Method and system for pushing intangible cultural heritage content based on AI technology

Abstract

This invention provides an AI-based method and system for pushing intangible cultural heritage content, involving data processing technology. This method allows users to experience intangible cultural heritage, such as ceramic firing, by wearing virtual-reality VR glasses. During the user's operation, images can be captured to identify the user's current process, and corresponding operational instructions, such as recommended gestures, can be recommended to guide the user's production process to more accurately meet standards, thus achieving automated recommendations.

Description

Technical Field

[0001] The present invention relates to data processing technology, and in particular to a method and system for pushing intangible cultural heritage content based on AI technology. Background Art

[0002] In today's society, the inheritance and development of intangible cultural heritage has received widespread attention. Among them, traditional ceramic firing techniques, as an important intangible cultural heritage project, contain profound cultural heritage and exquisite craftsmanship.

[0003] Currently, when users experience the intangible cultural heritage production process, they typically rely on manual guidance or pre-recorded video tutorials. For example, when attempting to shape a ceramic body into a specific shape (such as a bowl), users need to be manually instructed on the specific operation method, including hand position, angle, and corresponding movements. This approach has many drawbacks. First, labor costs are high and require the constant presence of professional personnel for guidance. Second, due to the subjectivity and variability of manual guidance, the results of the guidance received by different users may vary, making it difficult to ensure a consistent and standardized user experience.

[0004] Therefore, how to combine the user's operational data during the intangible cultural heritage experience to provide users with customized guidance has become an urgent problem that needs to be solved. Summary of the Invention

[0005] The present invention provides an AI-based method and system for pushing intangible cultural heritage content, which can provide users with customized guidance based on their operational data during the intangible cultural heritage experience process.

[0006] A first aspect of the present invention provides a method for pushing intangible cultural heritage content based on AI technology, comprising:

[0007] Push basic display content according to the display device, the basic display content includes a benchmark identifier;

[0008] The visual feature parameters of the intangible cultural heritage products are obtained based on the acquisition equipment, and the process nodes of the intangible cultural heritage products are determined based on the comparison results of the visual feature parameters and the standard feature parameters of each process stage;

[0009] When a process node meets the judgment conditions, a guide identifier corresponding to the process node is generated according to the difference between the visual feature parameters and the corresponding standard feature parameters, and the basic identifier is updated to the guide identifier.

[0010] Optionally, in a possible implementation of the first aspect, obtaining visual feature parameters of the intangible cultural heritage product based on a collection device, and determining a process node of the intangible cultural heritage product based on a comparison result between the visual feature parameters and standard feature parameters of each process stage include:

[0011] Identify the outline of the intangible cultural heritage artifact using a collection device, where the visual feature parameters include the outline of the artifact;

[0012] Selecting process stages in the process sequence as target stages in sequence, retrieving the standard profile of the target stage, wherein the standard feature parameters include the standard profile;

[0013] The total similarity value of the object outline and the standard outline under each viewing angle is calculated and the progress value corresponding to the total similarity value is determined;

[0014] The process axis is retrieved to determine the position of the progress value on the process axis, a process node is generated at the position, and when the progress value is greater than the stage threshold, the process enters the next target stage.

[0015] Optionally, in a possible implementation of the first aspect, obtaining visual feature parameters of the intangible cultural heritage artifact through the following steps includes:

[0016] Identify the breakpoints in the outline of the intangible cultural heritage artifact and calculate the distance between adjacent breakpoints;

[0017] The arc adjustment parameters are obtained according to the ratio of the preset constant and the point distance. The padding line is generated based on the arc adjustment parameters to connect the adjacent breakpoints. The visual feature parameters are obtained according to the outline of the object after padding.

[0018] Optionally, in a possible implementation of the first aspect, the process of acquiring visual feature parameters of the intangible cultural heritage product based on a collection device and determining a process node of the intangible cultural heritage product based on a comparison result between the visual feature parameters and standard feature parameters of each process stage further includes:

[0019] Obtaining a similarity value sequence of the visual feature parameter and the corresponding standard feature parameter according to the time sequence, and obtaining a similarity difference value of adjacent total similarity values ​​in the similarity value sequence;

[0020] When a preset number of consecutive similarity differences are all smaller than the similarity difference threshold, the collection time interval of the collection device is increased according to the extension multiple;

[0021] When a preset number of consecutive similarity difference values ​​are all greater than the similarity difference threshold, the collection time interval of the collection device is reduced according to the shortening factor.

[0022] Optionally, in a possible implementation of the first aspect, when a process node meets a determination condition, generating a guidance indicator corresponding to the process node based on a difference between a visual feature parameter and a corresponding standard feature parameter includes:

[0023] When the progress threshold of the process node is greater than or equal to the determination threshold, it is determined that the preset determination condition is met;

[0024] Comparing the feature parameter difference of the corresponding contour point with the visual feature parameter and the corresponding standard feature parameter, determining the contour point whose feature parameter difference in the visual feature parameter is not within the standard difference value interval as the difference point;

[0025] Determine the feature type of the difference point, traverse the guide actions corresponding to the feature type in the gesture action library, locate the gesture identifier to the actual position corresponding to the difference point, and configure the guide action for the gesture identifier to obtain the guide identifier.

