Intelligent training method and system for virtual dance training

Abstract

The invention discloses an intelligent training method and system for virtual dance training, and relates to the technical field of intelligent training.The intelligent training method comprises the steps of 1, pairing analysis of dance trainees and tutors, 2, action analysis of the dance trainees and 3, optimization and suggestion processing of dance training. Therefore, the influence of overlarge body type between the dancing student and the dancing tutor is reduced, the occurrence rate of the problem that the dancing student is damaged in order to forcibly reach the indexes of actions made by the dancing tutor is reduced, and the problem type of each problem monitoring time point of the dancing student is specifically analyzed, so that the problem is solved. The motion deviation problem of the dancer is divided into the beat error problem and the motion error problem, so that the dancer can conveniently adjust according to the actual error problem, and the learning efficiency of the dancer is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent training, and particularly relates to an intelligent training method and system for virtual dance training. Background Art

[0002] In traditional dance teaching, it mainly relies on on-site guidance by coaches and repeated practice by trainees. Trainees not only cannot obtain real-time action correction suggestions, resulting in low learning efficiency, but also the resources of professional dance coaches are limited, and the one-on-one training fees are expensive. Therefore, it is necessary to study an intelligent training method for virtual dance training to save training costs and improve learning efficiency.

[0003] Existing technologies such as a dance and physical training asynchronous tutoring and evaluation method and system disclosed in the invention patent application with the publication number of CN114463148A, the method includes: an equipment end, a collection module, a transmission module, a cloud platform, a control terminal, and a user end. The technical solution of this invention solves the problems of the existing teaching mode, such as inability to teach in a timely manner and low teaching quality and efficiency due to teaching environment, human reasons, and lack of teaching staff. Another existing technology is a dance training assistance system and method disclosed in the invention patent application with the publication number of CN113521711A, the system includes: receiving an editing operation on a dance action segment to obtain a new dance action combination; performing matching analysis on the new dance action combination and the music to determine whether there are errors. This invention enables students to reorganize the single actions included in the currently learned dance and conveniently obtain dance actions suitable for training, which helps students improve the proficiency of each single action and increases the training fun.

[0004] In view of the above solutions, the current intelligent training methods for virtual dance training lack certain attention to the intelligent selection of suitable dance tutors. The data such as the body types of dance trainees and dance tutors are often inconsistent. When the body types differ greatly, it is difficult for dance trainees to reach the action indicators made by dance tutors. If they forcefully reach the action indicators made by dance tutors, it is easy to cause injuries to dance trainees. Moreover, when analyzing the action deviation between dance trainees and dance tutors, there is often a problem that the actions of dance trainees are correct but are frequently misjudged as incorrect due to the large difference in body type, which dampens the enthusiasm of dance trainees. At the same time, there is a lack of certain attention to the intelligent judgment of whether dance trainees have action problems or beat problems. Traditional virtual dance training methods often only judge the action errors of dance trainees and lack the judgment of whether dance trainees have beat errors, thus reducing the learning efficiency of dance trainees. Summary of the Invention

[0005] The purpose of the present invention is to provide an intelligent training method and system for virtual dance training, which solves the problems existing in the background art.

[0006] To solve the above technical problems, the present invention adopts the following technical solutions: In the first aspect of the present invention, an intelligent training method for virtual dance training is provided, including: Step 1. Pairing and analysis of dance students and tutors: After the dance students wear each training device at the corresponding positions on their bodies, they pose each action according to the voice prompts, obtain the spatial relative coordinates of each training device to which the dance students belong in each action, and analyze the suitable tutors for the dance students based on this.

[0007] Step 2. Analysis of dance students' actions: When the dance students follow the corresponding suitable tutors for dance training, obtain the dance spatial relative coordinates of each training device of the dance students at each monitoring time point, and analyze the problem monitoring time points of the dance students.

[0008] Step 3. Processing of optimization suggestions for dance training: Analyze the problem types of each problem monitoring time point of the dance students, so as to screen out each beat problem monitoring time point and each action problem monitoring time point of the dance students, and give the dance students reminders for action adjustment.

