Character practice method and device, electronic equipment, storage medium and product

Abstract

The invention provides a character practice method and device, electronic equipment, a storage medium and a product. The method comprises the following steps: shooting in real time to obtain a user exercise book image; identifying grids in the exercise book image and determining a to-be-exercised area; the to-be-practiced area is matched with a standard grid in a character action model to determine the display position of the virtual action model in the to-be-practiced area, and the character action model is a dynamic three-dimensional model containing a hand action track in the process that a single character is written in the standard grid; the to-be-exercised characters are exercised based on the display position and the character action model, a learner can learn according to own time arrangement and rhythm and can also select characters needing to be exercised according to own requirements, the space-time flexibility of character exercise is improved, and personalized teaching is achieved.

Description

Technical Field

[0001] This disclosure relates to the field of metaverse technology, and more particularly to a character practice method, apparatus, electronic device, storage medium, and product. Background Technology

[0002] Character practice programs often rely on face-to-face guidance and demonstrations from professional teachers. While this teaching model can provide direct interaction and feedback, the fixed teaching location and time may conflict with learners' daily schedules, and students cannot choose the characters they want to practice, thus limiting the flexibility of learning. Summary of the Invention

[0003] This disclosure provides a character practice method, apparatus, electronic device, storage medium, and product to solve the problem in the related art that fixed teaching locations and time arrangements may conflict with learners' daily schedules, and students are unable to choose the characters they want to practice, thus limiting the flexibility of learning.

[0004] A first aspect of this disclosure provides a character practice method, the method comprising: Real-time capture of images of the user's practice notebook; Identify the squares in the exercise book image and determine the area to be practiced; The practice area is adapted to the standard square in the character motion model to determine the display position of the virtual motion model in the practice area. The character motion model is a dynamic three-dimensional model containing the hand motion trajectory of a single character during the writing process in the standard square. The character to be practiced is practiced based on the display position and character action model.

[0005] A second aspect of this disclosure provides a character practice apparatus, the apparatus comprising: The acquisition unit is used to capture images of the user's practice book in real time; The recognition unit is used to identify the squares in the exercise book image and determine the area to be practiced. The adaptation unit is used to adapt the area to be practiced to the standard square in the character motion model in order to determine the display position of the virtual motion model in the area to be practiced. The character motion model is a dynamic three-dimensional model containing the hand motion trajectory of a single character during the writing process of the standard square. The practice unit is used to practice the character to be practiced based on the display position and character action model.

[0006] A third aspect of this disclosure provides an electronic device comprising: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the methods described in the first aspect of this disclosure.

[0007] A fourth aspect of this disclosure provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to perform the methods described in the first aspect of this disclosure.

[0008] A fifth aspect of this disclosure provides a computer program product including a computer program that, when executed by a processor, implements the methods described in the first aspect of this disclosure.

[0009] In summary, this disclosure proposes a character practice method, which includes: capturing images of a user's practice book in real time; identifying squares in the practice book image and determining the area to be practiced; adapting the area to be practiced to standard squares in a character motion model to determine the display position of the virtual motion model in the area to be practiced, wherein the character motion model is a dynamic three-dimensional model containing the hand motion trajectory of a single character during writing in a standard square; and practicing the character to be practiced based on the display position and the character motion model.

[0010] According to the solution provided in this disclosure, the display position of the virtual motion model in the practice area is determined based on the standard squares in the character motion model. Then, based on the display position and the character motion model, which includes the hand motion trajectory of a single character during the writing process in the standard squares, the learner can practice the character to be practiced. Learners can learn according to their own time schedule and pace, and can also choose the characters to practice according to their own needs, thereby improving the spatiotemporal flexibility of character practice and realizing personalized teaching.

[0011] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0012] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure, and are not intended to unduly limit this disclosure.

