Artwork feature point identification system and method based on geographic information
The system dynamically adjusts art feature point presentation using GPS and image recognition, addressing fixed presentation issues by incorporating user feedback and cultural relevance, enhancing user interaction and immersion.
Patent Information
- Application Number
- CN202510814334.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-18
- Publication Date
- 2025-07-15
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
The existing technology cannot effectively display the characteristic points of artworks in combination with urban maps, resulting in fixed displays, difficult to reflect user interests and real-time changes, and lack of multi-dimensional identification methods.
The artwork feature point recognition system based on geographic information is adopted to obtain data through high-precision GPS and cameras, combine image recognition models and feature adjustment formulas to dynamically adjust the display order of artwork feature points, and use factors such as the number of comments, time intervals and spatial density to make weight corrections.
It realizes the dynamic display of the characteristic points of the artwork, enhances user interaction and cultural immersion, provides accurate interpretation of the characteristic points and peripheral recommendations, and promotes the dissemination and protection of urban artworks.
Smart Images
Figure CN120316149A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of art display, and particularly to an art feature point recognition system and method based on geographic information. Background Art
[0002] With the acceleration of the urbanization process, public environmental artworks, as an important part of urban culture, not only beautify the urban space but also enrich the spiritual life of citizens. However, these artworks are widely distributed and diverse in form, lacking effective digital management and recognition means, resulting in the difficulty of systematically recording, querying, and sharing artwork information. With the continuous development of urban cultural tourism and public art, a large number of artworks with historical value, artistic value, and cultural connotations (such as sculptures, murals, installation art, etc.) have emerged in urban maps. The traditional ways of obtaining artwork information mainly rely on static exhibitions, guidebooks, or online web introductions, which cannot highlight the urban characteristics in combination with the urban map. At the same time, when displaying the feature points of artworks, the fixed order of feature point display is prevented, and the inability to dynamically adjust leads to the disadvantage of being difficult to arouse user interest. Finally, most existing artwork recognition methods rely on a single image recognition model, ignoring the multi-dimensional influencing factors such as comment popularity, timeliness, cultural cycle, and spatial aggregation degree, resulting in the difficulty of reflecting user interests and real-time changes in the feature point ranking and recommendation results, and facilitating the binding recognition effect of users on cities and artworks. Summary of the Invention
[0003] In order to overcome the drawback of the fixation in the display of artwork feature points, the present invention provides an art feature point recognition system and method based on geographic information.
[0004] The technical implementation scheme of the present invention is: an art feature point recognition system based on geographic information, comprising: A first data acquisition module, configured to acquire image data of a target artwork, target artwork information of the location of the target artwork, and surrounding artwork information of the surrounding area of the target artwork; An image recognition module, configured to perform feature point recognition on the image data of the target artwork using an artwork feature recognition model to obtain the feature points of the target artwork; An adjustment value acquisition module, configured to obtain adjustment values of each artwork feature point using a feature adjustment formula according to the target artwork information and the surrounding artwork information; An intermediate value adjustment module, configured to obtain the intermediate value of the feature adjustment formula using a dynamic intermediate value adjustment formula according to the comment adjustment data; A feature point adjustment module, configured to perform sorting adjustment and then description and explanation on the artwork feature points in the urban map according to the adjustment values of the artwork feature points; The second data acquisition module is used to obtain the art object feature data in the surrounding area according to the ranking of art object feature points; The recommendation adjustment module is used to obtain the recommendation degree of each surrounding area by using the recommendation degree adjustment formula according to the art object feature data in the surrounding area; The feature point description module is used to improve the explanation of the main feature points of the target art object according to the recommendation degree of each surrounding area.
[0005] Preferably, the first data acquisition module is used to obtain the image data of the target art object, the target art object information at the location of the target art object, and the surrounding art object information in the surrounding area of the target art object, including: using the high-precision GPS and camera carried by the mobile device to obtain the image data of the target art object, the target art object information at the location of the target art object, and the surrounding art object information in the surrounding area of the target art object, where the target art object information includes the feature points of the target art object and the number of comments on each feature point of the target art object, and the surrounding art object information includes the feature points of the art objects in the surrounding area and the number of comments on each feature point; establishing an art object database by storing the art object information contributed by users, and obtaining the number of comments on each feature point of the target art object and the number of comments on each feature point of the art objects in the surrounding area from the art object database.