[0009] In the second aspect of the present invention, an intelligent training system for executing the above-mentioned intelligent training method for virtual dance training is provided, including: A pairing and analysis module for dance students and tutors, which is used for, after the dance students wear each training device at the corresponding positions on their bodies, posing each action according to the voice prompts, obtaining the spatial relative coordinates of each training device to which the dance students belong in each action, and analyzing the suitable tutors for the dance students based on this.

[0010] A dance student action analysis module, which is used for obtaining the dance spatial relative coordinates of each training device of the dance students at each monitoring time point when the dance students follow the corresponding suitable tutors for dance training, and analyzing the problem monitoring time points of the dance students.

[0011] A dance training optimization suggestion processing module, which is used for analyzing the problem types of each problem monitoring time point of the dance students, so as to screen out each beat problem monitoring time point and each action problem monitoring time point of the dance students, and giving the dance students reminders for action adjustment.

[0012] The beneficial effects of the present invention are as follows: (1) In step 1 of the present invention, the dance trainee is paired with the instructor for analysis. After the dance trainee wears each training equipment at the corresponding position on the body and poses each action according to the voice prompt, according to the X-axis, Y-axis, and Z-axis action coordinates when the dance trainee performs each action, the appropriate instructor for the dance trainee is intelligently matched, thereby reducing the influence of too large a body size difference between the dance trainee and the dance instructor, reducing the incidence of problems where the dance trainee is injured in order to forcibly meet the action indicators made by the dance instructor, and when analyzing the action deviation between the dance trainee and the dance instructor, reducing the incidence of problems where the dance trainee's action is correct but is frequently misjudged as incorrect due to a large body size difference, thereby improving the accuracy of judgment.

[0013] (2) In step 2 of the present invention, the dance trainee's action analysis is carried out. By analyzing whether there are large action deviations in the dance trainee's dance actions, it is convenient to give suggestions to the dance trainee subsequently.

[0014] (3) In step 3 of the present invention, the dance training optimization suggestion processing is carried out. By specifically analyzing the problem types at each problem monitoring time point of the dance trainee, the action deviation problems of the dance trainee are divided into beat error problems and action error problems, which is convenient for the dance trainee to adjust according to the actual error problems, thereby improving the learning efficiency of the dance trainee. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0016] Figure 1 It is a schematic flow chart of the method of the present invention.

[0017] Figure 2 It is a schematic diagram of the system module of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0019] Refer to Figure 1As shown in the figure, the first aspect of the present invention provides an intelligent training method for virtual dance training, including: Step 1. Pairing and analysis of dance trainees and tutors: After the dance trainees wear each training equipment to the corresponding positions on their bodies, they pose each action according to the voice prompts, obtain the spatial relative coordinates of each training equipment of the dance trainees in each action, and analyze the suitable tutors for the dance trainees based on this.

[0020] It should be noted that each of the training equipment, such as various knee pads, elbow pads, headbands and other equipment, has built-in sensors and is worn at the joints and on the forehead.

[0021] It should also be noted that the actions include: normal standing, raising both arms vertically, raising both arms parallel, etc.

[0022] In a specific embodiment of the present invention, for the acquisition of the spatial relative coordinates of each training equipment of the dance trainees in each action, the specific analysis method is: Obtain the target training equipment and each of the remaining training equipment from the local database, obtain the spatial geographical coordinates of the target training equipment of the dance trainees in each action, and take the spatial geographical coordinates of the target training equipment of the dance trainees as the origin to establish a spatial rectangular coordinate system. Record the spatial relative coordinates of the target training equipment of the dance trainees in each action as (0, 0, 0). Through a three-dimensional space sensor, obtain the spatial coordinates of each of the remaining training equipment of the dance trainees in each action relative to the target training equipment within the spatial rectangular coordinate system, and mark them as the spatial relative coordinates of each of the remaining training equipment of the dance trainees in each action.