[0013] Figure 1 A flowchart illustrating the character practice method provided in this embodiment of the disclosure; Figure 2 A flowchart illustrating the method for generating a character action model provided in this embodiment of the disclosure; Figure 3A schematic diagram of calligraphy practice provided for an embodiment of this disclosure; Figure 4 A schematic diagram illustrating the deformation of the grid in the exercise book provided for an embodiment of this disclosure; Figure 5 A schematic diagram of a character action model provided in an embodiment of this disclosure; Figure 6 A flowchart illustrating the method for determining the practice area provided in this embodiment of the disclosure; Figure 7 A flowchart illustrating a method for determining the display position of a virtual motion model in a practice area, as provided in an embodiment of this disclosure; Figure 8 A flowchart illustrating the method for determining a virtual action model provided in an embodiment of this disclosure; Figure 9 A flowchart illustrating the method for practicing characters to be practiced provided in this embodiment of the disclosure; Figure 10 A flowchart illustrating the character practice method provided as an application example of this disclosure; Figure 11 A schematic diagram of the structure of the character practice device provided in the embodiments of this disclosure; Figure 12 This is a schematic diagram of the hardware composition structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0014] Embodiments of this disclosure are described in detail below. Examples of these embodiments are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this disclosure, and should not be construed as limiting this disclosure.

[0015] As an important part of traditional Chinese culture, calligraphy not only carries profound historical heritage and cultural value, but also embodies the spirit and aesthetic taste of the Chinese nation. With its unique artistic charm and cultural significance, it has always been highly valued by all sectors of society. The inheritance and development of calligraphy art is not only related to the continuation of culture, but also a manifestation of national confidence and cultural identity.

[0016] However, traditional calligraphy practice often relies on face-to-face guidance and demonstrations from professional teachers. While this teaching model provides direct interaction and feedback, it has many limitations in terms of venue, time, and practice costs. First, fixed teaching locations and schedules may conflict with learners' daily schedules, limiting learning flexibility. Second, over-reliance on teacher guidance may restrict learners' space for independent exploration and innovation, affecting the implementation of personalized teaching.

[0017] Character practice programs often rely on face-to-face guidance and demonstrations from professional teachers. While this teaching model can provide direct interaction and feedback, the fixed teaching location and time may conflict with learners' daily schedules, and students cannot choose the characters they want to practice, thus limiting the flexibility of learning.

[0018] To address the shortcomings of related technologies, this disclosure determines the display position of the virtual motion model in the practice area based on the standard squares in the character motion model. Then, based on the display position and the character motion model, which includes the hand motion trajectory of a single character during writing in the standard squares, the learner can practice the character to be practiced. Learners can study according to their own schedule and pace, and can also choose the characters to practice according to their own needs, thereby improving the spatiotemporal flexibility of character practice and realizing personalized teaching.

[0019] The present disclosure will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0020] The present disclosure provides a character practice method that can be applied to character writing practice scenarios that require precise guidance and feedback, and is particularly suitable for fields such as calligraphy practice and language learning. The method can be executed by a system that integrates augmented reality (AR) and dynamic 3D reconstruction functions.

[0021] like Figure 1 As shown, Figure 1 This is a flowchart illustrating the character practice method provided in this embodiment of the disclosure. The character practice method provided in this embodiment includes the following steps: Step 101: Capture images of the user's practice notebook in real time; In one embodiment, a user opens an AR device with a specific application installed and takes a real-time image of a practice book containing calligraphy practice squares. The AR device can be a smartphone, tablet, or AR glasses, etc.

[0022] Step 102: Identify the squares in the exercise book image and determine the area to be practiced; In one embodiment, before recognizing the squares in the exercise book image, the user exercise book image can be preprocessed, including brightness adjustment, contrast adjustment, and image sharpening, to facilitate the recognition of squares in the user exercise book image.

[0023] In one embodiment, the user's exercise book can be laid flat to improve the accuracy of grid recognition in the exercise book image.

[0024] In one embodiment, image processing algorithms such as edge detection and Hough transform can be used to identify squares in the exercise image. Specifically, edge detection algorithms are used to identify all possible lines in the image, and then algorithms such as Hough transform are used to further confirm whether these lines constitute squares.

[0025] In one embodiment, the practice area refers to the practice square in the exercise book specified by the user. Specifically, the user can select a square as the practice area by gesture (such as pointing with a finger or pointing with the pen held by the user), such as recognizing the area specified by the user's index finger as the practice area.

[0026] Step 103: Adapt the practice area to the standard square in the character motion model to determine the display position of the virtual motion model in the practice area. The character motion model is a dynamic three-dimensional model containing the hand motion trajectory of a single character during the writing process in the standard square. In one embodiment, the character action model is used to guide the user on how to correctly write each character.

[0027] In one embodiment, the position and size of the identified squares in the actual exercise book are matched with the standard squares in the character motion model to determine the precise position and proportion of the virtual motion model in the actual exercise area. Specifically, the character motion model is scaled proportionally according to the actual size of the exercise squares specified by the user, so that the virtual motion model can accurately cover the user's writing area. In order to ensure that the squares in the virtual motion model are completely aligned with the exercise squares specified by the user, the character motion model can also be translated and rotated.

