environmental element determination unit is configured to determine environmental elements according to the urban environment information;

[0077] The objective environment feature determination unit is configured to determine the objective environment feature based on the environmental elements.

[0078] In a possible implementation manner, the video tag sharing and reuse device further includes: a first information acquisition module, a classification standard determination module, a special topic tag information determination module, a tag tree determination module, and a preset shared tag library establishment module, where

[0079] The first information acquisition module is configured to acquire urban attribute information and scene information;

[0080] The classification standard determination module is configured to determine a classification standard according to the urban attribute information and the scene information;

[0081] The special topic tag information determination module is configured to determine special topic tag information according to the classification standard;

[0082] The tag tree determination module is configured to determine a tag tree based on the special topic tag information;

[0083] The preset shared tag library establishment module is configured to establish a preset shared tag library according to the tag tree.

[0084] In a possible implementation manner, the shared tag information determination module includes: a city coordinate information acquisition unit, a first keyword determination unit, a second keyword determination unit, a common keyword determination unit, and a shared tag information determination unit, where,

[0085] The city coordinate information acquisition unit is configured to acquire city coordinate information;

[0086] The first keyword determination unit is configured to determine a first keyword according to the geomorphic features and the city coordinate information;

[0087] The second keyword determination unit is configured to determine a second keyword according to the objective environment features;

[0088] The common keyword determination unit is configured to determine a common keyword according to the first keyword and the second keyword;

[0089] The shared tag information determination unit is configured to determine the shared tag information based on the common keyword and the preset shared tag library.

[0090] In a possible implementation manner, the video tag information determination module includes: a tag theme determination unit, a target shared tag determination unit, a first tag information determination unit, an accuracy determination unit, and a video tag information determination unit, where,

[0091] The tag theme determination unit is configured to determine a tag theme and a tag category based on the shared tag information;

[0092] The target shared tag determination unit is configured to determine a target shared tag according to the tag theme and the tag category;

[0093] The first tag information determination unit is configured to determine first tag information according to the target shared tag;

[0094] The accuracy determination unit is configured to determine the accuracy corresponding to the first tag information;

[0095] The video tag information determination unit is configured to, if the accuracy is greater than a preset accuracy, determine the first tag information as the video tag information.

[0096] In a third aspect, the present application provides an electronic device, adopting the following technical solution:

[0097] An electronic device, the electronic device includes:

[0098] At least one processor;

[0099] A memory;

[0100] At least one application program, where the at least one application program is stored in a memory and configured to be executed by at least one processor, and the at least one application program is configured to: execute the above video tag sharing and multiplexing method.

[0101] In a fourth aspect, the present application provides a computer-readable storage medium, adopting the following technical solution:

[0102] A computer-readable storage medium, comprising: a computer program stored therein that can be loaded and executed by a processor to execute the above video tag sharing and multiplexing method.

[0103] In summary, the present application includes the following beneficial technical effects:

[0104] After obtaining urban video image information, the urban video image information is divided to obtain a plurality of sub-image information, thereby improving the accuracy of image analysis; then, the sub-image information is compared with preset standard image information to determine similar regions; thereafter, the similarity of the similar regions corresponding to the sub-image information and the preset standard image information is determined; the similarity is compared with a preset similarity. If the similarity is greater than the preset similarity, it indicates that the coincidence degree of the sub-image information and the preset standard image information is relatively high at this time. Then, the geomorphic features and objective environmental features corresponding to the similar regions are determined; the geomorphic features and objective environmental features are analyzed to determine common tag information; then, video tag information is determined according to the common tag information, thereby improving the accuracy of video tag sharing and multiplexing. Description of the Drawings

[0105] Figure 1 is a schematic flowchart of the video tag sharing and multiplexing method of the present application;

[0106] Figure 2 is a schematic block diagram of the video tag sharing and multiplexing device of the present application;

[0107] Figure 3 is a schematic diagram of an electronic device according to an embodiment of the present application. Detailed Embodiments

[0108] The following is a further detailed description in conjunction with Figures 1 - 3 of the present application.

[0109] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0110] An embodiment of the present application provides a method for sharing and reusing video tags, which is executed by an electronic device. The electronic device can be a server or a terminal device. Among them, the server can be an independent physical server, a server cluster or a distributed device composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smart phone, a tablet computer, a notebook computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected through wired or wireless communication methods, and the embodiments of the present application do not limit this here.

