Track capturing system for art teaching

Abstract

The invention discloses a trajectory capture system for art teaching, and relates to the technical field of education, the system comprises a plurality of modules, and the core module comprises a drawing trajectory acquisition, analysis, feedback and teaching resource module; the drawing track acquisition module is provided with a student drawing board and a painting brush, captures a drawing track in real time, positions pixel point changes through a two-dimensional coordinate system, and summarizes and fits to form a track coordinate set; the drawing track analysis module receives the data, accurately extracts key feature points and trend lines, compares the key feature points and the trend lines with a standard template, and judges abnormity by using an Euclidean distance and a closed region area; and the drawing teaching feedback module locks abnormal students, generates a comparison report, marks questions and provides modification suggestions. The drawing teaching resource module stores a standard template and an analysis method result; the system realizes real-time monitoring, accurate analysis and personalized feedback in the drawing process, provides efficient assistance for art teaching, improves the teaching pertinence and the learning effect of students, and promotes the inheritance and development of drawing skills.

Description

Technical Field

[0001] The present invention belongs to the field of educational technology, and in particular relates to a trajectory capturing system for art teaching. Background Art

[0002] In the process of painting creation and teaching, accurately capturing and analyzing the painting trajectory is of great significance. The painting trajectory reflects the painter's hand movements, creative ideas, and the way of handling lines and shapes. In traditional painting teaching, teachers mainly evaluate students' painting skills and progress by observing their paintings. However, this method cannot fully and accurately capture the subtle movements and trajectory changes of students during the painting process. With the development of technology, digital painting tools are becoming increasingly popular, and people's demand for intelligent and personalized painting teaching is also growing.

[0003] The existing problems mainly focus on the following aspects: it is often difficult for teachers to monitor and accurately evaluate the painting process of multiple students in real time. Students usually need to complete their works to know where the problem lies, resulting in delayed learning feedback and limited improvement of painting skills; in addition, the storage and retrieval of teaching resources lack systematicity, and standard painting templates and analysis methods are difficult to use efficiently. Based on this, this application proposes a trajectory capture system for art teaching. Summary of the Invention

[0004] In view of the shortcomings of the existing technology, the present invention provides a trajectory capture system for art teaching, which solves the problems of inaccurate analysis and delayed feedback in traditional art teaching in the existing technology.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] Trajectory capture system for art teaching, this system includes:

[0007] The drawing trajectory acquisition module, including a student drawing board, is provided to the student to acquire the student's drawing trajectory in real time during the drawing process, and transmit the acquired drawing trajectory to the drawing trajectory analysis module through the system bus for data analysis;

[0008] The drawing trajectory analysis module receives and analyzes the student's drawing trajectory collected by the drawing trajectory acquisition module, captures the key feature points and direction lines in the drawing trajectory, and compares them with the standard drawing template to extract abnormal key feature points and abnormal direction lines in the corresponding student's drawing trajectory, and locates the student with abnormal drawing behavior;

[0009] The drawing teaching feedback module generates a comparison report based on the abnormal key feature points and abnormal trend lines in the drawing trajectory of the corresponding student and the key feature points and trend lines in the standard drawing template, so that the student can compare and modify them;

[0010] The painting teaching resource module includes a database for storing a number of standard painting templates and the analysis method and analysis results described in any step of this solution.

[0011] As a further solution of the present invention, the drawing trajectory acquisition module also includes a student's brush for drawing on the student's drawing board.