[0026] Optionally, in a possible implementation of the first aspect, comparing the visual feature parameters and the feature parameter differences of the contour points corresponding to the corresponding standard feature parameters, and determining the contour points whose feature parameter differences in the visual feature parameters are not within the standard difference value interval as difference points, includes:

[0027] Obtaining the height difference and curvature difference of the corresponding contour points in the visual feature parameters and the corresponding standard feature parameters, wherein the feature parameter difference includes the height difference and the curvature difference;

[0028] Determine the contour points whose height difference values ​​in the visual feature parameters are not within the corresponding standard deviation value interval and / or whose curvature difference values ​​are not within the corresponding standard deviation value interval as difference points.

[0029] Optionally, in a possible implementation of the first aspect, determining a feature type of a difference point, traversing a gesture action library corresponding to the feature type, locating a gesture identifier to an actual position corresponding to the difference point, and configuring a guidance action for the gesture identifier to obtain a guidance identifier includes:

[0030] Determine the difference point corresponding to the height difference as the height adjustment type, determine the difference point corresponding to the curvature difference as the shape adjustment type, and determine the difference point corresponding to the height difference and curvature difference as the comprehensive adjustment type. The feature types include height adjustment type, shape adjustment type and comprehensive adjustment type;

[0031] The operation direction of the corresponding guidance action is determined according to the positive and negative deviations of the feature type, the gesture identifier is located to the actual position, and while configuring the guidance action for the gesture identifier, its action direction is determined as the operation direction to obtain an updated guidance identifier.

[0032] Optionally, in a possible implementation of the first aspect, the process of locating the gesture identifier to the actual position corresponding to the difference point and configuring a guidance action for the gesture identifier to obtain the guidance identifier further includes:

[0033] Based on the current moment, the moving speed of the user's hand motion in the dynamic time period is obtained, and the moving speed is adjusted to the movement speed of the guide sign.

[0034] Optionally, in a possible implementation of the first aspect, determining the dynamic time period by the following steps includes:

[0035] Taking the current moment as the benchmark, trace back the benchmark time to get the benchmark time period;

[0036] Obtaining the displacement distance of the user's hand in adjacent image frames within a reference time period, and obtaining the distance difference between the displacement distances corresponding to a preset number of consecutive image frames;

[0037] When the distance differences are all less than the threshold, the preset backtracking time is added to the base time period to obtain a dynamic time period;

[0038] When the distance difference is greater than or equal to the threshold, the dynamic time period is obtained by subtracting the preset backtracking time length from the reference time period.

[0039] A second aspect of the present invention provides an AI-based intangible cultural heritage content push system, comprising:

[0040] A push module, configured to push basic display content according to a display device, wherein the basic display content includes a reference identifier;

[0041] The process module is used to obtain the visual feature parameters of the intangible cultural heritage product based on the acquisition equipment, and determine the process node of the intangible cultural heritage product based on the comparison results of the visual feature parameters and the standard feature parameters of each process stage;

[0042] The guidance module is used to generate a guidance identifier corresponding to the process node according to the difference between the visual feature parameters and the corresponding standard feature parameters when the process node meets the judgment conditions, and update the basic identifier to the guidance identifier.

[0043] The beneficial effects of the present invention are as follows:

[0044] The present invention generates targeted guidance marks based on the differences between the visual feature parameters and the standard feature parameters. By comparing the feature parameter differences between the visual feature parameters and the standard feature parameters corresponding to the contour points, the difference points and feature types are determined, including height adjustment type, shape adjustment type and comprehensive adjustment type. The operation direction of the corresponding guidance action is determined based on the positive and negative deviations of the feature type, the gesture mark is positioned to the actual position corresponding to the difference point, and a guidance action is configured for it. This personalized guidance method can help users accurately understand the gap between their own production process and the standard, and make adjustments according to the guidance marks, thereby improving the accuracy and flexibility of the user's operation process.

[0045] The present invention can dynamically adjust the movement speed of the guide sign according to the changes in the user's hand movements. Taking the current moment as a benchmark, the benchmark time period is obtained by tracing back the benchmark time length, and the distance difference between the displacement distance of the user's hand in adjacent image frames within the time period and the displacement distance corresponding to a preset number of consecutive image frames is obtained. According to the comparison result of the distance difference and the threshold, the benchmark time period is dynamically adjusted to obtain the dynamic time period, and then the moving speed of the user's hand movement within the time period is obtained, and it is adjusted to the movement speed of the guide sign. When the user's hand movement changes smoothly, the dynamic time period is extended to obtain more comprehensive speed data; when the hand movement changes greatly, the dynamic time period is shortened to more accurately capture the speed change. In this way, the movement speed of the guide sign is matched with the user's operation rhythm, providing the user with a more natural and smooth operation guidance, and improving the flexibility of the guidance data. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 This is a schematic diagram of an application scenario provided by an embodiment of the present invention;

[0047] Figure 2 This is a flow chart of a method for pushing intangible cultural heritage content based on AI technology provided by an embodiment of the present invention;

[0048] Figure 3 This is a structural diagram of an intangible cultural heritage content push system based on AI technology provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0049] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0050] See also Figure 1 , is a schematic diagram of an application scenario provided by an embodiment of the present invention. In this embodiment, when users experience intangible cultural heritage, such as in the process of firing ceramics, users can wear VR glasses that combine virtuality and reality to experience the ceramic firing process. During the user's operation, images can be collected and the user's current process can be identified, so as to recommend corresponding operation instructions, such as recommending operation gestures, guiding the user's production process to be more in line with standards, and realizing automated recommendations. Among them, Figure 1The display device can be a VR device, and the acquisition device can be a camera. Cameras can be installed above and around the operation area. The server can analyze the images taken by the acquisition devices at various perspectives to determine the user's current process. The server can then provide corresponding operation instructions to the user in combination with the display device, thereby improving the accuracy and efficiency of the user's operation.