[0111] Referring to Figure 1 , the method includes: step S101, step S102, step S103, step S104, step S105, and step S106, where:

[0112] Step S101: Obtain urban video image information, and divide the urban video image information to obtain multiple sub-image information.

[0113] Specifically, corresponding image acquisition devices are deployed in public places, such as roads, squares, and around construction units. At the same time, the image acquisition devices capture multi-source video streams according to administrative divisions and scene requirements to ensure coverage of key areas. After the electronic device obtains the urban video image information collected by the image acquisition devices. Subsequently, the electronic device divides the urban video images according to different video element information to obtain multiple sub-image information, and the electronic device will classify and store them according to the video element information corresponding to the sub-image information.

[0114] Step S102: Determine similar regions according to the sub-image information and preset standard image information.

[0115] Step S103: Determine the similarity of each similar region.

[0116] In the embodiment of the present application, the preset standard image is the standard image corresponding to the video element information.

[0117] Specifically, the electronic device performs image preprocessing on the sub-image information, performs noise elimination and distortion correction, and uses super-resolution reconstruction technology (such as a motion compensation algorithm based on consecutive low-resolution images) to improve image clarity and eliminate the interference of blurring on feature extraction; subsequently, the electronic device extracts features from the sub-image information and the preset standard image information, and performs feature matching; the electronic device determines the corresponding similar regions according to the successfully matched feature pairs by using deep learning methods; subsequently, the electronic device performs data statistics on the feature pairs and calculates the similarity of each similar region corresponding to the preset standard image information.

[0118] Step S104: If the similarity is greater than the preset similarity, determine the geomorphic features and objective environmental features of the similar region.

[0119] Specifically, the electronic device compares the similarity with the preset similarity. If the similarity is less than or equal to the preset similarity, it indicates that the sub-image information does not match the preset standard image information accurately. If the similarity is greater than the preset similarity, it indicates that the sub-image information matches the preset standard image information accurately at this time. Immediately, the electronic device analyzes and processes the urban video image information and the urban environmental information transmitted by the staff to determine the geomorphic features and objective environmental features of each similar region.

[0120] Step S105: Determine the shared tag information according to the geomorphic features and objective environmental features.

[0121] Specifically, when the image acquisition device performs image acquisition, the positioning device equipped in the image acquisition device will transmit the corresponding urban coordinate information to the electronic device. The electronic device integrates the corresponding urban coordinate information to determine the range corresponding to the urban coordinate information. Immediately, the electronic device extracts keywords according to the geomorphic features and urban coordinate information to determine the first keyword. At the same time, the electronic device extracts keywords from the objective environmental features to determine the second keyword. The electronic device compares the first keyword and the second keyword, analyzes the semantic association and overlapping part between the first keyword and the second keyword, and determines the common keyword. The electronic device matches the common keyword with the preset shared tag library to determine the shared tag information corresponding to the final common keyword.

[0122] Step S106: Determine the video tag information based on the shared tag information.

[0123] Specifically, the electronic device analyzes and processes the shared tag information, clarifies the tag theme and tag category represented by each shared tag information, and counts the quantity information and importance corresponding to each tag theme and tag category respectively, so as to determine which shared tag information in the shared tag information is dominant and set it as the target shared tag. Immediately, the electronic device determines the first tag information corresponding to the urban video image information according to the target shared tag. The electronic device verifies the first tag information to determine the accuracy and consistency corresponding to the first tag information. If the accuracy and consistency are respectively greater than the preset accuracy and preset consistency, the first tag information is set as the video tag information.

[0124] An embodiment of the present application provides a method for sharing and reusing video tags. After obtaining urban video image information, the urban video image information is divided to obtain multiple sub-image information, thereby improving the accuracy of image analysis. Then, the sub-image information is compared with preset standard image information to determine similar regions. After that, the similarity of the similar regions corresponding to the sub-image information and the preset standard image information is determined. The similarity is compared with a preset similarity. If the similarity is greater than the preset similarity, it means that the coincidence degree between the sub-image information and the preset standard image information is relatively high at this time. Then, the geomorphic features and objective environmental features corresponding to the similar regions are determined. The geomorphic features and objective environmental features are analyzed to determine common tag information. Then, according to the common tag information, video tag information is determined, thereby improving the accuracy of video tag sharing and reuse.

[0125] Dividing the urban video image information to obtain multiple sub-image information includes: determining video element information according to the urban video image information; determining element classification according to the video element information; determining an image division standard based on the element classification; and obtaining multiple sub-image information based on the image division standard.