[0006] Preferably, the image recognition module is used to perform feature point recognition on the image data of the target art object by using the art object feature recognition model to obtain the feature points of the target art object, including: inputting the image data of the target art object into the trained art object feature recognition model to obtain the feature points of the target art object, where the trained art object feature recognition model is obtained by preprocessing the historical target art object images and then inputting them into the CNN model for training to obtain an art object feature recognition model capable of recognizing each feature point of the art object, and the image preprocessing includes preprocessing of image enhancement.
[0007] Preferably, the adjustment value acquisition module is used to obtain the adjustment value of each art object feature point by using the feature adjustment formula according to the target art object information and the surrounding art object information, including: the feature adjustment formula is: ; In the formula, is the adjustment value of the art object feature point; is the adjustment coefficient of the feature adjustment formula; is the number of comments on the art object feature point; is the intermediate value of the feature adjustment formula.
[0008] Preferably, the intermediate value adjustment module is used to obtain the intermediate value of the feature adjustment formula according to the comment adjustment data using a dynamic intermediate value adjustment formula, including: the comment adjustment data includes the time interval since the last annotation of the art feature point, the time interval between the current actual time point and the cultural time, the cultural time period of the art feature point, the density of the art feature points in the surrounding area corresponding to the target art feature point, and the maximum density threshold of the art feature points in the surrounding area, where the time interval since the last annotation of the art feature point is the time interval after each art feature point was last commented by the user; the cultural time period of the art feature point is the time interval period related to the festival art feature points, and the dynamic intermediate value adjustment formula is: ; In the formula, is the intermediate value of the feature adjustment formula; is the weight adjustment coefficient; is the time interval since the last annotation of the art feature point; is the time interval between the current actual time point and the cultural time; is the cultural time period of the art feature point; is the density of the art feature points in the surrounding area corresponding to the target art feature point; is the maximum density threshold of the art feature points in the surrounding area.
[0009] Preferably, the feature point adjustment module is used to sort and adjust the art feature points in the city map according to the adjustment value of the art feature points and then describe and explain, including: combining the art feature points with spatial coordinates, mapping the art feature points to the city map, sorting the display order of the art feature points according to the adjustment value of the art feature points to obtain the ranking of the art feature points, dividing the ranking of the art feature points to obtain the main feature points and the auxiliary feature points, the main feature points being the feature points with the highest ranking, and the auxiliary feature points being the remaining ranked feature points, and describing and explaining the art feature points according to the ranking of the art feature points.
[0010] Preferably, the second data acquisition module is used to obtain the art feature data in the surrounding area according to the ranking of the art feature points, including: the art feature data in the surrounding area includes the associated feature points of the art in each surrounding area, the ranking of the art feature points in each surrounding area, and the distance between each surrounding area and the location of the target art, where the associated feature points of the art in the surrounding area are the feature points with a correlation greater than or equal to the preset threshold between the art feature points in the surrounding area and the main feature points of the target art; the ranking of the art feature points in each surrounding area is the ranking of the associated feature points of the art in the surrounding area.
[0011] Preferably, the recommendation adjustment module is configured to use a recommendation degree adjustment formula based on the art object feature data of the surrounding areas to obtain the recommendation degrees of the surrounding areas, including: The recommendation degree adjustment formula is: ; In the formula, is the recommendation degree of the surrounding area; is the weight adjustment coefficient of the recommendation adjustment formula; is the ranking of the art object feature points in the surrounding area; is the distance between the surrounding area and the location of the target art object; is the urban scale parameter; is the cosine similarity between the target art object and the art objects in the surrounding area based on the CNN feature vectors.
[0012] Preferably, the feature point description module is configured to improve the explanation of the main feature points of the target art object according to the recommendation degrees of the surrounding areas, including: generating a recommendation linked list after sorting according to the recommendation degrees of the surrounding areas, where the recommendation linked list is used to recommend the surrounding areas after explaining the main feature points of the art object, and adding the recommendation linked list to the explanation of the main feature points of the target art object for recommendation.