[0028] Step 104: Practice the character to be practiced based on the display position and character action model.

[0029] In one embodiment, based on the adapted display position, virtual effects corresponding to the character action model are played sequentially according to the correct stroke order, such as animations of hand movement trajectories, to guide the user to imitate the correct writing actions for character practice.

[0030] In one embodiment, after the user completes each stroke, the system can provide instant feedback on the user's practice performance, such as providing a score for each stroke and suggestions for improvement.

[0031] This disclosure determines the display position of the virtual motion model in the practice area based on the standard squares in the character motion model. Then, based on the display position and the character motion model, which includes the hand motion trajectory of a single character during writing in the standard squares, the learner can practice the character to be practiced. Learners can learn according to their own time and pace, and can also choose the characters to practice according to their own needs, thereby improving the spatiotemporal flexibility of character practice and realizing personalized teaching.

[0032] In one embodiment, such as Figure 2 As shown, character practice methods include: Step 201: Obtain multiple target character practice videos containing hand writing actions. The target character practice videos are practice videos for a single character. In one embodiment, the characters in this application can be text, numbers, symbols, or graphics. For ease of understanding, the characters in this application are exemplified by text.

[0033] In one embodiment, such as Figure 3 As shown, the target character practice videos all include clear hand movements and squares for standardized writing.

[0034] In one embodiment, calligraphy practice videos can be collected or recorded, and the videos can be cropped according to individual characters to obtain individual character calligraphy practice videos; alternatively, practice videos can be recorded separately for each character.

[0035] In one embodiment, a video recording of multiple target characters including handwriting actions can be recorded using professional camera equipment, or a portable device such as a smartphone can be used to record and acquire such a video.

[0036] In one embodiment, after obtaining the calligraphy practice video, characters can be selected. Typically, characters that cover common strokes are selected, so that practicing with a small number of characters can cover a large number of strokes, and can then be generalized to other characters.

[0037] Step 202: Input the target character practice video into the dynamic 3D reconstruction model to generate a dynamic 3D model containing hand movement trajectories; In one embodiment, the dynamic 3D reconstruction model can convert 2D video into a 3D dynamic model. In this application, the dynamic 3D reconstruction model refers to the 4D Gaussian Splatting (4D-GS) model. The 4D-GS model provides a solution to the complex motion simulation problem in dynamic scene rendering by introducing an efficient Gaussian deformation field network. This model consists of an efficient spatial-temporal structure encoder and a multi-head Gaussian deformation decoder, which can accurately adjust the spatial position and shape of 3D Gaussians. This allows it to capture and reproduce the motion trajectory and deformation of dynamic objects over time, such as the hand movement trajectory in this application, achieving accurate rendering of the continuity and coherence of each element in the scene over time.

[0038] In one embodiment, the target character practice video is input into a dynamic 3D reconstruction model, and the spatial-temporal structure encoder in the model is used to extract the temporal sequence features of the hand movements in the video; then, these features are parsed by a multi-head Gaussian deformable decoder to generate a dynamic 3D model containing the hand movement trajectory.

[0039] Step 203: Based on the standard squares in the exercise book, delete the dynamic 3D model to generate a character motion model, which includes hand motion trajectory and standard squares.

[0040] In one embodiment, the character action model is a dynamic three-dimensional model after removing redundant squares, retaining only information related to the writing of a specific character, including hand movement trajectory and standard squares.

[0041] In one embodiment, the character action model is used to guide calligraphy practice in an augmented reality environment.

[0042] In one embodiment, the positions of the squares in the model need to be manually drawn or adjusted to conform to the standard square layout on the actual exercise book.

[0043] In one embodiment, such as Figure 4 As shown, because the reconstructed exercise book in the 4D-GS model cannot remain level, and the squares on the reconstructed exercise book may be deformed, it is necessary to edit the dynamic 3D model and manually draw a square at the position of the exercise book for subsequent alignment with the real exercise book in the augmented reality scene. Figure 5 As shown, the rest of the 3D model is then deleted, leaving only the hand model and the aforementioned grid, thus obtaining the motion model for calligraphy practice.

[0044] In one embodiment, if the original reconstruction result is not refined enough, the dynamic 3D model can be completed and enhanced to improve the user experience in augmented reality.