[0126] Specifically, the electronic device extracts features from the urban video image information to determine all video element information corresponding to the urban video image information. Then, the electronic device classifies and arranges the obtained video element information, and stores the attributes corresponding to each video element information in categories, such as name, position (coordinate range in the image), size, color, texture, etc. Then, the electronic device determines the element classification according to the characteristics and analysis purposes corresponding to the video element information. The electronic device labels the element classification in the urban image information, takes the image boundary corresponding to each element classification as the division boundary, and sets it as the image division standard. Then, the electronic device divides the urban image information according to the image division standard, and sets the divided area as the sub-image information.

[0127] Determining a similar region according to the sub-image information and the preset standard image information includes: extracting features from the sub-image information to determine first feature information; extracting features from the preset standard image information to determine second feature information; determining first edge information and second edge information according to the sub-image information and the preset standard image information; calculating a similarity value between the first feature information and the second feature information; if the similarity value is greater than a preset similarity value, determining the coincidence degree between the first edge information and the second edge information; and if the coincidence degree is greater than a preset coincidence degree, determining the similar region.

[0128] Specifically, the electronic device extracts features from the preprocessed sub-image information and sets the feature information corresponding to the sub-image information as the first feature information. At the same time, after receiving the preset standard image transmitted by the staff, the electronic device extracts features from the preset standard image to determine the second feature information. Then, the electronic device extracts the edges of the sub-image information and the preset standard image information to determine the first edge information corresponding to the sub-image information and the second edge information corresponding to the preset standard image information. Subsequently, the electronic device uses the feature matching method to calculate the similarity between the first feature information and the second feature information. The electronic device compares the similarity value with the preset similarity value. If the similarity value is less than or equal to the preset similarity value, it indicates that the first feature information and the second feature information do not match at this time, which means that the sub-image information and the preset standard image information do not match. If the similarity value is greater than the preset similarity value, it indicates that the first feature information and the second feature information match successfully at this time, which means that the sub-image information and the preset standard image information match successfully. Then, the electronic device determines the degree of overlap between the first edge information and the second edge information by calculating the overlapping pixel point data of the first edge information and the second edge information after binarization processing. If the degree of overlap is less than or equal to the preset degree of overlap, it indicates that there is no matching and overlapping area between the sub-image information and the preset standard image information. If the degree of overlap is greater than the preset degree of overlap, it indicates that there is a corresponding overlapping area between the sub-image information and the preset standard image information. Then, the electronic device sets the overlapping area as the similar area.

[0129] Determine the geomorphic features and objective environmental features of the similar area, including: determining the urban geomorphic image according to the urban video image information; determining the geomorphic features based on the urban geomorphic image; obtaining the urban environmental information; determining the environmental elements according to the urban environmental information; and determining the objective environmental features based on the environmental elements.

[0130] In the embodiment of the present application, the urban environmental information includes meteorological information, environmental pollution information, ecological information, and hydrological environment information, and the environmental elements include climate elements, ecological elements, and pollution elements.

[0131] Specifically, the electronic device extracts the image features including the urban landform from the urban video image information, separates the part of the urban video image information containing the landform from other parts, such as buildings, pedestrians, etc. Then, the electronic device paints a 3D image of the part of the urban video image information containing the landform and sets it as the urban landform image; the electronic device uses the digital elevation model data to calculate the terrain parameters such as the slope, aspect, and elevation of the urban landform in the urban landform image. At the same time, the electronic device performs texture analysis on the urban landform image, and finally analyzes and determines the landform features; after receiving the urban environmental information transmitted by the staff, the electronic device performs element recognition on the urban environmental information and identifies the main environmental elements. For example, the climate elements include temperature, precipitation, sunlight, etc.; the ecological elements include vegetation types, biodiversity, etc.; the pollution elements include the pollutant concentration in the air and the pollutant content in the water; then, the electronic device defines and classifies each environmental element to clarify the environmental elements unique in the city. The electronic device performs statistical analysis on the environmental elements, analyzes statistical quantities such as their average values, standard deviations, and change trends, determines the objective environmental features, and transmits them to the display device in the form of charts and maps.

[0132] Determining the shared label information further included: obtaining the urban attribute information and the scene information; determining the classification criteria according to the urban attribute information and the scene information; determining the thematic label information according to the classification criteria; determining the label tree based on the thematic label information; establishing a preset shared label library according to the label tree.