[0051] See also Figure 2 , is a flow chart of a method for pushing intangible cultural heritage content based on AI technology provided by an embodiment of the present invention, Figure 2 The execution subject of the method shown may be a software and / or hardware device. The execution subject of the present application may include but is not limited to at least one of the following: user equipment, network equipment, etc. Among them, the user equipment may include but is not limited to computers, smart phones, personal digital assistants (PDAs) and the electronic devices mentioned above. Network equipment may include but is not limited to a single network server, a server group consisting of multiple network servers, or a cloud based on cloud computing consisting of a large number of computers or network servers, wherein cloud computing is a type of distributed computing, a super virtual computer composed of a group of loosely coupled computers. This embodiment does not limit this. It includes steps S101 to S103, as follows:

[0052] S101: Push basic display content according to a display device, where the basic display content includes a reference identifier.

[0053] When the user is ready to begin the intangible cultural heritage experience of ceramic making, they put on the VR device. The VR device can then push basic display content. This basic display content includes benchmark markers, such as images of standard hand gestures, to guide the user through the process. The basic display content refers to pre-configured guidance data used to guide the user through the initial production process, and the benchmark markers are the guiding markers.

[0054] For example, after the user puts on the VR device, a translucent, floating image of a standard hand posture will appear on the console directly in front of them. This image shows the hand posture during the initial movement of ceramic throwing, with the hands in a ring, simulating the state of grasping the clay. This benchmark is an important guide for users to begin the ceramic making experience. It not only allows users to intuitively see the basic hand posture for the current production stage, providing a preliminary model for subsequent actual operation, but also allows users to refer back to this benchmark at any time throughout the ceramic making process to check whether their hand posture deviates from the standard, ensuring standardization and accuracy of operation.

[0055] S102, obtaining visual feature parameters of the intangible cultural heritage product based on the acquisition device, and determining the process node of the intangible cultural heritage product based on the comparison results of the visual feature parameters and the standard feature parameters of each process stage.

[0056] As users make ceramics, cameras positioned at various locations in the workshop begin operating. These cameras capture the state of the ceramic blank in the user's hands in all directions and in real time. Visual feature parameters refer to the shape change parameters of intangible cultural heritage artifacts, such as their outline. Standard feature parameters refer to the shape parameters of standard artifacts at each process stage. By comparing these parameters, the user's current production progress can be determined, allowing for subsequent production guidance. Process nodes refer to the nodes corresponding to the user's process progress. Intangible cultural heritage artifacts can be ceramics.

[0057] Detailed and precise standard feature parameters can be pre-set for each stage of ceramic production. For example, in the throwing stage, the standard green body profile can be a cylinder with uniform top and bottom and a flat bottom.

[0058] The server compares the visual features of the ceramic body captured by the camera with the standard features at each process stage. By meticulously analyzing the body's contours from multiple perspectives (such as top and side views), the server identifies the corresponding process node.

[0059] Based on the above embodiment, the specific implementation of step S102 may be:

[0060] The object outline of the intangible cultural heritage product is identified according to the acquisition equipment, and the visual feature parameters include the object outline.

[0061] Capturing devices with different viewing angles can capture the contours of intangible cultural heritage artifacts from different angles. This allows for more comprehensive data on the user's production process. For example, during the initial wheel throwing process, the clay may be an irregular block, and the camera can identify its general external shape. As the user manipulates the clay, it gradually forms a roughly cylindrical shape, and the camera can capture this changing contour. During the trimming process, the contours become more refined and regular, and the camera can also accurately identify and record them. This identified object contour is a key component of the visual feature parameters. It records the shape of the ceramic body at every moment of the production process.

[0062] It is understandable that, due to various factors in the actual ceramic production process, the collected object contour may not be a continuous and complete line. For example, the user's hand may block the object contour, which may make the extracted object contour incomplete. Therefore, in order to improve the accuracy of the process judgment, in some embodiments, the visual feature parameters can be obtained by the following steps:

[0063] Identify the breakpoints in the outline of the intangible cultural heritage product, calculate the point distance between adjacent breakpoints, obtain the arc adjustment parameter according to the ratio of the preset constant and the point distance, generate the filling line based on the arc adjustment parameter to connect the adjacent breakpoints, and obtain the visual feature parameters according to the outline of the item after filling.

[0064] Breakpoints are discontinuous points in an object's outline. For example, uneven hand manipulation or variations in clay texture during the throwing process can cause uneven surfaces on the object, resulting in discontinuities in the object's outline in the image. To calculate the distance between adjacent breakpoints, the coordinates of the breakpoints in the image are determined, and a mathematical formula is used to calculate the actual distance between them. This distance reflects the degree of discontinuity.

[0065] The arc adjustment parameter is the coefficient used to adjust the arc angle of the line segment connecting adjacent breakpoints. The fill line is the arc connecting adjacent breakpoints. Based on the determined arc parameters, an arc can be drawn to connect the two breakpoints and the arc angle can be adjusted using these parameters.