[0012] As a further solution of the present invention, the specific method for the drawing trajectory acquisition module to obtain the drawing trajectory of the student in real time during the drawing process is:

[0013] The two-dimensional coordinate system associated with the student drawing board is constructed with the lower left corner of the student drawing board as the origin, the left edge of the student drawing board as the vertical axis, and the lower edge of the student drawing board as the horizontal axis;

[0014] The two-dimensional coordinate system includes a number of pixel points, each pixel point corresponds to a coordinate in the two-dimensional coordinate system;

[0015] Get the pixel value A preset by the teacher and use it as the background pixel value of the student's drawing board. If the pixel value of all pixels in the student's drawing board is A, it means that the current student has not drawn anything on the drawing board;

[0016] Real-time monitoring of any pixel point in the student drawing board of any student. If the pixel value of the pixel point changes, it means that the student is drawing in the student drawing board with the student brush. The pixel point with the changed pixel value and the corresponding coordinate in the two-dimensional coordinate system are extracted;

[0017] The coordinates of all pixel points whose pixel values ​​have changed are summarized to obtain the coordinate set of the drawing trajectory, which is recorded as C = C1, C2, ..., C j , where j is the total number of coordinates involved in the two-dimensional coordinate system corresponding to the student's painting trajectory;

[0018] Then fit the painting trajectory coordinate set to obtain the student's painting trajectory.

[0019] As a further solution of the present invention, the drawing trajectory analysis module captures key feature points and direction lines in the drawing trajectory and compares them with the standard drawing template in the following manner:

[0020] Extract the standard painting template MB corresponding to the students' painting from the painting teaching resource module;

[0021] Extract the key feature points and direction lines preset by the teacher in MB and summarize them into a key feature point set TZ = TZ1, TZ2, ..., TZ n And the trend line set XT=XT1,XT2,...,XT u ;

[0022] TZ1, TZ2, ..., TZ in the TZ n Represents n key feature points, the value of n is determined by the teacher, TZ m is any one in TZ, m is the counting index, 1≤m≤n;

[0023] XT1, XT2, ..., XT in the XT u Represents u different trend lines, the value of u is determined by the teacher, XT o is any one in XT, o is the counting index, 1≤o≤u;

[0024] Based on the determined student's drawing trajectory, the key feature points are obtained and recorded as the key feature point set TZ′=TZ′1,TZ′2,...,TZ′ n , TZ′ m is any one of TZ′;

[0025] Then obtain the direction line set XT′=XT′1,XT′2,...,XT′ associated with the student's drawing trajectory u , XT′ o is any one of XT′;

[0026] The key feature points are aligned with the coordinate system, and the subsequent processing method is determined based on the processing results of the key feature points.

[0027] As a further solution of the present invention, the steps of the drawing trajectory analysis module performing coordinate system alignment processing on the key feature points and determining a subsequent processing method based on the processing results of the key feature points include:

[0028] Obtain key feature points TZ from the key feature point set TZ and the key feature point set TZ′ respectively m and key feature point TZ′ m , and align TZ by spatial coordinates m With TZ′ m Align the coordinate system and calculate TZ m With TZ′ m Euclidean distance between

[0029] Will The Euclidean distance threshold D preset by the teacher yu Compare, if Then consider TZ′ m It is a normal key feature point, and the next key feature point will be determined.

[0030] like Then TZ′ m Considered as abnormal key feature points;

[0031] Repeat the above steps to record all abnormal key feature points;

[0032] If any two adjacent key feature points are normal key feature points, the trend line between the two adjacent key feature points is extracted and verified.

[0033] As a further solution of the present invention, the drawing trajectory analysis module verifies the direction lines in the following specific manner:

[0034] Get the corresponding trend line XT from the trend line set XT′ and the trend line set XT respectively o and the direction line XT′ o ;

[0035] XT o With XT′ o Fit to the same two-dimensional coordinate system, connect XT with short lines o With XT′ o The key feature points corresponding to the two ends form one or more closed areas, and the total area of ​​the closed areas is counted and recorded as

[0036] Get the closed area threshold S preset by the teacher yu ,Will With S yu Compare, if Determine XT′ o For abnormal direction lines;

[0037] like Determine XT′ o For normal direction lines.

[0038] As a further solution of the present invention, the specific method in which the drawing trajectory analysis module identifies students with abnormal drawing movements is as follows:

[0039] After the student finishes drawing, the student's drawing trajectory and the number of abnormal direction lines and abnormal key feature points determined in the drawing trajectory are extracted, and the threshold number of abnormal direction lines and abnormal key feature points preset by the instructor are obtained. If either the number of abnormal direction lines or the number of abnormal key feature points exceeds the threshold, the student is identified as a student with abnormal drawing behavior;

[0040] Otherwise, the student is locked as a student with normal painting actions.