[0133] In the embodiment of the present application, the historical urban database contains the urban attribute information and the scene information of the city in the past 5 years.

[0134] Specifically, after the electronic device obtains the urban attribute information and scenario information transmitted by the historical urban information database, the electronic device integrates and analyzes the urban attribute information and scenario information to determine the classification criteria for classifying the tags; then the electronic device determines each thematic tag information according to the classification criteria. The thematic tag information includes place tags, basic attribute tags, business tags, thematic tags, AI tags. The basic attribute tags can include the coding type, access mode, device type, etc. of the device. The place tags are divided into large categories such as administrative office, park, medical, life service, catering, etc. The thematic tags are divided into May Day holiday, education, smart construction site, forest fire prevention, flood control, etc.; the electronic device analyzes each thematic tag information to determine the logical relationship between each thematic tag information and builds a corresponding tag tree; the electronic device selects a suitable data storage structure to establish a preset shared tag library, such as a relational database (such as MySQL, Oracle) or a non-relational database (such as MongoDB). The electronic device designs the table structure or data model of the database according to the structure of the tag tree to ensure that it can store information such as the name, hierarchical relationship, and description of the tags; at the same time, the electronic device enters the thematic tag information in the tag tree into the preset shared tag library to establish the preset shared tag library.

[0135] According to the geomorphic features and objective environmental features, determine the common tag information, including: obtaining the urban coordinate information; determining the first keyword according to the geomorphic features and the urban coordinate information; determining the second keyword according to the objective environmental features; determining the common keyword according to the first keyword and the second keyword; determining the common tag information based on the common keyword and the preset shared tag library.

[0136] Specifically, after receiving the urban coordinate information transmitted by the geographic information system database, the electronic device combines the geomorphic features and the urban coordinate information to clarify the geographical location characteristics of the city, extracts keywords. For geomorphic features, if it is a mountainous area, keywords such as "mountain city", "surrounded by mountains", "hilly landform" can be extracted; if it is a plain, keywords such as "plain terrain", "vast plain" can be extracted. The electronic device screens the extracted keywords, removes keywords with repeated meanings, overly broad or lack of pertinence, and finally determines the first keyword that can accurately reflect the relationship between the urban geomorphology and coordinates. At the same time, the electronic device combines the specific geographical regions or landmarks involved in the coordinate information and adds relevant keywords, such as "city at the southern foot of [mountain name]", "plain city near [river name]", etc. Then the electronic device classifies the objective environmental characteristics in detail according to elements such as climate, vegetation, soil, and hydrology. For example, in terms of climate, analyze the temperature zone, precipitation pattern, seasonal changes, etc. of the city; in terms of vegetation, pay attention to the main vegetation types, vegetation coverage, etc. For each environmental element category, extract keywords that can reflect the uniqueness of the urban objective environment. In terms of climate, if the city belongs to the subtropical monsoon climate, keywords such as "subtropical monsoon climate", "humid climate", "distinct seasons" can be extracted; in terms of vegetation, if it is mainly evergreen broad-leaved forest, keywords such as "evergreen broad-leaved forest vegetation", "high forest coverage" can be extracted. The electronic device integrates the keywords extracted from each environmental element, screens them again, and removes the parts that are repeated or have weak relevance with the keywords of other elements to determine the final second keyword.

[0137] Furthermore, the electronic device uses a text matching algorithm to compare the first keyword with the second keyword, thereby measuring the similarity between the first keyword and the second keyword. Through comparison, find the keywords that exist in both the first keyword and the second keyword, and these keywords are the common keywords. For example, if there is "city along the river" in the first keyword set and "clear river water quality" in the second keyword set, then "river" can be used as a common keyword. In the preset shared tag library, the electronic device retrieves according to the common keywords. The preset shared tag library is a database table or data structure that stores various tags and their related information. The electronic device uses a database query statement (such as an SQL statement) or corresponding data operation methods to find the tags that match the common keywords. The electronic device determines the common tag information according to the matching results. During the matching process, the electronic device combines fuzzy matching in addition to precise matching. For example, if the common keyword is "river", tags with similar semantics such as "river course", "water system" can be found. For the multiple matched tags, they can be screened and sorted according to factors such as the weight of the tag, the usage frequency, and the degree of relevance with the common keyword, and finally determine the common tag information that can most accurately describe the urban characteristics.