[0066] It is understandable that when the two breakpoints are very close, if a smaller curvature is set, the arc will be relatively gentle. In this way, when connecting the two breakpoints, the arc may not be able to closely fit the contour trend near the breakpoints, resulting in a large deviation between the contour after filling and the contour of the actual object, resulting in distortion. Setting a larger curvature can make the arc better fit the contour near the breakpoint, maintain the coherence and authenticity of the contour, and make the contour after filling closer to the actual shape of the ceramic body. On the contrary, if the distance between the points is large, a smaller curvature can be used to make the arc relatively gentle.

[0067] Through the above method, the breakpoints in the outline of the ceramic body object can be effectively filled in and more accurate visual feature parameters can be obtained.

[0068] The process stages in the process sequence are selected in sequence as target stages, and the standard profile of the target stage is retrieved. The standard feature parameters include the standard profile.

[0069] It's understandable that ceramic production is a strictly ordered and phased process, with a pre-defined process sequence typically encompassing multiple stages, such as throwing, trimming, decorating, and firing. Each stage can be set as the target stage in this pre-configured process sequence.

[0070] For each target stage, the database stores a corresponding standard profile. These profiles can be standard shapes determined by personnel based on actual conditions. For example, during the throwing stage, the standard profile is a perfect cylinder with a flat bottom, vertical sidewalls, and uniform thickness. When the system sets a process stage as the target stage, it retrieves the corresponding standard profile from the database. This standard profile becomes an important reference for measuring whether the current ceramic body production meets the standards and is a key component of the standard characteristic parameters.

[0071] The total similarity value of the object outline and the standard outline under each perspective is calculated and integrated to determine the progress value corresponding to the total similarity value.

[0072] Specifically, the similarity of the object's outline from various perspectives (such as top and side) can be compared with the standard outline from that perspective. The similarities calculated from multiple perspectives are then added together to obtain a total similarity. The total similarity value reflects the degree of completion of the current ceramic production at the target stage. Based on pre-defined correspondences, the total similarity value can be converted into a corresponding progress value. For example, if the total similarity value is 80%, the corresponding progress value may indicate that the current ceramic production is 80% complete at that stage of the process. The progress value provides users and the system with a quantitative indicator, clearly indicating the progress of the ceramic production at the current stage.

[0073] The process axis is retrieved to determine the position of the progress value on the process axis, a process node is generated at the position, and when the progress value is greater than the stage threshold, the process enters the next target stage.

[0074] The process axis is a data axis used to represent user progress. On this axis, the various process stages are arranged in chronological order, and each stage has its own corresponding range and threshold. Each stage on the process axis has a corresponding progress value at each position. Once the user's corresponding progress value is determined, the corresponding process node can be generated at the corresponding position.

[0075] Each process stage has a threshold value, which serves as the criterion for advancing to the next stage. When the progress value exceeds this threshold, the user has essentially met the production requirements for the current stage and can proceed to the next stage. For example, if the threshold for the throwing stage is set at 90%, when the progress value reaches 92%, the system will set the next process stage (such as the trimming stage) as the target stage, and then repeat the above steps to continue analyzing and guiding the user towards the new target stage, thereby helping the user gradually complete the entire ceramic production process.

[0076] In addition, the process of step S102 (obtaining visual feature parameters of the intangible cultural heritage product based on the acquisition device, and determining the process node of the intangible cultural heritage product based on the comparison results of the visual feature parameters and the standard feature parameters of each process stage) may also include the following embodiments:

[0077] A similarity value sequence of visual feature parameters and corresponding standard feature parameters is obtained in chronological order, and similarity differences of adjacent total similarity values ​​in the similarity value sequence are obtained; when a continuous preset number of similarity differences are all smaller than a similarity difference threshold, the collection time interval of the collection device is increased according to an extension multiple; when a continuous preset number of similarity differences are all larger than a similarity difference threshold, the collection time interval of the collection device is reduced according to a shortening multiple.

[0078] It can be understood that in order to reduce the amount of data collected by the acquisition device and to promptly capture changes in the user's production process, so as to quickly determine whether there is a deviation in the process and provide users with more accurate operation guidance, the frequency of image acquisition by the acquisition device can be dynamically adjusted.

[0079] Specifically, during the user's ceramic production process, the camera continuously captures images of the ceramic body, arranges and records the total similarity values ​​at adjacent moments to obtain a similarity value sequence, and calculates the similarity difference between adjacent total similarity values ​​in real time. It can be understood that the similarity difference between adjacent moments can reflect the rate of change of the body state, which is crucial for accurately grasping the dynamic changes in the ceramic production process. The similarity threshold refers to a preset value used to determine the magnitude of the change in the similarity difference.

[0080] If the similarity differences between multiple consecutive moments are large and increasing, this indicates that the state of the ceramic body is changing rapidly. This means that during this period, the differences between the shape and other features of the ceramic body and similar samples in the feature library are rapidly increasing. This may be due to the user making significant shape adjustments, such as when quickly shaping the body's general shape in the early stages of throwing.

[0081] When the state of a ceramic body changes rapidly, these changes need to be captured promptly so the system can quickly determine if there are any deviations in the process and provide users with precise operational guidance. Therefore, in this case, the interval between data acquisition devices can be shortened, and the acquisition frequency can be increased to more comprehensively record changes in the body, thereby enabling timely detection of abnormal changes in the body state. The shortening factor refers to the preset multiple by which the acquisition interval is shortened.