[0041] As a further solution of the present invention, the specific method in which the painting teaching feedback module generates a comparison report for students to compare and modify is as follows:

[0042] Extract all abnormal trend lines and abnormal key feature points from the drawing trajectory after the student completes the drawing;

[0043] The abnormal trend lines and abnormal key feature points are marked with pixel values ​​A′ that are clearly distinguishable from the drawing trajectory and background pixel value A. A′ is determined by the instructor;

[0044] Extract the trend lines and key feature points corresponding to the abnormal trend lines and abnormal key feature points in the student's drawing trajectory from the standard drawing template MB, and mark them with pixel values ​​A″ that are clearly distinguishable from the drawing trajectory, background pixel values ​​A, and pixel values ​​A′. A″ is determined by the instructor.

[0045] At this point, the comparison report is generated and transmitted to the student's drawing board through the system bus for the student to compare and modify.

[0046] Beneficial effects of the present invention:

[0047] (1) This application can fully and accurately record every detail of the student's painting movements by equipping each student with a drawing board and obtaining the painting trajectory in real time. This helps teachers fully understand the student's operations during the painting process, including the trajectory changes of each link such as starting, moving, and ending the brush. Secondly, by extracting key feature points and direction lines and analyzing them, it can effectively identify students with abnormal painting movements. By fitting abnormal key feature points and abnormal direction lines with normal key feature points and normal direction lines, it can clearly point out the painting trajectories that need to be corrected and modified for students, thereby helping students to make targeted modifications and exercises, which helps to improve the teaching quality.

[0048] (2) This application combines scientific analysis methods such as coordinate system alignment processing of key feature points, Euclidean distance comparison, and direction line verification, making the analysis of painting trajectories more objective and accurate, reducing the interference of human factors, and ensuring the fairness and reliability of teaching evaluation; in addition, the system can also record abnormal key feature points and abnormal direction lines, providing data support for subsequent teaching research and student progress tracking, which helps to continuously improve teaching methods and strategies, better meet the personalized learning needs of students, and promote the improvement of students' painting skills. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The present invention will be further described below with reference to the accompanying drawings.

[0050] Figure 1 It is a structural diagram of the system of the present invention;

[0051] Figure 2 Schematic diagram of the process of the method described in Example 2 of the present invention;

[0052] Figure 3 Schematic diagram of the process of the method described in Example 3 of the present invention. DETAILED DESCRIPTION

[0053] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 any creative efforts shall fall within the scope of protection of the present invention.

[0054] Example 1

[0055] Trajectory capture system for art teaching, such as Figure 1 As shown, specifically including the following:

[0056] A drawing trajectory acquisition module for real-time acquisition of students' drawing trajectories, including a student drawing board. The board uses high-precision pressure sensing and coordinate positioning technology to accurately capture every subtle movement of the student's pen tip on the board, including the weight, direction, and speed of the brushstrokes, thereby fully recording the student's drawing trajectory.

[0057] During the student's painting process, the student's drawing board will transmit the collected painting trajectory to the painting trajectory analysis module through the system bus;

[0058] In addition to the student drawing board, this module also includes a student brush for painting on the student drawing board. The student brush is matched with the student drawing board. A painting track will only be generated when the student brush touches the student drawing board, thereby preventing students from accidentally touching the board during the painting process.

[0059] The drawing trajectory analysis module receives the student's drawing trajectory collected by the drawing trajectory collection module and extracts key feature points and direction lines from the student's drawing trajectory. The key feature points are important feature points calibrated by the instructor and required to be reflected by the student during the drawing process. The direction lines are the connecting parts between two adjacent key feature points.