[0138] Determine video tag information based on shared tag information, including: determine the tag theme and tag category based on the shared tag information; determine the target shared tag according to the tag theme and tag category; determine the first tag information according to the target shared tag; determine the accuracy corresponding to the first tag information; if the accuracy is greater than the preset accuracy, determine the first tag information as the video tag information.

[0139] Specifically, the electronic device performs text analysis on the shared tag information, extracts keywords and key phrases in the tags; uses clustering algorithms (such as K-Means clustering, hierarchical clustering) to cluster the shared tag information with similar semantics into different groups; the electronic device defines a clear name for the tag theme for each clustering group, and this name should be able to summarize the core content of the shared tag information in this group. At the same time, the electronic device further divides the theme into different categories according to the nature and characteristics of the tag theme and names them as tag categories; then the electronic device counts the quantity information and importance corresponding to each tag theme and tag category respectively, so as to determine which shared tag information in the shared tag information is dominant and sets it as the target shared tag; then, the electronic device analyzes the target shared tag, and according to the urban video image information, considers whether relevant tags need to be expanded or supplemented. The electronic device integrates the expanded and supplemented tags with the target shared tag, removes duplicate tags, and generates the first tag information; the electronic device compares the first tag information with the urban video image information to check whether each first tag information accurately reflects the actual content in the urban video image information, and determines the accuracy score for each tag. For example, if the first tag information is completely consistent with the content of the urban video image information, the score is 1; partially consistent, the score is between 0 and 1; inconsistent, the score is 0. Calculate the average accuracy score of all tags as the specific value of the accuracy of the first tag information; then the electronic device compares the accuracy with the preset accuracy. If the accuracy is greater than the preset accuracy, the electronic device sets the first tag information as the video tag information.

[0140] Refer to Figure 2 , the video tag sharing and reuse device 20 may specifically include: a sub-image information determination module 201, a similar area determination module 202, a similarity determination module 203, a feature determination module 204, a shared tag information determination module 205, and a video tag information determination module 206, where,

[0141] The sub-image information determination module 201 is used to obtain urban video image information and divide the urban video image information to obtain a plurality of sub-image information;

[0142] The similar area determination module 202 is used to determine a similar area according to the sub-image information and the preset standard image information;

[0143] A similarity determination module 203, configured to determine the similarity of each similar region;

[0144] A feature determination module 204, configured to determine the geomorphic features and objective environmental features of the similar region if the similarity is greater than a preset similarity;

[0145] A shared tag information determination module 205, configured to determine shared tag information according to the geomorphic features and objective environmental features;

[0146] A video tag information determination module 206, configured to determine video tag information based on the shared tag information.

[0147] In a possible implementation manner of the embodiment of the present application, the sub-image information determination module 201 includes: a video element information determination unit, an element classification determination unit, an image division criterion determination unit, and a sub-image information determination unit, where

[0148] The video element information determination unit is configured to determine video element information according to the urban video image information;

[0149] The element classification determination unit is configured to determine the element classification according to the video element information;

[0150] The image division criterion determination unit is configured to determine an image division criterion based on the element classification;

[0151] The sub-image information determination unit is configured to obtain a plurality of sub-image information based on the image division criterion.

[0152] In a possible implementation manner of the embodiment of the present application, the similar region determination module 202 includes: a first feature information determination unit, a second feature information determination unit, an edge information determination unit, a similarity value determination unit, a coincidence degree determination unit, and a similar region determination unit, where

[0153] The first feature information determination unit is configured to perform feature extraction on the sub-image information to determine first feature information;

[0154] The second feature information determination unit is configured to perform feature extraction on the preset standard image information to determine second feature information;

[0155] The edge information determination unit is configured to determine first edge information and second edge information according to the sub-image information and the preset standard image information;

[0156] The similarity value determination unit is configured to calculate a similarity value between the first feature information and the second feature information;

[0157] A coincidence degree determination unit, configured to determine the coincidence degree between the first edge information and the second edge information if the similarity value is greater than a preset similarity value;

[0158] A similar region determination unit, configured to determine a similar region if the coincidence degree is greater than a preset coincidence degree.