[0013] Preferably, a method for identifying art object feature points based on geographic information further includes: S1: Obtain the image data of the target art object, the target art object information of the location of the target art object, and the surrounding art object information of the surrounding areas of the target art object; S2: Use a feature adjustment formula to obtain the adjustment values of the art object feature points according to the target art object information and the surrounding art object information; S3: Sort and adjust the art object feature points in the city map according to the adjustment values of the art object feature points and then describe and explain them; S4: Obtain the art object feature data of the surrounding areas according to the art object feature point rankings; S5: Use a recommendation degree adjustment formula based on the art object feature data of the surrounding areas to obtain the recommendation degrees of the surrounding areas; S6: Improve the explanation of the main feature points of the target art object according to the recommendation degrees of the surrounding areas.
[0014] The beneficial effects are: 1. The present invention dynamically adjusts the priority order when displaying art object feature points in combination with the city map through a feature adjustment formula, effectively solving the problem of the fixed display of art object feature points, and at the same time solving the problem of recommending art object feature points of the surrounding areas for the target art object; 2. Through the dynamic intermediate value adjustment formula, the weights of feature points are dynamically corrected by integrating time interval, cultural cycle, and spatial density. The improved idea of the HRRN algorithm is combined to make the display data of feature points more diverse dynamically; 3. When users use the city map for art tour guide, they can obtain accurate explanations of feature points and recommendations of surrounding feature points, which deepens users' understanding of feature points and related feature points derived from feature points, enhances interactivity and cultural immersion, and contributes to the dissemination and protection of urban artworks. BRIEF DESCRIPTION OF THE DRAWINGS
[0015] Figure 1 It is a schematic structural diagram of the art feature point recognition system based on geographic information of the present invention; Figure 2 It is a flowchart of the art feature point recognition method based on geographic information of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS
[0016] The above solution will be further described below in conjunction with specific embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the present application. The implementation conditions adopted in the embodiments can be further adjusted according to the conditions of specific manufacturers, and the implementation conditions not specified are usually those in conventional experiments.
[0017] Embodiment 1: An art feature point recognition system based on geographic information, as Figure 1 shown, includes: The first data acquisition module is used to acquire the image data of the target artwork, the target artwork information of the location of the target artwork, and the surrounding artwork information of the surrounding area of the target artwork; Using the high-precision GPS and camera carried by the mobile device, the image data of the target artwork, the target artwork information of the location of the target artwork, and the surrounding artwork information of the surrounding area of the target artwork are acquired. The target artwork information includes the feature points of the target artwork and the number of comments on each feature point of the target artwork, and the surrounding artwork information includes the feature points of the artworks in the surrounding area and the number of comments on each feature point; The artwork database is established by storing the artwork information contributed by users, and the number of comments on each feature point of the target artwork and the number of comments on each feature point of the artworks in the surrounding area are obtained from the artwork database.
[0018] It should be further explained that on a mobile terminal (such as a smartphone or a tablet), a high-precision GPS module and a high-definition camera are integrated. The GPS module is used to obtain the longitude and latitude information of the current device, and the camera is used to collect image data of the target artwork and its surrounding environment. After the user starts the application, the first data acquisition module calls the camera to take multiple frames of images of the target artwork at a preset resolution, and automatically selects several frames with clear pixels and the least distortion as the "image data of the target artwork" and stores them in the local cache. Using the geographical coordinates obtained by the GPS, it requests the artwork information at this coordinate from the backend server, including the artwork ID, name, and address. At the same time, it retrieves the corresponding records from the artwork database to obtain the identifiers of the characteristic points of the artwork and the "number of comments" attribute. Taking the coordinates of the target artwork as the center and a set radius, it queries all the artwork records in the surrounding area from the database. For each surrounding artwork, it reads its list of characteristic points and the corresponding number of comments to form a set of surrounding artwork information. The backend regularly or in real time uploads the characteristic point annotations and comments of the artworks submitted by the user through the client to the cloud and merges these data into the artwork database. Through interface calls, it directly obtains the "number of comments of each characteristic point of the target artwork" and the "number of comments of each characteristic point of the surrounding artworks" to ensure the timeliness and integrity of the data.