[0060] The student's drawing trajectory is then compared and analyzed with the standard drawing template to identify the student with abnormal drawing. The abnormal key feature points and abnormal direction lines are extracted from the drawing trajectory of the student with abnormal drawing and recorded.

[0061] The drawing teaching feedback module extracts abnormal key feature points and abnormal direction lines from the drawing trajectory of the determined abnormal drawing student, combines them with the corresponding key feature points and direction lines in the standard drawing template, and generates a comparison report associated with the student's current drawing trajectory. The comparison report clearly identifies the flawed parts of the student's drawing for comparison and modification;

[0062] The canvas size of the standard painting template is the same as the canvas size of the student's tablet, so that a coordinate system can be constructed to locate the pixel points within the same size canvas.

[0063] The painting teaching resource module contains a complete database for storing several standard painting templates. Teachers can select from several standard painting templates when issuing painting tasks and specify the corresponding key feature points;

[0064] At the same time, the database is also used to store the analysis methods used in each step of this solution, such as painting trajectory collection, analysis, and teaching feedback, as well as the analysis result data generated, providing data support for the continuous optimization and improvement of the system.

[0065] The purpose of this system is to obtain the painting trajectory of students during the painting process through the painting trajectory acquisition module, capture the key feature points and direction lines in the painting trajectory analysis module and compare them with the standard painting template, and then use the painting teaching feedback module to identify students with abnormal painting movements and generate a comparison report. With the help of the painting teaching resource module, standard painting templates are stored to improve students' painting skills, help them correct mistakes, improve teaching effects and quality, and make art teaching more scientific, efficient and personalized.

[0066] Example 2

[0067] This embodiment further discloses a method for determining abnormal trend lines and abnormal key feature points from the student's drawing trajectory based on embodiment 1, such as Figure 2 As shown, specifically including the following:

[0068] Before obtaining the student's drawing trajectory, it is necessary to determine when the student is drawing on the student's drawing board. This solution provides the following method for determining the student's drawing trajectory:

[0069] Based on the determined student drawing board, obtaining an original image of the student drawing board when the student is not drawing, wherein the background pixel value in the original image is a pixel value A preset by the instructor;

[0070] The pixel point corresponding to the lower left corner of the student's drawing board is used as the origin of the two-dimensional coordinate system, the left edge of the student's drawing board is used as the vertical axis of the two-dimensional coordinate system, and the lower edge of the student's drawing board is used as the horizontal axis of the two-dimensional coordinate system to construct the two-dimensional coordinate system associated with the student's drawing board;

[0071] At this point, the position of any pixel in the student's drawing board can be expressed by coordinates in a two-dimensional coordinate system.

[0072] Monitor the pixel value of any pixel in the student's drawing board in real time. If the pixel value of any pixel changes, that is, the pixel value of the pixel is not equal to the pixel value A preset by the operator, it means that the student is drawing on the student's drawing board with the student's brush. Extract all the pixel points with changed pixel values ​​and the coordinates of all the pixel points with changed pixel values ​​in the two-dimensional coordinate system;

[0073] By summarizing the acquired coordinates and sorting the summarized coordinates according to the time sequence of the pixel value change, we can finally get the drawing trajectory coordinate set, which is denoted as C, specifically expressed as C = C1, C2, ..., C j , where j is the number of all coordinates involved in the constructed two-dimensional coordinate system corresponding to the student's painting trajectory;

[0074] By fitting the drawing trajectory coordinate set C, the student's drawing trajectory can be obtained.

[0075] As can be seen from Example 1, the canvas size of the student's drawing board is the same as the canvas size of the standard painting template. It can be understood that under ideal conditions, the more standard the student's drawing is, the more consistent it is with the standard painting template. Based on this principle, the drawing trajectory of the student's drawing can be compared and analyzed with the standard painting template to determine the abnormal direction lines and abnormal key feature points in the drawing trajectory of the student's drawing, as follows:

[0076] Extract the current student's drawing trajectory from the drawing teaching resource module, and the standard drawing template corresponding to the student's drawing trajectory issued by the instructor, and record the standard drawing template as MB;

[0077] Students need to use the standard drawing template MB as a reference and draw the number of key feature points and direction lines that are consistent with the standard drawing template MB;

[0078] The standard drawing template MB already contains pre-set key feature points and direction lines. The instructor can also determine the key feature points and direction lines that students will use when drawing with reference to the standard drawing template MB based on actual conditions. The instructor can extract the key feature points and direction lines preset by the instructor from the standard drawing template MB and summarize them into a key feature point set TZ and a direction line set XT.