[0023] It should be noted that the local database is used to store the target training equipment and each of the remaining training equipment, the spatial relative coordinates of each training tutor and their training equipment in each action, the action deviation coefficient threshold, the comparison spatial relative coordinates of the suitable tutor for each training equipment at each monitoring time point, the allowable deviation value of the X-axis action at each monitoring time point corresponding to each action similarity coefficient interval, and the beat problem analysis time period of each problem monitoring time point.

[0024] It should also be noted that the target training equipment is the training equipment worn on the forehead, and each of the remaining training equipment is the training equipment worn at the joints.

[0025] Summarize the spatial relative coordinates of each training equipment of the dance trainees in each action.

[0026] In a specific embodiment, for the acquisition of the spatial geographical coordinates of the target training equipment of the dance trainees in each action, the specific acquisition method is: Obtain the spatial geographical coordinates of the target training equipment of the dance trainees in each action through a spatial positioning sensor.

[0027] In a specific embodiment, the method for establishing a spatial rectangular coordinate system is as follows: The target training device is internally equipped with a micro gyroscope. The true north direction in the vertical direction, the true north direction and the true east direction in the parallel direction are obtained from the gyroscope. The true north direction in the vertical direction is used as the positive direction of the Z-axis of the spatial rectangular coordinate system, the true north direction in the parallel direction is used as the positive direction of the X-axis of the spatial rectangular coordinate system, and the true east direction in the parallel direction is used as the positive direction of the Y-axis of the spatial rectangular coordinate system.

[0028] In a specific embodiment of the present invention, the method for analyzing the suitable tutor for a dance student is as follows: The spatial relative coordinates of each training tutor and their respective training devices for each movement are obtained from the local database. Based on the spatial relative coordinates of the training devices to which the dance student belongs for each movement, the movement similarity coefficient between the dance student and each training tutor is analyzed.

[0029] The training tutor with the largest movement similarity coefficient is taken as the suitable tutor for the dance student.

[0030] In a specific embodiment of the present invention, the method for analyzing the movement similarity coefficient between a dance student and each training tutor is as follows: Based on the spatial relative coordinates of the training devices to which the dance student belongs for each movement, the X-axis relative coordinate values of the spatial positions of the training devices to which the dance student belongs for each movement are extracted , the Y-axis relative coordinate values and the Z-axis relative coordinate values , where n represents the number of each training device, , m is a positive integer greater than 2, i represents the number of each movement, , j is a positive integer greater than 2.

[0031] Based on the spatial relative coordinates of the training devices of each training tutor for each movement, the X-axis relative coordinate values of the spatial positions of the training devices of each training tutor for each movement are extracted , the Y-axis relative coordinate values and the Z-axis relative coordinate values , where p represents the number of each training tutor, , q is a positive integer greater than 2.

[0032] Calculate the movement similarity coefficient between the dance student and each training tutor , where e represents the natural constant.

[0033] Step 1. Pairing and analysis of dance students and tutors: After dance students wear various training equipment to the corresponding positions on their bodies and pose various movements according to voice prompts, based on the X-axis, Y-axis, and Z-axis movement coordinates of dance students when performing various movements, the appropriate tutors for dance students are intelligently matched, thereby reducing the impact of a large size difference between dance students and dance tutors, and reducing the incidence of problems where dance students are injured in order to forcibly meet the movement indicators of dance tutors. Moreover, when analyzing the movement deviation between dance students and dance tutors, the incidence of the problem of frequent misjudgment of correct movements of dance students as incorrect due to a large size difference is reduced, thereby improving the accuracy of judgment.

[0034] Step 2. Analysis of dance students' movements: When dance students follow their corresponding appropriate tutors for dance training, obtain the relative dance space coordinates of each training device of the dance students at each monitoring time point, and analyze the problem monitoring time points of the dance students.

[0035] In a specific embodiment, the method for obtaining the relative dance space coordinates of each training device of the dance students at each monitoring time point is as follows: According to the method for obtaining the relative space coordinates of each training device of the dance students in each movement, similarly obtain the relative dance space coordinates of each training device of the dance students at each monitoring time point.