[0019] An image recognition module, which is used to perform feature point recognition on the image data of the target artwork using an artwork feature recognition model to obtain the characteristic points of the target artwork; Input the image data of the target artwork into the trained artwork feature recognition model to obtain the characteristic points of the target artwork. The trained artwork feature recognition model is obtained by preprocessing the historical target artwork images and then inputting them into the CNN model for training to obtain an artwork feature recognition model that can recognize the characteristic points of the artwork. The image preprocessing includes preprocessing of image enhancement.
[0020] It should be further explained that the image enhancement operation includes denoising: using median filtering or Gaussian filtering algorithms to remove the shooting noise; color correction: using the white balance algorithm to restore the color of the image; contrast enhancement: improving the image detail contrast based on histogram equalization; collecting several thousand representative historical target artwork images and manually annotating their characteristic points; inputting the preprocessed images and the corresponding annotation coordinates into the CNN model; using the cross-entropy loss or regression loss function to iteratively optimize the model parameters until the localization error of the validation set is lower than the preset threshold to obtain an artwork feature recognition model that can recognize the characteristic points of the artwork.
[0021] An adjustment value acquisition module, which is used to obtain the adjustment values of the characteristic points of each artwork using a feature adjustment formula according to the target artwork information and the surrounding artwork information; The feature adjustment formula is as follows: ; In the formula, is the adjustment value of the art feature point; is the adjustment coefficient of the feature adjustment formula; is the number of comments on the art feature point; is the intermediate value of the feature adjustment formula.
[0022] It should be further explained that the adjustment value acquisition module receives the input data from the first data acquisition module and the image recognition module, including the number of comments on each art feature point; the intermediate value of each art feature point (provided by the intermediate value adjustment module); the preset adjustment coefficient is obtained based on historical experience and experiments.
[0023] The intermediate value adjustment module is used to obtain the intermediate value of the feature adjustment formula by using the dynamic intermediate value adjustment formula according to the comment adjustment data; The comment adjustment data includes the time interval since the art feature point was last labeled, the time interval between the current actual time point and the cultural time, the cultural time period of the art feature point, the density of the art feature points in the surrounding area corresponding to the target art feature point, and the maximum density threshold of the art feature points in the surrounding area. Among them, the time interval since the art feature point was last labeled is the time interval after each art feature point was last commented by the user; the cultural time period of the art feature point is the interval time period related to festivals. The dynamic intermediate value adjustment formula is as follows: ; In the formula, is the intermediate value of the feature adjustment formula; is the weight adjustment coefficient; is the time interval since the art feature point was last labeled; is the time interval between the current actual time point and the cultural time; is the cultural time period of the art feature point; is the density of the art feature points in the surrounding area corresponding to the target art feature point; is the maximum density threshold of the art feature points in the surrounding area.
[0024] It should be further explained that the intermediate value adjustment module obtains the following raw data from the database and the real-time interface: the time interval since each art feature point was last labeled, the time interval between the current actual time point and the cultural time, the cultural time period corresponding to each feature point (for example: the Spring Festival-related feature point period is 365 days), the density of the art feature points in the surrounding area corresponding to the target art feature point, and the preset maximum density threshold for normalization processing; in the formula For increasing the display of each feature point of the art work, For reflecting the adjustment of the intermediate value at different time points within the cultural cycle, so that the display of the art work feature points adapts to the user's festival needs, and it can also combine the unique festival needs of the user itself, such as the personalized user culture needs on the wedding anniversary; For combining the feature points of the art works prevailing in the surrounding area, so that the display order of the art work feature points is more automated and intelligent.
[0025] The feature point adjustment module is used to sort and adjust the art work feature points in the city map according to the adjustment value of the art work feature points and then describe and explain; Combine the art work feature points with the spatial coordinates, map the art work feature points to the city map, sort the display order of the art work feature points according to the adjustment value of the art work feature points to obtain the art work feature point ranking, divide the art work feature point ranking to obtain the main feature points and the auxiliary feature points, the main feature points are the feature points with the highest ranking, and the auxiliary feature points are the feature points of the remaining rankings, and describe and explain the art work feature points according to the art work feature point ranking.