[0079] The key feature point set TZ is expressed as: TZ = TZ1, TZ2, ..., TZ n ;

[0080] The trend line set XT is expressed as: XT = XT1, XT2, ..., XT u ;

[0081] Among them, TZ1, TZ2, ..., TZ in the key feature point set TZ n They represent n different key feature points, and the value of n is determined by the operator in combination with the characteristics of the standard painting template MB, which is the number of original key feature points of the standard painting template MB. The key feature point TZ is specified. m is any one of the key feature point set TZ, m is a counting index, and the value range of m is 1 to n, including 1 and n;

[0082] XT1, XT2, ..., XT in the trend line set XT u Represents u different trend lines, the value of u is determined by the teacher in combination with the characteristics of the standard painting template MB, and the designated trend line XT o is any one of the trend line set XT, and o is a counting index ranging from 1 to u, including 1 and u.

[0083] The relationship between the key feature points and the trend lines is that both ends of each trend line are connected to the key feature points, that is, the key feature points and the trend lines are connected end to end.

[0084] Then extract the key feature points in the drawing trajectory of any student, summarize them, and record them as the key feature point set TZ′ associated with the student's drawing trajectory, expressed as TZ′=TZ′1,TZ′2,...,TZ′ n , and specify TZ′ m is any one of the key feature point set TZ′;

[0085] Similarly, we obtain the set of trend lines associated with the student's drawing trajectory XT′=XT′1,XT′2,...,XT′ u , and specify XT′ o is the set of trend lines XT′1,XT′2,...,XT′ u Any one of;

[0086] First, we process the key feature point set. The reason is that if the position of the key feature point is greatly deviated from the drawing, the deviation of the direction line drawn will also be greatly deviated. Based on this, we first give the processing method of the key feature point set:

[0087] Through the above steps, the key feature point set TZ determined in the standard painting template MB and the key feature point set TZ′ extracted from the drawing trajectory of the student drawing with reference to the standard painting template MB can be obtained;

[0088] Get any key feature point TZ′ in the key feature point set TZ′ m , and the key feature point TZ′ m The corresponding key feature point TZ in the key feature point set TZ m , further extract key feature points TZ′ m And the key feature point TZ m The coordinates of each in the two-dimensional coordinate system, and the key feature points TZ are aligned by spatial coordinates m and key feature point TZ′ m The coordinates corresponding to each point are aligned so that the coordinates corresponding to the two key feature points can be fitted into the same two-dimensional coordinate system;

[0089] Use the Euclidean distance calculation formula to calculate the key feature point TZ m and key feature point TZ′ m The Euclidean distance between the corresponding coordinates is recorded as

[0090] Then obtain the Euclidean distance threshold D preset by the teacher yu , the Euclidean distance The Euclidean distance threshold D preset by the teacher yu For comparison, if the Euclidean distance Less than the Euclidean distance threshold D yu Then the key feature point TZ′ m It is a normal key feature point, and the next key feature point will be determined.