[0045] In one embodiment, dynamic 3D reconstruction technology can accurately capture and reproduce the details of hand movements during the writing process. The generated character motion model can be used multiple times in different users and scenarios, reducing costs while improving the utilization rate of teaching resources.

[0046] In one embodiment, since each character has its own independent action model, customized practice content can be provided according to the progress and needs of different users, supporting more flexible and personalized learning.

[0047] In one embodiment, such as Figure 6 As shown, identifying squares in a workbook image and determining the area to be practiced includes: Step 601: Identify the squares in the exercise book image and use the first preset box to mark the borders of the squares to obtain the first square; In one embodiment, the first preset frame is a rectangular frame or boundary frame that performs preliminary border marking on the squares. It is usually a rectangular frame. After identifying the squares in the exercise image, the position and size of each square are determined, and the squares in the image are marked using the rectangular frame. Specifically, this can be achieved by drawing a rectangular outline on the squares in the exercise image.

[0048] In one embodiment, by using a first preset frame to mark the borders of the squares, the position and size of each square can be defined more clearly.

[0049] Step 602: Use the second preset frame to enhance the border of the first square to obtain the second square; In one embodiment, the second preset box is usually an enhancement box, that is, an enhancement box is drawn on the square after the rectangular box is marked. The enhancement box can be a simple border with thick lines, or a border with color or pattern, or other forms of visual enhancement border, so as to make the selected square more eye-catching and easy for the user to identify.

[0050] Step 603: Select the user-specified square from the second square as the practice area.

[0051] In one embodiment, the square specified by the user can be the square that the user can select in step 102 by gesture (such as pointing with a finger or pointing with the pen held by the user).

[0052] In one embodiment, when a user selects a square, the system identifies the user's designated area and retains the enhanced box of that area, while removing the enhanced boxes on other squares to ensure that the user's attention is focused on the selected area.

[0053] In one embodiment, by identifying the squares in the exercise book image and using a first preset box to mark the squares with borders, a first square is obtained; by using a second preset box to enhance the borders of the first square, a second square is obtained; and the square specified by the user is determined from the second square as the area to be practiced. Using two different preset boxes for border marking and enhancement can significantly improve the system's accuracy in recognizing squares.

[0054] In one embodiment, such as Figure 7 As shown, the practice area is adapted to the standard squares in the character motion model to determine the display position of the virtual motion model in the practice area, including: Step 701: Based on the size of the area to be practiced, scale the standard squares in the character action model to obtain scaled squares. In one embodiment, the size of the practice area refers to the actual size of the specific writing area selected by the user on the actual exercise book, which is typically the width and height of a square.

[0055] In one embodiment, standard squares in the character action model are used to define the boundaries of the writing.

[0056] In one embodiment, the size of the squares in the character motion model is adjusted according to the actual size of the area to be practiced, so that the virtual motion model can accurately cover the practice area specified by the user. Specifically, the actual width and height of the area to be practiced are first obtained, then the proportional relationship between the area and the standard squares in the character motion model is calculated, and finally, according to the proportional relationship, all elements (including hand motion trajectories) in the squares are scaled accordingly to adapt to the actual size of the area to be practiced.

[0057] Step 702: Align the scaled squares with the boundary of the area to be practiced to obtain the display position of the virtual motion model in the area to be practiced.

[0058] In one embodiment, the scaled square is geometrically transformed, such as translated or rotated, with respect to the boundary of the user's actual practice area to ensure complete overlap, thereby determining the display position of the virtual motion model in the practice area. Specifically, this can be achieved by detecting the positions of the four corner points of the practice area and then moving and rotating the scaled square to the positions defined by these corner points.

[0059] In one embodiment, the corresponding virtual motion model is scaled according to the condition that its squares are scaled proportionally to the size of the squares specified by the user, and the squares of the virtual motion model are aligned with the squares specified by the user, thereby determining the placement posture of the virtual motion model effects. After that, the effects can be played on the virtual motion model according to the stroke order.

[0060] In one embodiment, through scaling and alignment processing, the virtual motion model can accurately match the user's actual writing environment, providing more intuitive and accurate practice guidance.

[0061] In one embodiment, regardless of the user's exercise book specifications, customized calligraphy practice can be provided by adjusting it to meet the individual needs of different users.