[0082] For example, when the similarity differences of a preset number of consecutive adjacent moments are large and show an increasing trend, the collection interval can be shortened to half of the original time.

[0083] If the similarity difference between adjacent moments is small, or even shows a downward trend, it indicates that the state of the ceramic body is changing slowly or tending to be stable. This indicates that the ceramic body is gradually approaching a stable state similar to a sample in the feature library, and may be in the final stage of the body repair process, where fine-tuning is being performed.

[0084] When the ceramic body is stable and changes are minimal over a short period of time, frequent data collection will generate a large amount of redundant data, increasing the processing burden. Extending the data collection interval can reduce unnecessary data collection and lower the data processing load. The extension factor is a preset multiple by which the data collection interval is extended.

[0085] For example, when the similarity differences of a preset number of consecutive adjacent moments are small and show a downward trend, the collection interval can be extended to 1.5 times the original time.

[0086] S103: When the process node meets the determination condition, a guide identifier corresponding to the process node is generated according to the difference between the visual feature parameters and the corresponding standard feature parameters, and the basic identifier is updated to the guide identifier.

[0087] Decision conditions are used to provide more targeted guidance to users. When the progress of a ceramic production process node reaches or exceeds a threshold, it means that the user needs more targeted operational guidance, and the decision condition is determined to be met. For example, in the ceramic trimming process, if the progress of the current ceramic workpiece process node reaches 70% (assuming the decision threshold is 60%), the condition is met.

[0088] Difference points are contour points whose visual feature parameters differ from those of the standard. These difference points can be used to determine the difference between the ceramic body currently being produced by the user and the standard state. For example, the ceramic body produced by the user may be too high compared to the standard state. Guidance markers are used to guide the user when making error adjustments. For example, the guidance marker can be a dynamic virtual hand posture image that simulates the correct hand posture. If the height of the ceramic body produced by the user is too high, it can be a hand posture of scraping downwards. This guidance marker will directly replace the previous reference marker. Users can clearly and intuitively see this guidance in the VR device, and then adjust their hand operations according to the hand posture and movements displayed by the guidance marker, better complete the various stages of ceramic production, and gradually make the ceramic body produced by the user approach the standard process effect.

[0089] Based on the above embodiment, the specific implementation of step S103 may be:

[0090] When the progress threshold of the process node is greater than or equal to the determination threshold, it is determined that the preset determination condition is met.

[0091] Among them, the judgment threshold refers to the threshold for providing more targeted guidance to users. The threshold can be pre-configured. For example, in the ceramic trimming process stage, assuming that the judgment threshold is set to 70%, the server calculates that the progress value of the current process node is 75%, and the preset judgment condition is met at this time. This means that the user has completed most of the work in the trimming operation, and then more precise guidance is needed to complete the remaining part to make the body closer to the standard state. The advantage of setting the judgment condition in this way is that it can clearly indicate when more detailed guidance is needed for users, avoiding intervening in user operations too early or too late, and ensuring the timeliness and effectiveness of the guidance.

[0092] The visual feature parameters are compared with the feature parameter differences of the corresponding contour points of the corresponding standard feature parameters, and the contour points whose feature parameter differences in the visual feature parameters are not within the standard difference value interval are determined as difference points.

[0093] Specifically, the contour points of the visual feature parameters and the corresponding standard feature parameters can be matched one by one. In practical applications, the feature points of the visual feature parameters and the corresponding standard feature parameters can be extracted first, and then matched by the feature points. The difference in parameters such as the height and curvature of these contour points is then calculated, and the contour points that are not within the normal range are regarded as difference points. The feature parameter difference refers to the difference between the feature parameters of the corresponding contour points, such as the height parameter and the curvature parameter. The standard deviation interval refers to the interval corresponding to the normal error range set in advance. When the feature parameter difference exceeds the standard deviation interval, the corresponding contour point is identified as a difference point. These difference points intuitively reflect the position and degree of deviation between the current state of the ceramic body and the standard state.

[0094] For example, when determining whether the contour of a certain part of a ceramic body meets the standard, suppose the standard requires a curvature between 0.8 and 1.2, but the curvature of the corresponding contour point in the actual calculated visual feature parameters is 0.6. This difference is not within the standard deviation range, so the contour point is determined to be a discrepancy. In this way, the specific location where the current ceramic body is inconsistent with the standard state can be accurately identified.

[0095] In some embodiments, the difference can be determined by the following steps:

[0096] Obtain the height difference and curvature difference of the corresponding contour points in the visual feature parameters and the corresponding standard feature parameters, where the feature parameter difference includes the height difference and the curvature difference; determine the contour points in the visual feature parameters whose height difference is not in the corresponding standard difference value interval and / or whose curvature difference is not in the corresponding standard difference value interval as difference points.

[0097] For each set of corresponding contour points, obtain their height values. This height value can be the vertical distance relative to a reference surface (such as the table of a wheel throwing machine). The difference between the height value of the contour point in the visual feature parameters and the height value of the corresponding contour point in the standard feature parameters is then calculated. This difference is the height difference. For example, if the height of a contour point in the standard feature parameters is 10 cm, and the height of the corresponding contour point in the visual feature parameters is 10.3 cm, then the height difference is 10.3 - 10 = 0.3 cm.