[0026] It should be further explained that combining the art work feature points with the spatial coordinates can enable the user to display the corresponding art work feature points according to the aiming of the spatial geographical position, sort all the feature points from large to small according to the adjustment value, generate the art work feature point ranking, that is, the art work feature point ranking list, and the sorting algorithm adopts quick sort, merge sort or the built-in database sorting function to ensure the efficiency of large-scale feature point sorting; mark several feature points with the highest scores in the ranking list as the main feature points, and mark the feature points in the remaining positions as the auxiliary feature points; according to the ranking list, generate a literal description for each main feature point, and use secondary explanations for the auxiliary feature points; it should be explained that in this embodiment, for a selected art work, the display of multiple feature points of the art work is carried out.
[0027] The second data acquisition module is used to acquire the art work feature data in the surrounding area according to the art work feature point ranking; The art work feature data in the surrounding area includes the associated feature points of the art works in each surrounding area, the rankings of the art work feature points in each surrounding area, and the distances between each surrounding area and the location of the target art work, where the associated feature points of the art works in the surrounding area are the feature points whose correlation between the art work feature points in the surrounding area and the main feature points of the target art work is greater than or equal to the preset threshold; the rankings of the art work feature points in each surrounding area are the rankings of the associated feature points of the art works in the surrounding area.
[0028] It should be further explained that with the location of the target artwork as the center, a radius is set to obtain all the artwork records in the surrounding area, and the feature points and their ranking information of these surrounding artworks are retrieved from the artwork database; for each feature point of each surrounding artwork, the correlation index between it and each main feature point of the target artwork is calculated, and the feature points with a correlation greater than or equal to the preset threshold are identified as the associated feature points of the artworks in the surrounding area. For the above-mentioned associated feature points, they are sorted again according to their adjustment values or comment numbers within the surrounding artworks to obtain the rankings of the feature points of each surrounding area artwork; at the same time, the actual geographical distance between the location of each surrounding artwork and the location of the target artwork is calculated.
[0029] A recommendation adjustment module, which is used to use the recommendation adjustment formula according to the feature data of the artworks in the surrounding area to obtain the recommendation degrees of each surrounding area; The recommendation adjustment formula is: ; In the formula, is the recommendation degree of the surrounding area; is the weight adjustment coefficient of the recommendation adjustment formula; is the ranking of the feature points of the artworks in the surrounding area; is the distance between the surrounding area and the location of the target artwork; is the urban scale parameter; is the cosine similarity between the target artwork and the artworks in the surrounding area based on the CNN feature vector.
[0030] It should be further explained that the recommendation adjustment module first receives the feature data of the artworks in the surrounding area output by the second data acquisition module, including the ranking of each associated feature point of the artworks in the surrounding area, the distance between the surrounding area and the location of the target artwork, and the style similarity calculated based on the CNN feature vector. In the formula reflects that the higher the ranking, the higher the recommendation degree; reflects that the closer the distance, the higher the recommendation degree; reflects that the higher the style similarity, the higher the recommendation degree.
[0031] A feature point description module, which is used to improve the explanation of the main feature points of the target artwork according to the recommendation degrees of each surrounding area.
[0032] After sorting according to the recommendation degrees of each surrounding area, a recommendation linked list is generated. The recommendation linked list is used to recommend the surrounding area after explaining the main feature points of the artwork, and the recommendation linked list is added to the explanation of the main feature points of the target artwork for recommendation.
[0033] It should be further explained that all the artworks in the surrounding areas are sorted from the highest to the lowest in terms of their recommendation degrees to form an ordered list, which is used to form a recommended linked list. The recommended linked list is added to the explanation of the main feature points of the target artwork for recommendation. Based on the dynamic recommendation of the artwork feature points, users can understand the origin and dissemination path of the artwork feature points, and at the same time, users can understand the knowledge content of the derivative feature points of the artwork feature points, enhancing the user experience.