[0062] In one embodiment, such as Figure 8 As shown, before adapting the area to be practiced to the standard squares in the character motion model to determine the display position of the virtual motion model in the area to be practiced, the character practice method also includes: Step 801: In response to the absence of a character action model corresponding to the character to be practiced in the resource database, perform a stroke decomposition process on the character to be practiced to obtain the strokes to be practiced corresponding to the character to be practiced. In one embodiment, before performing the stroke decomposition process on the character to be practiced, the character action model can be decomposed into multiple stroke actions according to strokes to obtain each stroke action model, and each stroke action model is imported into an AR engine, such as resource libraries (resource databases) like Unity, Unreal Engine, ARKit (iOS), ARCore (Android), etc., for subsequent display as virtual special effects in the scene. Among them, the decomposition of strokes can be manual decomposition, obtained by network retrieval, or input into a large language model to obtain the stroke decomposition of the character. The resource library is a database storing various characters and their corresponding character action models, and the virtual special effect refers to the animation corresponding to the aforementioned action model.

[0063] In one embodiment, a square at a specific orientation in the special effect display grid is used as the recognition area for the character to be practiced (such as a square on the left side of the special effect display grid). The user first writes the character to be practiced in this area, and then the AR device recognizes the character in this area and uses the recognized character as the character to be practiced. The special effect display grid refers to the grid that displays the animation corresponding to the character action model.

[0064] In one embodiment, performing a stroke decomposition process on the character to be practiced refers to the process of decomposing a complex character into its constituent basic strokes. For example, the Chinese character "中" can be decomposed into four basic strokes: vertical, horizontal fold, horizontal, and vertical.

[0065] Step 802: In response to the presence of an action model corresponding to the stroke to be practiced in the resource database, perform a recombination process on the action model corresponding to the stroke to be practiced in accordance with the decomposed stroke order to determine the virtual action model corresponding to the character to be practiced.

[0066] In one embodiment, according to the order of strokes, the action models of each individual stroke existing in the resource database are recombined into a complete character action model. Specifically, for a character not saved (the action model of this character is not saved in the resource library), perform a stroke decomposition, and match the decomposed strokes with the action strokes saved in the resource library. If each decomposed stroke can be matched with the same stroke action in the resource library, then combine the matched stroke actions in the order of the decomposed strokes to obtain the recombined action model. After that, determine the display position of the virtual action model and play it according to the method in the aforementioned steps 701 to step 702.

[0067] In one embodiment, in response to the absence of a character action model corresponding to the character to be practiced in the resource database, the character to be practiced is decomposed into strokes to obtain the corresponding strokes to be practiced. In response to the presence of an action model corresponding to the stroke to be practiced in the resource database, the action models corresponding to the strokes to be practiced are recombined according to the order of stroke decomposition to determine the virtual action model corresponding to the character to be practiced. Even if there is no complete character action model corresponding to the character to be practiced in the resource database, detailed practice guidance can still be provided to users through stroke decomposition and recombination techniques, greatly expanding the applicability and flexibility of the system. Furthermore, through decomposition and recombination, existing stroke action models can be fully utilized, reducing the need to repeatedly create action models for the same strokes, and improving the overall utilization rate of resources.

[0068] In one embodiment, after displaying a virtual motion model, the user imitates the model's movements to practice calligraphy. Each stroke of the written character is image-recognized and compared with standard strokes, including overlapping areas and color (strokes have varying shades of color depending on the pressure applied), and a corresponding score is given. When the score exceeds a threshold, the next stroke can be written, and the above steps are repeated until a single character is practiced. The standard strokes can be characters from an acquired target character practice video or from an existing standard font library.

[0069] In one embodiment, such as Figure 9 As shown, the practice of the character to be practiced is based on the display position and character action model, including: Step 901: Obtain the user's first stroke information for the character to be practiced; In one embodiment, the first writing stroke information includes information such as the stroke path, pressure, and area.

[0070] In one embodiment, existing image recognition algorithms, such as the YOLO algorithm, can be used to identify and obtain the user's first handwriting stroke information for the character to be practiced.

[0071] Step 902: Based on the first writing stroke information and the preset writing stroke information, determine the user's writing score for the character to be practiced; In one embodiment, the preset writing stroke information refers to the path, pressure, area, and other information of a pre-defined standard stroke, which serves as a comparison reference for evaluating the user's writing quality.