[0159] In a possible implementation manner of the embodiment of the present application, the feature determination module 204 includes: an urban landform image determination unit, a landform feature determination unit, an urban environment information acquisition unit, an environmental element determination unit, and an objective environment feature determination unit, where

[0160] The urban landform image determination unit is configured to determine an urban landform image according to urban video image information;

[0161] The landform feature determination unit is configured to determine landform features based on the urban landform image;

[0162] The urban environment information acquisition unit is configured to acquire urban environment information;

[0163] The environmental element determination unit is configured to determine environmental elements according to the urban environment information;

[0164] The objective environment feature determination unit is configured to determine objective environment features based on the environmental elements.

[0165] In a possible implementation manner of the embodiment of the present application, the video label sharing and reuse device 20 further includes: a first information acquisition module, a classification standard determination module, a special topic label information determination module, a label tree determination module, and a preset shared label library establishment module, where

[0166] The first information acquisition module is configured to acquire urban attribute information and scene information;

[0167] The classification standard determination module is configured to determine a classification standard according to the urban attribute information and the scene information;

[0168] The special topic label information determination module is configured to determine special topic label information according to the classification standard;

[0169] The label tree determination module is configured to determine a label tree based on the special topic label information;

[0170] The preset shared label library establishment module is configured to establish a preset shared label library according to the label tree.

[0171] In a possible implementation manner of the embodiment of the present application, the shared label information determination module 205 includes: an urban coordinate information acquisition unit, a first keyword determination unit, a second keyword determination unit, a common keyword determination unit, and a common label information determination unit, where

[0172] An urban coordinate information acquisition unit for acquiring urban coordinate information;

[0173] A first keyword determination unit for determining a first keyword according to the geomorphic features and urban coordinate information;

[0174] A second keyword determination unit for determining a second keyword according to the objective environmental features;

[0175] A common keyword determination unit for determining common keywords according to the first keyword and the second keyword;

[0176] A common label information determination unit for determining common label information based on the common keywords and a preset shared label library.

[0177] A possible implementation manner of the embodiment of the present application, the video label information determination module 206 includes: a label theme determination unit, a target common label determination unit, a first label information determination unit, an accuracy determination unit, and a video label information determination unit, where

[0178] The label theme determination unit is used to determine the label theme and label category based on the common label information;

[0179] The target common label determination unit is used to determine the target common label according to the label theme and label category;

[0180] The first label information determination unit is used to determine the first label information according to the target common label;

[0181] The accuracy determination unit is used to determine the accuracy corresponding to the first label information;

[0182] The video label information determination unit is used to determine the first label information as the video label information if the accuracy is greater than the preset accuracy.

[0183] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0184] The embodiment of the present application also introduces an electronic device from the perspective of an entity device, such as Figure 3 shown Figure 3 The electronic device 30 shown includes: a processor 301 and a memory 303. Among them, the processor 301 and the memory 303 are connected, such as connected through a bus 302. Optionally, the electronic device 30 may further include a transceiver 304. It should be noted that in actual applications, the transceiver 304 is not limited to one, and the structure of the electronic device 30 does not constitute a limitation to the embodiment of the present application.

[0185] The processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute various exemplary logical blocks, modules, and circuits described in connection with the disclosure of this application. The processor 301 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0186] The bus 302 may include a path for transmitting information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For the sake of representation, Figure 3 only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.

[0187] The memory 303 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or it may also be an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0188] The memory 303 is used to store the application program code for executing the solution of this application, and is controlled by the processor 301 for execution. The processor 301 is used to execute the application program code stored in the memory 303 to implement the content shown in the foregoing method embodiments.

[0189] Among them, the electronic device includes but is not limited to: mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Tablet Computers), PMPs (Portable Multimedia Players), in-vehicle terminals (such as in-vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. It can also be a server, etc. Figure 3 The illustrated electronic device is only an example and should not impose any limitations on the functions and usage scope of the embodiments of this application.

[0190] It should be understood that although each step in the flowchart of the accompanying drawings is shown sequentially according to the indication of the arrows, these steps do not necessarily have to be executed sequentially according to the order indicated by the arrows. Unless clearly stated in this article, the execution of these steps has no strict order limit and can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages. These sub-steps or stages do not necessarily have to be executed at the same moment, but can be executed at different moments, and their execution order does not necessarily have to be sequential, but can be executed alternately or in turn with at least a part of other steps or sub-steps or stages of other steps.

[0191] The above are only some implementation manners of this application. It should be noted that for those of ordinary skill in the art in this technical field, without departing from the principle of this application, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of this application.