[0098] Curvature describes the degree of curvature of a curve. For the contour curve of a ceramic body, the curvature at the contour point in the visual feature parameters and the curvature at the corresponding contour point in the standard feature parameters are calculated separately. These two curvature values ​​can be obtained using mathematical methods (such as calculating the curvature through the derivative of the curve). The difference between them is then calculated to obtain the curvature difference. For example, if the curvature at a contour point in the standard feature parameters is 0.5, while the curvature at the corresponding contour point in the visual feature parameters is 0.4, then the curvature difference is 0.1.

[0099] For height and curvature differences, corresponding standard deviation ranges can be pre-set. These ranges can be determined based on the precision requirements of the ceramic manufacturing process. For example, for height differences, a standard deviation range of ±0.2 cm might be set, meaning that height differences within this range are considered within the normal manufacturing error range. For curvature differences, a standard deviation range of ±0.1 cm might be set, meaning that curvature differences within this range are acceptable.

[0100] The calculated height difference and curvature difference are compared with the corresponding standard deviation value interval. If the height difference of a contour point in the visual feature parameters is not within the corresponding standard deviation value interval, or the curvature difference is not within the corresponding standard deviation value interval, or both are not within the corresponding interval, then this contour point is determined to be a difference point.

[0101] It's understandable that the height difference directly reflects the degree of vertical deviation from the standard shape of the blank. For example, when making dishes, if the height difference at a certain location exceeds the standard range, it may mean that the depth of the dish does not meet the requirements. The curvature difference measures the degree of curvature of the blank's contour curve compared to the standard. For example, a vase typically has a specific curved shape. The curvature difference can help determine whether the curve meets the design requirements and whether there are any areas that are too curved or too straight. Therefore, the parameters of these two dimensions can be combined when determining the difference points.

[0102] Determine the feature type of the difference point, traverse the guide actions corresponding to the feature type in the gesture action library, locate the gesture identifier to the actual position corresponding to the difference point, and configure the guide action for the gesture identifier to obtain the guide identifier.

[0103] After identifying the difference point, we need to clarify its feature type to find the appropriate guided action. The feature type is the adjustment type corresponding to the difference point, which can be categorized based on different characteristic parameters, such as types related to height or curvature. The gesture action library is a pre-built database that stores various guided action information for different feature types of difference points.

[0104] Taking curvature adjustment as an example, the server traverses a gesture action library, which pre-stores various guided actions corresponding to different feature types. For example, let's assume the library includes a guided action for curvature adjustment: "Use a trimming knife to scrape in a specific direction to adjust the curvature." The system uses VR technology to locate the gesture identifier representing this guided action at the actual location of the discrepancy. For example, if the discrepancy is located at a point on the side of the ceramic body where the curvature does not meet the standard, the gesture identifier will appear precisely near that location, presenting it to the user in an intuitive manner. The gesture identifier is also configured with a corresponding guided action, simulating an animation of scraping with a trimming knife, allowing the user to clearly understand how to adjust the body at the discrepancy. This ultimately generates a complete guided action. This generated guided action provides intuitive and easy-to-understand guidance for the user, leveraging the immersive and interactive nature of VR technology to help users better complete fine-tuning adjustments during the ceramic production process, improving both quality and efficiency.

[0105] In some embodiments, the guide identifier may be obtained by the following steps:

[0106] Determine the difference point corresponding to the height difference as the height adjustment type, determine the difference point corresponding to the curvature difference as the shape adjustment type, determine the difference point corresponding to the height difference and the curvature difference as the comprehensive adjustment type, and the feature types include height adjustment type, shape adjustment type and comprehensive adjustment type; determine the operation direction of the corresponding guidance action according to the positive and negative bias of the feature type, locate the gesture marker to the actual position, and while configuring the guidance action for the gesture marker, determine its action direction as the operation direction to obtain the updated guidance marker.

[0107] Among them, the height adjustment type is a type for adjusting the height, the shape adjustment type is a type for adjusting the shape, and the comprehensive adjustment type is a type for comprehensive adjustment of the height and shape.

[0108] When determining the direction of the corresponding guided action based on the positive and negative bias of the feature type, for height adjustment, if the height difference is positive (i.e., the actual height is greater than the standard height), the action might be downward adjustment, such as pressing down or scraping. If the height difference is negative (i.e., the actual height is less than the standard height), the action might be upward addition of material. For shape adjustment, if the curvature difference is positive (i.e., the actual curvature is greater than the standard), the action might be to flatten the curve, such as by sanding. If the curvature difference is negative (i.e., the actual curvature is less than the standard), the action might be to increase the curvature of the curve, such as by applying local pressure with a finger on the surface of a mud pile, creating a depression and increasing the curvature of that area. For combined adjustment, the positive and negative biases of both height and curvature must be considered to determine an appropriate action direction that addresses both height and shape. For example, a gesture to lower the height, such as pressing down or scraping, can be performed first to bring the height closer to the standard value. After adjusting the height, a gesture to reduce the curvature, such as sanding with a palm, can be performed.

[0109] Once the direction is determined, VR technology can be used to precisely position the gesture icon representing the guiding action at the actual location corresponding to the difference point. For example, in a VR scene, when a contour point is determined to be a shape adjustment difference point and the operation direction is to make the curve smoother, a gesture icon simulating a polishing action will appear at the actual location, and the gesture icon will be assigned a guiding action consistent with the operation direction, intuitively informing the user of the required operation location and action.