[0072] In one embodiment, based on the first writing stroke information and preset writing stroke information, the mathematical expression for determining the user's writing score for the character to be practiced is as follows:

[0073] Where S represents the score of the stroke, S1 represents the score of the overlapping area, S2 represents the color score, w1 represents the weight of S1, w2 represents the weight of S2; Sa represents the area of ​​the user's written stroke area occupied by the preset written stroke area, and St represents the area of ​​the preset written stroke. This represents the average color of the pixels in the area where the user wrote the strokes. This represents the average pixel color of a preset standard stroke. to The preset difference threshold is used, and the average color here can be a grayscale value.

[0074] Step 903: In response to the writing score not being lower than the preset scoring threshold, practice the second writing stroke of the character to be practiced based on the display position and character action model. The second writing stroke is the next writing stroke after the first writing stroke.

[0075] In one embodiment, the preset scoring threshold is a pre-set minimum passing score. Only when the user's writing score reaches or exceeds this threshold will the user be allowed to practice the next stroke, which serves as a condition for displaying the next stroke action.

[0076] In one embodiment, after obtaining the corresponding score, it is compared with a pre-set threshold S. Compare, when S is satisfied S You can then proceed to writing the next stroke until you have completed the practice of a single character.

[0077] In one embodiment, by evaluating a user's writing performance in real time and providing scoring feedback, users can identify their shortcomings in a timely manner, thereby quickly improving their writing skills.

[0078] In one embodiment, when the virtual motion model is displayed, the opacity of the virtual motion model can be set (the opacity is set to 50% by default) to avoid the virtual motion model obscuring the user's hand and to avoid affecting the user's normal experience.

[0079] In summary, the solution provided in this public disclosure is as follows: First, the display position of the virtual motion model in the practice area is determined based on the standard squares in the character motion model. Then, based on this display position and the character motion model, which contains the hand motion trajectory of a single character during the writing process in the standard squares, the learner can practice the character to be practiced. Learners can learn according to their own time schedule and pace, and can also choose the characters to practice according to their own needs, thereby improving the spatiotemporal flexibility of character practice and realizing personalized teaching.

[0080] Secondly, by identifying the squares in the exercise image and using a first preset box to mark the squares with borders, a first square is obtained; using a second preset box to enhance the borders of the first square, a second square is obtained; from the second square, the user-specified square is determined as the area to be practiced. Using two different preset boxes for border marking and enhancement can significantly improve the system's accuracy in recognizing squares.

[0081] Furthermore, in response to the absence of a character action model corresponding to the character to be practiced in the resource database, the character to be practiced is decomposed into strokes to obtain the corresponding strokes to be practiced. In response to the presence of an action model corresponding to the stroke to be practiced in the resource database, the action model corresponding to the stroke to be practiced is recombined according to the order of stroke decomposition to determine the virtual action model corresponding to the character to be practiced. Even if there is no complete character action model corresponding to the character to be practiced in the resource database, detailed practice guidance can still be provided to users through stroke decomposition and recombination technology, which greatly expands the applicability and flexibility of the system.

[0082] Furthermore, by evaluating users' writing performance in real time and providing feedback, users can identify their shortcomings in a timely manner and thus quickly improve their writing skills.

[0083] The following application example further illustrates the character practice method provided in this disclosure: like Figure 10 As shown, Figure 10 A flowchart illustrating the character practice method provided in this application example. The character practice method provided in this application example includes the following steps: Step 1001: Capture images of the user's practice notebook in real time; Step 1002: Identify the squares in the exercise book image and use the first preset box to mark the borders of the squares to obtain the first square; Step 1003: Use the second preset frame to enhance the border of the first square to obtain the second square; Step 1004: Determine the user-specified square from the second square as the practice area; Step 1005: Based on the size of the area to be practiced, the standard square in the character action model is scaled to obtain the scaled square. The character action model is a dynamic three-dimensional model containing the hand movement trajectory of a single character during the writing process of the standard square. Step 1006: Align the scaled squares with the boundary of the area to be practiced to obtain the display position of the virtual motion model in the area to be practiced; Step 1007: Obtain the user's first stroke information for the character to be practiced; Step 1008: Based on the first writing stroke information and the preset writing stroke information, determine the user's writing score for the character to be practiced; Step 1009: In response to the writing score not being lower than the preset scoring threshold, practice the second writing stroke of the character to be practiced based on the display position and character action model. The second writing stroke is the next writing stroke after the first writing stroke.