[0034] Embodiment 2: On the basis of Embodiment 1, a method for identifying the feature points of artworks based on geographical information, as Figure 2 shown, further includes: S1: Obtain the image data of the target artwork, the target artwork information of the location of the target artwork, and the surrounding artwork information of the surrounding area of the target artwork; S2: According to the target artwork information and the surrounding artwork information, use the feature adjustment formula to obtain the adjustment values of the feature points of each artwork; S3: After sorting and adjusting the feature points of the artworks in the city map according to the adjustment values of the feature points of the artworks, describe and explain them; S4: According to the ranking of the feature points of the artworks, obtain the feature data of the artworks in the surrounding area; S5: According to the feature data of the artworks in the surrounding area, use the recommendation degree adjustment formula to obtain the recommendation degrees of each surrounding area; S6: Improve the explanation of the main feature points of the target artwork according to the recommendation degrees of each surrounding area.
[0035] The above embodiments are only the preferred embodiments of the present invention and are not used to limit the scope of implementation of the present invention. Therefore, all equivalent changes made according to the content described in the claims of the present invention should be included within the scope of the claims of the present invention.
Claims
1. An art feature point recognition system based on geographic information, characterized in that Including: A first data acquisition module, configured to acquire image data of a target artwork, target artwork information of the location of the target artwork, and surrounding artwork information of the surrounding area of the target artwork; An image recognition module, configured to perform feature point recognition on the image data of the target artwork using an artwork feature recognition model to obtain feature points of the target artwork; An adjustment value acquisition module, configured to use a feature adjustment formula to obtain adjustment values of each artwork feature point according to the target artwork information and the surrounding artwork information; An intermediate value adjustment module, configured to obtain an intermediate value of the feature adjustment formula according to the comment adjustment data using a dynamic intermediate value adjustment formula; A feature point adjustment module, configured to perform sorting adjustment and then description and explanation on the artwork feature points in the city map according to the adjustment values of the artwork feature points; A second data acquisition module, configured to acquire surrounding area artwork feature data according to the ranking of the artwork feature points; A recommendation adjustment module, configured to use a recommendation degree adjustment formula according to the surrounding area artwork feature data to obtain the recommendation degree of each surrounding area; A feature point description module, configured to perform a complete explanation on the main feature points of the target artwork according to the recommendation degree of each surrounding area.
2. The art feature point recognition system based on geographic information according to claim 1, characterized in that The first data acquisition module, configured to acquire image data of a target artwork, target artwork information of the location of the target artwork, and surrounding artwork information of the surrounding area of the target artwork, including: using the high-precision GPS and camera carried by a mobile device to acquire image data of the target artwork, target artwork information of the location of the target artwork, and surrounding artwork information of the surrounding area of the target artwork, where the target artwork information includes feature points of the target artwork and the number of comments on each feature point of the target artwork, and the surrounding artwork information includes feature points of the surrounding area artworks and the number of comments on each feature point; establishing an artwork database by storing the artwork information contributed by users, and obtaining the number of comments on each feature point of the target artwork and the number of comments on each feature point of the surrounding area artworks from the artwork database.
3. The feature of an art feature point recognition system based on geographic information as described in claim 2 is that, The image recognition module, configured to perform feature point recognition on the image data of the target artwork using an artwork feature recognition model to obtain feature points of the target artwork, including: inputting the image data of the target artwork into a trained artwork feature recognition model to obtain feature points of the target artwork, where the trained artwork feature recognition model is obtained by preprocessing the historical target artwork images and then inputting them into a CNN model for training to obtain an artwork feature recognition model capable of recognizing each feature point of the artwork, and the image preprocessing includes preprocessing of image enhancement.
4. The art feature point recognition system based on geographic information according to claim 1, characterized in that, The adjustment value acquisition module, configured to use a feature adjustment formula to obtain adjustment values of each artwork feature point according to the target artwork information and the surrounding artwork information, including: The feature adjustment formula is: ； Wherein, is the adjustment value of the art feature points; is the adjustment coefficient of the feature adjustment formula; is the number of comments on the art feature points; is the intermediate value of the feature adjustment formula.