[0091] If the Euclidean distance Greater than or equal to the Euclidean distance threshold D preset by the teacher yu , then determine the key feature point TZ′ m With key feature point TZ m There is a big difference between them, so the key feature point TZ′ m Considered as abnormal key feature points;

[0092] Repeat the above steps of determining abnormal key feature points until all key feature points of the student's painting are determined, and record the abnormal key feature points and normal key feature points respectively;

[0093] If any two adjacent key feature points are normal key feature points, the trend line between the two adjacent key feature points is extracted and recorded as the trend line XT′ o , and then extract the trend line XT′ from the trend line set XT o Corresponding trend line XT o ;

[0094] Use the space coordinate alignment method to move the line XT' o And the line XT o Fit to the same two-dimensional coordinate system, and then use short lines to connect the direction lines XT o and the trend line XT′ o The key feature points corresponding to both ends, such as the line XT′ o And the line XT o The key feature points at the bottom are connected with short lines, and then the trend line XT′ o And the line XT o The key feature points at the top are connected by short lines;

[0095] At this point, go to line XT o , towards line XT′ o and two connecting strike lines XT′ o And the line XT o The short lines of the key feature points at both ends together form one or more closed areas. The area of ​​the closed area is counted and recorded as

[0096] Extract the closed area threshold S preset by the teacher yu , will go to line XT o and the trend line XT′ o The area of ​​the associated enclosed area and the closed area threshold S yu Compare, if the closed area Greater than or equal to the closed area threshold S yu , then it is considered that the direction line XT′ in the student's drawing trajectory o The corresponding trend line XT in the standard painting template MB o The difference between them is large, which is regarded as an abnormal trend line;

[0097] If the enclosed area Smaller than the closed area threshold S yu , then it is considered that the direction line XT′ in the student's drawing trajectory o For normal trend lines, record normal trend lines and abnormal trend lines.

[0098] Example 3

[0099] This embodiment further discloses a method for locking students with abnormal drawing movements and generating a comparison report based on the embodiment 1 and the embodiment 2. Figure 3 As shown, the specific steps include:

[0100] This embodiment needs to be implemented after the student has finished drawing. First, the complete drawing trajectory of the student's drawing needs to be extracted. Then, based on the method described in Example 2, the number of abnormal direction lines and the number of abnormal key feature points determined in the drawing trajectory need to be extracted. Then, the threshold value of the number of abnormal direction lines and the number of abnormal key feature points preset by the instructor are obtained.

[0101] Comparing the determined number of abnormal trend lines and abnormal key feature points in the drawing trajectory with the threshold number of abnormal trend lines and the threshold number of abnormal key feature points preset by the instructor respectively;

[0102] If either the number of abnormal lines or the number of abnormal key feature points in the drawing trajectory exceeds the threshold preset by the instructor, the student will be identified as having abnormal drawing behavior;

[0103] If the number of abnormal lines and abnormal key feature points in the drawing trajectory does not exceed the thresholds preset by the instructor, the student is considered to have normal drawing movements;

[0104] Then, all abnormal trend lines and abnormal key feature points are extracted from the student's drawing trajectory, and the determined abnormal trend lines and abnormal key feature points are color-labeled with pixel values ​​A' that are clearly distinguishable from the background pixel values ​​A and the pixel values ​​of the drawing trajectory. The specific value of pixel value A' is determined by the instructor based on the actual situation.

[0105] At this point, the abnormal key feature points and abnormal trend lines after color annotation in the drawing trajectory are obtained, and then the trend lines and key feature points corresponding to the abnormal trend lines and abnormal key feature points in the student's drawing trajectory are intercepted from the standard drawing template MB, and the coordinates of the trend lines and key feature points corresponding to the abnormal trend lines and abnormal key feature points in the student's drawing trajectory in the standard drawing template MB are further obtained. The trend lines and key feature points in the standard drawing template MB are annotated in the two-dimensional coordinate system where the abnormal key feature points and abnormal trend lines are located by coordinate positioning. The trend lines and key feature points in the standard drawing template MB are annotated with pixel values ​​A″ that are clearly distinguishable from the drawing trajectory, background pixel values ​​A, and pixel values ​​A′. The pixel value A″ is determined by the instructor based on actual conditions.

[0106] At this point, the portion marked as pixel value A′ is the portion of the student’s drawing trajectory that needs to be corrected, and the portion marked as pixel value A″ is the reference for the portion of the student’s drawing trajectory that needs to be corrected;

[0107] At this point, the comparison report is generated and the painting teaching feedback module transmits the comparison report to the student's drawing board through the system bus. The student modifies his or her own painting trajectory with reference to the comparison report.