[0084] To implement the character practice method provided in this disclosure, this disclosure also provides a character practice device, such as... Figure 11 As shown. Figure 11 This is a schematic diagram of the structure of the character practice device provided in this embodiment of the disclosure. The character practice device 1100 includes: Acquisition unit 1101 is used to capture images of the user's practice book in real time; The recognition unit 1102 is used to recognize the squares in the exercise book image and determine the area to be practiced; The adaptation unit 1103 is used to adapt the practice area to the standard square in the character motion model in order to determine the display position of the virtual motion model in the practice area. The character motion model is a dynamic three-dimensional model containing the hand motion trajectory of a single character during the writing process of the standard square. Practice unit 1104 is used to practice the character to be practiced based on the display position and character action model.

[0085] In one embodiment, the character practice device 1100 further includes a model generation unit, which is used for: Obtain multiple target character practice videos that include handwriting actions; each target character practice video is a practice video for a single character. Input the target character practice video into the dynamic 3D reconstruction model to generate a dynamic 3D model containing hand movement trajectories; The dynamic 3D model is deleted based on the standard squares in the exercise book to generate a character motion model, which includes hand motion trajectory and standard squares.

[0086] In one embodiment, the acquisition unit 1101 is specifically used for: Identify the squares in the exercise book image and use a first preset box to mark the borders of the squares to obtain the first square; The first square is enhanced by using the second preset frame to obtain the second square; The user-specified square in the second square is selected as the practice area.

[0087] In one embodiment, the adapter unit 1103 is specifically used for: Based on the size of the area to be practiced, the standard squares in the character action model are scaled to obtain scaled squares. Align the scaled squares with the boundary of the area to be practiced to obtain the display position of the virtual motion model in the area to be practiced.

[0088] In one embodiment, the character practice device 1100 further includes a determining unit, which is configured to: In response to the absence of a character action model corresponding to the character to be practiced in the resource database, the character to be practiced is decomposed into strokes to obtain the corresponding strokes to be practiced. In response to the existence of an action model corresponding to the stroke to be practiced in the resource database, the action model corresponding to the stroke to be practiced is reorganized according to the stroke decomposition order to determine the virtual action model corresponding to the character to be practiced.

[0089] In one embodiment, the practice unit 1104 is specifically used for: Obtain the user's first stroke information for the character to be practiced; Based on the first writing stroke information and the preset writing stroke information, determine the user's writing score for the character to be practiced; In response to the writing score not being lower than the preset score threshold, the second writing stroke of the character to be practiced is performed based on the display position and character action model. The second writing stroke is the next writing stroke after the first writing stroke.

[0090] It should be noted that the character practice device provided in the above embodiments is only illustrated by the division of the above program modules when performing character practice. In actual applications, the above processing can be assigned to different program modules as needed, that is, the internal structure of the character practice device can be divided into different program modules to complete all or part of the processing described above. In addition, the character practice device provided in the above embodiments and the character practice method embodiments provided in this disclosure belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0091] Figure 12 This is a schematic diagram of the hardware composition structure of the electronic device provided in the embodiments of this disclosure, such as... Figure 12 As shown, the electronic device 1200 includes at least one processor 1202; and a memory 1201 communicatively connected to the at least one processor 1202; wherein the memory 1201 stores instructions executable by the at least one processor 1202, the instructions being executed by the at least one processor 1202 to implement the steps of the character practice method of the present disclosure embodiments.

[0092] Optionally, the electronic device may specifically be a character practice device according to the embodiments of this application, and the electronic device may implement the corresponding processes implemented by the character practice device in the various methods of the embodiments of this application. For the sake of brevity, it will not be described in detail here.

[0093] It is understood that the electronic device also includes a communication interface 1203. Various components in the electronic device are coupled together via a bus system 1204. It is understood that the bus system 1204 is used to implement communication between these components. In addition to a data bus, the bus system 1204 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 12 The general labeled all buses as Bus System 1204.

[0094] It is understood that memory 1201 can be volatile memory or non-volatile memory, or both. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), ferromagnetic random access memory (FRAM), flash memory, magnetic surface memory, optical disc, or compact disc read-only memory (CD-ROM); magnetic surface memory can be disk storage or magnetic tape storage. Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), SyncLink Dynamic Random Access Memory (SLDRAM), and Direct Rambus Random Access Memory (DRRAM).The memory 1201 described in the embodiments of the present invention is intended to include, but is not limited to, these and any other suitable types of memory.