5. The art feature point recognition system based on geographic information according to claim 4, characterized in that, The intermediate value adjustment module is used to obtain the intermediate value of the feature adjustment formula by adjusting the data according to the comments using a dynamic intermediate value adjustment formula, including: the comment adjustment data includes the time interval since the last annotation of the art feature points, the time interval between the current actual time point and the cultural time, the cultural time period of the art feature points, the density of the art feature points in the surrounding area corresponding to the target art feature points, and the maximum density threshold of the art feature points in the surrounding area, where the time interval since the last annotation of the art feature points is the time interval after the last user comment on each art feature point; the cultural time period of the art feature points is the time interval period related to festivals for the art feature points related to festivals, and the dynamic intermediate value adjustment formula is: ； In the formula, is the intermediate value of the feature adjustment formula; is the weight adjustment coefficient; is the time interval since the last annotation of the art feature point; is the time interval between the current actual time point and the cultural time; is the cultural time period of the art feature point; is the density of the art feature points in the surrounding area corresponding to the target art feature point; is the maximum density threshold of the art feature points in the surrounding area.
6. The feature of an art feature point recognition system based on geographic information as described in claim 1 is that, The feature point adjustment module is used to sort, adjust, describe, and explain the art feature points in the city map according to the adjustment values of the art feature points, including: combining the art feature points with spatial coordinates, mapping the art feature points to the city map, sorting the display order of the art feature points according to the adjustment values of the art feature points to obtain the art feature point rankings, dividing the art feature point rankings to obtain main feature points and auxiliary feature points, where the main feature points are the feature points with the highest rankings, and the auxiliary feature points are the remaining ranked feature points, and describing and explaining the art feature points according to the art feature point rankings.
7. The feature of an art feature point recognition system based on geographic information as described in claim 1 is that, The second data acquisition module is used to obtain the art feature data of the surrounding area according to the art feature point rankings, including: the art feature data of the surrounding area includes the associated feature points of the art in each surrounding area, the rankings of the art feature points in each surrounding area, and the distances between each surrounding area and the location of the target art. Among them, the associated feature points of the art in the surrounding area are the feature points with a correlation greater than or equal to the preset threshold between the art feature points in the surrounding area and the main feature points of the target art; the rankings of the art feature points in each surrounding area are the rankings of the associated feature points of the art in the surrounding area.
8. The feature of an art feature point recognition system based on geographic information as described in claim 7 is that, The recommendation adjustment module is used to obtain the recommendation degrees of each surrounding area by using a recommendation degree adjustment formula according to the art feature data of the surrounding area, including: the recommendation degree adjustment formula is: ； In the formula, is the recommendation degree of the surrounding area; is the weight adjustment coefficient of the recommendation adjustment formula; is the ranking of the characteristic points of the artworks in the surrounding area; is the distance between the surrounding area and the location of the target artwork; is the urban scale parameter; is the cosine similarity between the target artwork and the artworks in the surrounding area based on the CNN feature vector.
9. The feature of an art feature point recognition system based on geographic information as described in claim 1 is that, The feature point description module is used to improve the explanation of the main feature points of the target art according to the recommendation degrees of each surrounding area, including: generating a recommendation linked list after sorting according to the recommendation degrees of each surrounding area, where the recommendation linked list is used to recommend the surrounding area after explaining the main feature points of the art, and adding the recommendation linked list to the explanation of the main feature points of the target art for recommendation.
10. A method for identifying feature points of artworks based on geographic information, a system for identifying feature points of artworks based on geographic information according to any one of claims 1-9, characterized in that it further Including: S1: Obtain the image data of the target art, the target art information of the location of the target art, and the surrounding art information of the surrounding area of the target art; S2: According to the target art information and the surrounding art information, use the feature adjustment formula to obtain the adjustment values of each art feature point; S3: Sort, adjust, describe, and explain the art feature points in the city map according to the adjustment values of the art feature points; S4: Obtain the art feature data of the surrounding area according to the art feature point rankings; S5: Obtain the recommendation degrees of each surrounding area by using the recommendation degree adjustment formula based on the art work feature data of the surrounding area; S6: Perfectly explain the main feature points of the target art work according to the recommendation degrees of each surrounding area.