[0108] This embodiment aims to identify abnormal students by comparing the number of abnormal lines and key feature points in the student's drawing trajectory with the instructor's preset threshold, and then extracting these abnormal elements and color-labeling them; then, the corresponding part is cut out from the standard drawing template, similarly labeled and placed in the same coordinate system, which serves as a reference for the student's drawing modification. Finally, the comparison report is transmitted to the student's drawing board to assist the student in independently correcting drawing errors, thereby improving the quality of drawing teaching and the student's independent learning ability.

[0109] Example 4

[0110] As embodiment 4 of the present invention, the methods described in embodiment 2 and embodiment 3 are combined for implementation.

[0111] Some of the data in the formulas described above are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0112] The above contents are merely examples and explanations of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in similar ways. As long as they do not deviate from the invention or exceed the scope defined by the claims, they should all fall within the scope of protection of the present invention.

[0113] It is important to note that all user data collected in this application is collected with the user's consent and authorization. Furthermore, the use of user data is legal and compliant, and the use and processing of user data complies with the relevant laws, regulations, and standards of the relevant regions.

Claims

1. A trajectory capture system for art teaching, characterized in that: This system includes: The drawing trajectory acquisition module, including a student drawing board, is provided to the student to acquire the student's drawing trajectory in real time during the drawing process, and transmit the acquired drawing trajectory to the drawing trajectory analysis module through the system bus for data analysis; The drawing trajectory analysis module receives and analyzes the student's drawing trajectory collected by the drawing trajectory acquisition module, captures the key feature points and direction lines in the drawing trajectory, and compares them with the standard drawing template to extract abnormal key feature points and abnormal direction lines in the corresponding student's drawing trajectory, and locates the student with abnormal drawing behavior; The drawing teaching feedback module generates a comparison report based on the abnormal key feature points and abnormal trend lines in the drawing trajectory of the corresponding student and the key feature points and trend lines in the standard drawing template, so that the student can compare and modify them; The painting teaching resource module includes a database for storing a number of standard painting templates and the analysis method and analysis results described in any step of this solution.

2. The art teaching trajectory capture system according to claim 1, characterized in that: The drawing trajectory acquisition module also includes a student's brush for drawing on the student's drawing board.

3. The art teaching trajectory capture system according to claim 2, characterized in that: The specific method for the drawing trajectory acquisition module to obtain the drawing trajectory of the student in real time during the drawing process is: The two-dimensional coordinate system associated with the student drawing board is constructed with the lower left corner of the student drawing board as the origin, the left edge of the student drawing board as the vertical axis, and the lower edge of the student drawing board as the horizontal axis; The two-dimensional coordinate system includes a number of pixel points, each pixel point corresponds to a coordinate in the two-dimensional coordinate system; Get the pixel value A preset by the teacher and use it as the background pixel value of the student's drawing board. If the pixel value of all pixels in the student's drawing board is A, it means that the current student has not drawn anything on the drawing board; Real-time monitoring of any pixel point in the student drawing board of any student. If the pixel value of the pixel point changes, it means that the student is drawing in the student drawing board with the student brush. The pixel point with the changed pixel value and the corresponding coordinate in the two-dimensional coordinate system are extracted; The coordinates of all pixel points whose pixel values ​​have changed are summarized to obtain the coordinate set of the drawing trajectory, which is recorded as C = C1, C2, ..., C j , where j is the total number of coordinates involved in the two-dimensional coordinate system corresponding to the student's painting trajectory; Then fit the painting trajectory coordinate set to obtain the student's painting trajectory.