[0110] Through the above method, targeted and operational guidance signs can be generated according to the actual differences of ceramic blanks, providing users with effective guidance and helping them better complete the ceramic production experience.

[0111] In addition, based on the above embodiment, in the process of the step of "locating the gesture identifier to the actual position corresponding to the difference point, and configuring a guiding action for the gesture identifier to obtain a guiding identifier", the following embodiments are also included:

[0112] Based on the current moment, the moving speed of the user's hand motion in the dynamic time period is obtained, and the moving speed is adjusted to the movement speed of the guide sign.

[0113] It can be understood that when users use VR devices to experience ceramic production, this step is mainly to match the movement speed of the guide signs with the speed of the user's hand movements, thereby providing guidance that is more in line with the user's operating rhythm.

[0114] Specifically, when adjusting the speed of a guide sign, you can first determine the current moment as a reference point. Then, define a dynamic time period to obtain the user's historical speed. Generally speaking, this time period may be between a few seconds and more than ten seconds.

[0115] When obtaining the movement speed of the user's hand motion, the distance the hand moves in unit time can be calculated based on the position coordinates of the hand at different times, thereby obtaining the movement speed, and the movement speed is set as the movement speed of the guide mark.

[0116] In some embodiments, the dynamic time period may be determined by:

[0117] Taking the current moment as the benchmark, trace back the benchmark time length to obtain the benchmark time period; obtain the displacement distance of the user's hand in adjacent image frames within the benchmark time period, and obtain the distance difference between the displacement distances corresponding to a preset number of consecutive image frames; when the distance differences are all less than the threshold, add the preset backtracking time length to the benchmark time period to obtain the dynamic time period; when there is a distance difference greater than or equal to the threshold, subtract the preset backtracking time length from the benchmark time period to obtain the dynamic time period.

[0118] Among them, the reference duration is a pre-set duration. The current moment and the reference moment can be used to trace back the corresponding time period to obtain the reference time period. Within the reference time period, the displacement distance of the user's hand in adjacent image frames can be obtained. The user's hand movement information can be collected in real time and recorded in the form of image frames. By analyzing the position changes of the user's hand in these image frames, the distance moved by the hand between adjacent image frames is calculated. Then, the distance difference between the displacement distances corresponding to a preset number of consecutive image frames can be obtained. The preset number is a pre-set value. By calculating these distance differences, the changes in the user's hand displacement distance can be understood.

[0119] When the distance differences corresponding to a preset number of consecutive image frames are all less than the threshold, it indicates that the user's hand movements were relatively stable within the baseline time period, with minimal changes in displacement distance. In this case, to more comprehensively analyze the speed trends of the user's hand movements, a preset lookback duration can be added to the baseline time period to create a longer dynamic time period. For example, if the preset lookback duration is 2 seconds, the original 5-second baseline time period will be increased to 7 seconds. This 7-second lookback duration becomes the new dynamic time period. This allows more data to be collected when the user's hand movements are stable, allowing for accurate calculation of hand movement speed.

[0120] When the distance difference is greater than or equal to the threshold, it indicates that the user's hand movements have changed significantly within the baseline time period, and the displacement distance has fluctuated significantly. In this case, to focus more on the key changes in the user's hand movements, the preset lookback time can be subtracted from the baseline time period to obtain a shorter dynamic time period. For example, after subtracting the preset lookback time of 2 seconds, the original 5-second baseline time period becomes 3 seconds. This 3-second time period is the new dynamic time period. By shortening the time period, the speed information of the user's hand movements can be more accurately captured, allowing for timely adjustment of the movement speed of the guide sign.

[0121] Through the above steps, the time period used to analyze the hand movement speed can be dynamically adjusted according to the changes in the user's hand movements, so as to more accurately calculate the hand movement speed, provide a more reliable basis for adjusting the movement speed of the guide sign, and enable the movement speed of the guide sign to better match the user's operation rhythm.

[0122] See also Figure 3 , is a schematic structural diagram of an AI-based intangible cultural heritage content push system provided by an embodiment of the present invention. The AI-based intangible cultural heritage content push system includes:

[0123] A push module, configured to push basic display content according to a display device, wherein the basic display content includes a reference identifier;

[0124] The process module is used to obtain the visual feature parameters of the intangible cultural heritage product based on the acquisition equipment, and determine the process node of the intangible cultural heritage product based on the comparison results of the visual feature parameters and the standard feature parameters of each process stage;

[0125] The guidance module is used to generate a guidance identifier corresponding to the process node according to the difference between the visual feature parameters and the corresponding standard feature parameters when the process node meets the judgment conditions, and update the basic identifier to the guidance identifier.

[0126] Figure 3 The apparatus of the embodiment shown can be used to perform Figure 2 The implementation principles and technical effects of the steps in the method embodiment shown are similar and will not be repeated here.