[0095] The methods disclosed in the above embodiments can be applied to or implemented by the processor 1202. The processor 1202 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above methods can be completed by integrated logic circuits in the hardware of the processor 1202 or by instructions in software form. The processor 1202 may be a general-purpose processor, a DSP, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor 1202 can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the methods disclosed in the embodiments of this invention can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software modules may be located in a storage medium located in the memory 1201. The processor 1202 reads information from the memory 1201 and, in conjunction with its hardware, completes the steps of the aforementioned methods.

[0096] In an exemplary embodiment, the electronic device may be implemented by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), FPGAs, general-purpose processors, controllers, MCUs, microprocessors, or other electronic components to perform the aforementioned method.

[0097] This disclosure also provides a non-transitory computer-readable storage medium storing computer instructions, which are used to cause a computer to execute the steps of the character practice method of the present invention.

[0098] Optionally, the computer-readable storage medium can be applied to the character practice device in the embodiments of this application, and the computer instructions cause the computer to execute the corresponding processes implemented by the character practice device in the various methods of the embodiments of this application. For the sake of brevity, they will not be described in detail here.

[0099] This disclosure also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the character practice method provided in this embodiment of the invention.

[0100] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0101] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0102] In addition, in the various embodiments of the present invention, each functional unit can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0103] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0104] Alternatively, if the integrated units of this invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0105] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A character practice method, characterized in that, include: Real-time capture of images of the user's practice notebook; Identify the squares in the exercise book image and determine the area to be practiced; The practice area is adapted to the standard square in the character motion model to determine the display position of the virtual motion model in the practice area. The character motion model is a dynamic three-dimensional model containing the hand motion trajectory of a single character during the writing process in the standard square. The character to be practiced is practiced based on the display position and the character action model.

2. The method according to claim 1, characterized in that, The method includes: Acquire multiple target character practice videos that include handwriting actions, wherein the target character practice videos are practice videos for a single character; The target character practice video is input into the dynamic 3D reconstruction model to generate a dynamic 3D model containing hand movement trajectories; The dynamic 3D model is deleted based on the standard squares in the exercise book to generate a character motion model, which includes hand motion trajectories and standard squares.

3. The method according to claim 1, characterized in that, The step of identifying the squares in the exercise book image and determining the area to be practiced includes: Identify the squares in the exercise book image and use a first preset box to mark the squares with borders to obtain the first square; The first square is enhanced with a second preset frame to obtain the second square; The user-specified square is determined from the second square as the practice area.

4. The method according to claim 1, characterized in that, The step of adapting the area to be practiced to the standard squares in the character motion model to determine the display position of the virtual motion model in the area to be practiced includes: Based on the size of the area to be practiced, the standard squares in the character action model are scaled to obtain scaled squares. The scaled squares are aligned with the boundary of the area to be practiced to obtain the display position of the virtual motion model in the area to be practiced.

5. The method according to claim 2, characterized in that, Before adapting the practice area to a standard grid in the character motion model to determine the display position of the virtual motion model in the practice area, the method further includes: In response to the absence of a character action model corresponding to the character to be practiced in the resource database, the character to be practiced is decomposed into strokes to obtain the strokes to be practiced corresponding to the character to be practiced. In response to the existence of an action model corresponding to the stroke to be practiced in the resource database, the action model corresponding to the stroke to be practiced is reorganized according to the stroke decomposition order to determine the virtual action model corresponding to the character to be practiced.

6. The method according to claim 1, characterized in that, The practice of the character to be practiced based on the display position and the character action model includes: Obtain the user's first stroke information for the character to be practiced; Based on the first writing stroke information and the preset writing stroke information, the user's writing score for the character to be practiced is determined; In response to the writing score being no lower than a preset scoring threshold, practice is performed on the second writing stroke of the character to be practiced based on the display position and the character action model. The second writing stroke is the next writing stroke after the first writing stroke.

7. A character practice device, characterized in that, include: The acquisition unit is used to capture images of the user's practice book in real time; The recognition unit is used to identify the squares in the exercise book image and determine the area to be practiced; An adaptation unit is used to adapt the area to be practiced to the standard square in the character motion model in order to determine the display position of the virtual motion model in the area to be practiced. The character motion model is a dynamic three-dimensional model containing the hand motion trajectory of a single character during the writing process of the standard square. The practice unit is used to practice the character to be practiced based on the display position and the character action model.

8. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1 to 6.

10. A computer program product comprising a computer program that, when executed by a processor, implements the method of any one of claims 1 to 6.

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