4. The art teaching trajectory capture system according to claim 3, characterized in that: The specific method of the drawing trajectory analysis module to capture key feature points and direction lines in the drawing trajectory and compare them with the standard drawing template is as follows: Extract the standard painting template MB corresponding to the students' painting from the painting teaching resource module; Extract the key feature points and direction lines preset by the teacher in MB and summarize them into a key feature point set TZ = TZ1, TZ2, ..., TZ n And the trend line set XT=XT1,XT2,...,XT u ; TZ1, TZ2, ..., TZ in the TZ n Represents n key feature points, the value of n is determined by the teacher, TZ m is any one in TZ, m is the counting index, 1≤m≤n; XT1, XT2, ..., XT in the XT u Represents u different trend lines, the value of u is determined by the teacher, XT o is any one in XT, o is the counting index, 1≤o≤u; Based on the determined student's drawing trajectory, the key feature points are obtained and recorded as the key feature point set TZ′=TZ′1,TZ′2,...,TZ′ n , TZ′ m is any one of TZ′; Then obtain the direction line set XT′=XT′1,XT′2,...,XT′ associated with the student's drawing trajectory u , XT′ o is any one of XT′; The key feature points are aligned with the coordinate system, and the subsequent processing method is determined based on the processing results of the key feature points.

5. The art teaching trajectory capture system according to claim 4, characterized in that: The drawing trajectory analysis module performs coordinate system alignment processing on the key feature points and determines the subsequent processing method based on the processing results of the key feature points, including the following steps: Obtain key feature points TZ from the key feature point set TZ and the key feature point set TZ′ respectively m and key feature point TZ′ m , and align TZ by spatial coordinates m and TZ′ m Align the coordinate system and calculate TZ m and TZ′ m Euclidean distance between Will The Euclidean distance threshold D preset by the teacher yu Compare, if Then consider TZ′ m It is a normal key feature point, and the next key feature point will be determined. like Then TZ′ m Considered as abnormal key feature points; Repeat the above steps to record all abnormal key feature points; If any two adjacent key feature points are normal key feature points, the trend line between the two adjacent key feature points is extracted and verified.

6. The art teaching trajectory capture system according to claim 5, characterized in that: The specific method of verifying the direction lines in the drawing trajectory analysis module is as follows: Get the corresponding trend line XT from the trend line set XT′ and the trend line set XT respectively o and the direction line XT′ o ; XT o With XT′ o Fit to the same two-dimensional coordinate system, connect XT with short lines o With XT′ o The key feature points corresponding to the two ends form one or more closed areas, and the total area of ​​the closed areas is counted and recorded as Get the closed area threshold S preset by the teacher yu ,Will With S yu Compare, if Determine XT′ o For abnormal direction lines; like Determine XT′ o For normal direction lines.

7. The art teaching trajectory capture system according to claim 6, characterized in that: The specific method by which the drawing trajectory analysis module identifies students with abnormal drawing movements is as follows: After the student finishes drawing, the student's drawing trajectory and the number of abnormal direction lines and abnormal key feature points determined in the drawing trajectory are extracted, and the threshold number of abnormal direction lines and abnormal key feature points preset by the instructor are obtained. If either the number of abnormal direction lines or the number of abnormal key feature points exceeds the threshold, the student is identified as a student with abnormal drawing behavior; Otherwise, the student is locked as a student with normal painting actions.

8. The art teaching trajectory capturing system according to claim 7, characterized in that: The specific method for the painting teaching feedback module to generate a comparison report for students to make comparison and modifications is as follows: Extract all abnormal trend lines and abnormal key feature points from the drawing trajectory after the student completes the drawing; The abnormal trend lines and abnormal key feature points are marked with pixel values ​​A′ that are clearly distinguishable from the drawing trajectory and background pixel value A. A′ is determined by the instructor; Extract the trend lines and key feature points corresponding to the abnormal trend lines and abnormal key feature points in the student's drawing trajectory from the standard drawing template MB, and mark them with pixel values ​​A″ that are clearly distinguishable from the drawing trajectory, background pixel values ​​A, and pixel values ​​A′. A″ is determined by the instructor. At this point, the comparison report is generated and transmitted to the student's drawing board through the system bus for the student to compare and modify.

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