[0127] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for pushing intangible cultural heritage content based on AI technology, characterized in that: include: Push basic display content according to the display device, the basic display content includes a benchmark identifier; The visual feature parameters of the intangible cultural heritage product are obtained by the acquisition equipment. Based on the comparison results of the visual feature parameters and the standard feature parameters of each process stage, the process nodes of the intangible cultural heritage product are determined, including: Identify the outline of the intangible cultural heritage artifact using a collection device, where the visual feature parameters include the outline of the object; Selecting process stages in the process sequence as target stages in sequence, retrieving the standard profile of the target stage, wherein the standard feature parameters include the standard profile; The total similarity value of the object outline and the standard outline under each viewing angle is calculated and the progress value corresponding to the total similarity value is determined; Retrieve the process axis, determine the position of the progress value on the process axis, generate a process node at the position, and enter the next target stage when the progress value is greater than the stage threshold; When a process node meets the judgment conditions, a guide identifier corresponding to the process node is generated based on the difference between the visual feature parameters and the corresponding standard feature parameters, and the basic identifier is updated to the guide identifier, including: When the progress threshold of the process node is greater than or equal to the determination threshold, it is determined that the preset determination condition is met; Comparing the feature parameter difference of the corresponding contour point with the visual feature parameter and the corresponding standard feature parameter, determining the contour point whose feature parameter difference in the visual feature parameter is not within the standard difference value interval as the difference point; Determine the feature type of the difference point, traverse the guide actions corresponding to the feature type in the gesture action library, locate the gesture identifier to the actual position corresponding to the difference point, and configure the guide action for the gesture identifier to obtain the guide identifier.

2. The method according to claim 1, characterized in that The visual feature parameters of the intangible cultural heritage products are obtained through the following steps, including: Identify the breakpoints in the outline of the intangible cultural heritage artifact and calculate the distance between adjacent breakpoints; The arc adjustment parameters are obtained according to the ratio of the preset constant and the point distance. The padding line is generated based on the arc adjustment parameters to connect the adjacent breakpoints. The visual feature parameters are obtained according to the outline of the object after padding.

3. The method according to claim 1, characterized in that The process of obtaining visual feature parameters of the intangible cultural heritage product based on the acquisition equipment and determining the process nodes of the intangible cultural heritage product based on the comparison results of the visual feature parameters and the standard feature parameters of each process stage also includes: Obtaining a similarity value sequence of the visual feature parameter and the corresponding standard feature parameter according to the time sequence, and obtaining a similarity difference value of adjacent total similarity values ​​in the similarity value sequence; When a preset number of consecutive similarity differences are all smaller than the similarity difference threshold, the collection time interval of the collection device is increased according to the extension multiple; When a preset number of consecutive similarity difference values ​​are all greater than the similarity difference threshold, the collection time interval of the collection device is reduced according to the shortening factor.

4. The method according to claim 1, wherein Compare the feature parameter differences of the corresponding contour points of the visual feature parameters and the corresponding standard feature parameters, and determine the contour points whose feature parameter differences in the visual feature parameters are not within the standard difference value interval as difference points, including: Obtaining the height difference and curvature difference of the corresponding contour points in the visual feature parameters and the corresponding standard feature parameters, wherein the feature parameter difference includes the height difference and the curvature difference; Determine the contour points whose height difference values ​​in the visual feature parameters are not within the corresponding standard deviation value interval and / or whose curvature difference values ​​are not within the corresponding standard deviation value interval as difference points.

5. The method according to claim 4, characterized in that Determine the feature type of the difference point, traverse the guide actions corresponding to the feature type in the gesture action library, locate the gesture identifier to the actual position corresponding to the difference point, and configure the guide action for the gesture identifier to obtain the guide identifier, including: Determine the difference point corresponding to the height difference as the height adjustment type, determine the difference point corresponding to the curvature difference as the shape adjustment type, and determine the difference point corresponding to the height difference and curvature difference as the comprehensive adjustment type. The feature types include height adjustment type, shape adjustment type and comprehensive adjustment type; The operation direction of the corresponding guidance action is determined according to the positive and negative deviations of the feature type, the gesture identifier is located to the actual position, and while configuring the guidance action for the gesture identifier, its action direction is determined as the operation direction to obtain an updated guidance identifier.

6. The method according to claim 1, characterized in that The process of locating the gesture identifier to the actual position corresponding to the difference point and configuring a guidance action for the gesture identifier to obtain the guidance identifier also includes: Based on the current moment, the moving speed of the user's hand motion in the dynamic time period is obtained, and the moving speed is adjusted to the movement speed of the guide sign.

7. The method according to claim 6, characterized in that The following steps are used to determine the dynamic time period: Taking the current moment as the benchmark, trace back the benchmark time to get the benchmark time period; Obtaining the displacement distance of the user's hand in adjacent image frames within a reference time period, and obtaining the distance difference between the displacement distances corresponding to a preset number of consecutive image frames; When the distance differences are all less than the threshold, the preset backtracking time is added to the base time period to obtain a dynamic time period; When the distance difference is greater than or equal to the threshold, the dynamic time period is obtained by subtracting the preset backtracking time length from the reference time period.

8. An AI-based intangible cultural heritage content push system according to any one of claims 1 to 7, characterized in that: include: A push module, configured to push basic display content according to a display device, wherein the basic display content includes a reference identifier; The process module is used to obtain the visual feature parameters of the intangible cultural heritage product based on the acquisition equipment, and determine the process node of the intangible cultural heritage product based on the comparison results of the visual feature parameters and the standard feature parameters of each process stage; The guidance module is used to generate a guidance identifier corresponding to the process node according to the difference between the visual feature parameters and the corresponding standard feature parameters when the process node meets the judgment conditions, and update the basic identifier to the guidance identifier.

Images