Claims

1. A video tag sharing and multiplexing method, characterized in that: include: Acquire city video image information, and divide the city video image information to obtain a plurality of sub-image information; Determining a similar area according to the sub-image information and preset standard image information; Determining the similarity of each similar region; If the similarity is greater than a preset similarity, determining the geomorphic features and objective environmental features of the similar area; Determining shared tag information according to the geomorphic features and the objective environmental features; Determining video tag information based on the shared tag information; The determining of the shared tag information also includes: Obtain city attribute information and scene information; Determining a classification standard according to the city attribute information and the scene information; Determine topic label information according to the classification standard; Based on the topic tag information, determine a tag tree; According to the tag tree, a preset shared tag library is established; The determining of the common tag information according to the geomorphic features and the objective environmental features includes: Get city coordinate information; Determining a first keyword according to the geomorphic features and the city coordinate information; Determining a second keyword according to the objective environmental characteristics; Determine a common keyword according to the first keyword and the second keyword; Determining the shared tag information based on the shared keywords and the preset shared tag library; The determining of the video tag information based on the common tag information includes: Based on the shared tag information, determining a tag theme and a tag category; Determine a target shared tag according to the tag subject and the tag category; Determining first tag information according to the target common tag; Determining the accuracy of the first tag information; If the accuracy is greater than the preset accuracy, it is determined that the first tag information is the video tag information.

2. A video tag sharing and multiplexing method according to claim 1, characterized in that: The city video image information is divided to obtain a plurality of sub-image information, including: Determining video element information according to the city video image information; Determining element classification according to the video element information; Based on the element classification, determining an image division standard; Based on the image division standard, the plurality of sub-image information is obtained.

3. A video tag sharing and multiplexing method according to claim 1, characterized in that: The determining of the similar area according to the sub-image information and the preset standard image information includes: Extracting features from the sub-image information to determine first feature information; Extracting features from the preset standard image information to determine second feature information; Determining first edge information and second edge information according to the sub-image information and the preset standard image information; Calculating a similarity value between the first feature information and the second feature information; If the similarity value is greater than a preset similarity value, determining the degree of overlap between the first edge information and the second edge information; If the degree of overlap is greater than a preset degree of overlap, the similar area is determined.

4. A video tag sharing and multiplexing method according to claim 1, characterized in that: The determining of the geomorphic features and objective environmental features of the similar area includes: Determining a city landform image according to the city video image information; Determining the landform features based on the urban landform image; Obtain urban environmental information; Determining environmental factors according to the urban environmental information; Based on the environmental factors, the objective environmental characteristics are determined.

5. A video tag sharing and multiplexing device, characterized in that: include: A sub-image information determination module is used to obtain city video image information, divide the city video image information, and obtain a plurality of sub-image information; A similar region determination module, used to determine a similar region based on the sub-image information and preset standard image information; A similarity determination module, used to determine the similarity of each similar region; A feature determination module, configured to determine the geomorphic features and objective environmental features of the similar area if the similarity is greater than a preset similarity; A common tag information determination module, used to determine the common tag information according to the landform features and the objective environment features; A video tag information determination module, used to determine the video tag information based on the common tag information; The first information acquisition module is used to acquire city attribute information and scene information; A classification standard determination module, used to determine a classification standard according to the city attribute information and the scene information; A topic label information determination module, used to determine the topic label information according to the classification standard; A tag tree determination module, used to determine a tag tree based on the topic tag information; A preset shared tag library establishment module, used to establish a preset shared tag library according to the tag tree; A city coordinate information acquisition unit, used to acquire city coordinate information; A first keyword determining unit, configured to determine a first keyword according to the geomorphic features and the city coordinate information; A second keyword determining unit, configured to determine a second keyword according to the objective environment feature; a common keyword determining unit, configured to determine a common keyword according to the first keyword and the second keyword; A shared tag information determining unit, configured to determine the shared tag information based on the shared keywords and the preset shared tag library; A tag theme determination unit, configured to determine a tag theme and a tag category based on the shared tag information; a target common tag determining unit, configured to determine a target common tag according to the tag subject and the tag category; A first label information determining unit, configured to determine first label information according to the target common label; an accuracy determination unit, configured to determine the accuracy corresponding to the first tag information; The video tag information determining unit is configured to determine that the first tag information is the video tag information if the accuracy is greater than a preset accuracy.

6. An electronic device, characterized in that: The electronic device includes: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute a video tag sharing and multiplexing method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed in a computer, the computer is caused to execute the video tag sharing and multiplexing method according to any one of claims 1 to 4.

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