[0036] In a specific embodiment of the present invention, the method for analyzing the problem monitoring time points of dance students is as follows: Based on the relative dance space coordinates of each training device of the dance students at each monitoring time point, analyze the movement deviation coefficient of the dance students at each monitoring time point.

[0037] Obtain the movement deviation coefficient threshold from the local database. If the movement deviation coefficient of the dance student at a certain monitoring time point is greater than the movement deviation coefficient threshold, then mark this monitoring time point as a problem monitoring time point, thereby screening the problem monitoring time points of the dance students.

[0038] In a specific embodiment of the present invention, the method for analyzing the movement deviation coefficient of the dance students at each monitoring time point is as follows: Obtain the relative comparison space coordinates of each training device of the appropriate tutor at each monitoring time point from the local database, and extract the X-axis relative comparison space coordinates of each training device of the appropriate tutor at each monitoring time point , where t represents the number of each monitoring time point, , and s is a positive integer greater than 2.

[0039] Based on the relative dance space coordinates of each training device of the dance students at each monitoring time point, extract the X-axis relative dance space coordinates of each training device of the dance students at each monitoring time point .

[0040] Extract the action similarity coefficients between the dance trainees and the matching tutors based on the action similarity coefficients between the dance trainees and each training tutor.

[0041] Obtain the allowable X-axis action deviation values at each monitoring time point corresponding to each action similarity coefficient interval from the local database, and map to obtain the allowable X-axis action deviation values between the dance trainees and the matching tutors at each monitoring time point. 。

[0042] It should be noted that the larger the action similarity coefficient, the smaller the allowable X-axis action deviation value at each monitoring time point. The larger the action similarity coefficient indicates that the data such as body shape between the dance trainees and the matching tutors is closer. When the data such as body shape is closer, the actions should also be closer, and the allowable deviation value of the action data is smaller.

[0043] Calculate the X-axis action deviation coefficient of the dance trainees at each monitoring time point. 。

[0044] Similarly, calculate the Y-axis action deviation coefficient of the dance trainees at each monitoring time point. and the Z-axis action deviation coefficient. Calculate the action deviation coefficient of the dance trainees at each monitoring time point. 。

[0045] Step 2. Analysis of the dance trainees' actions in the present invention. By analyzing whether there are excessive action deviations in the dance trainees' dance actions, it is convenient to give suggestions to the dance trainees subsequently.

[0046] Step 3. Processing of optimization suggestions for dance training: Analyze the problem types at each problem monitoring time point of the dance trainees, so as to screen the problem monitoring time points of each beat and each action of the dance trainees, and give reminders for action adjustment to the dance trainees.

[0047] In a specific embodiment, the specific screening method for screening the problem monitoring time points of each beat and each action of the dance trainees is as follows: If the problem type at a certain problem monitoring time point of the dance trainees is a beat error, then mark this problem monitoring time point as a problem monitoring time point of the beat; otherwise, mark this problem monitoring time point as a problem monitoring time point of the action, so as to screen the problem monitoring time points of each beat and each action of the dance trainees.

[0048] In a specific embodiment of the present invention, for analyzing the problem types at each problem monitoring time point of a dance trainee, the specific analysis method is as follows: Based on the relative coordinates of the dance space of each training device at each monitoring time point of the dance trainee, extract the relative coordinates of the dance space of each training device at each problem monitoring time point of the dance trainee, and determine whether there is a problem of beat error at each problem monitoring time point of the dance trainee. If there is a problem of beat error at a certain problem monitoring time point of the dance trainee, then take the beat error as the problem type at this problem monitoring time point. Otherwise, take the movement error as the problem type at this problem monitoring time point, and summarize the problem types at each problem monitoring time point of the dance trainee.

[0049] In a specific embodiment of the present invention, for determining whether there is a problem of beat error at each problem monitoring time point of the dance trainee, the specific determination method is as follows: Obtain the beat problem analysis time period at each problem monitoring time point from the local database.

[0050] Based on the relative coordinates of the comparison space of each training device at each monitoring time point of the adapted tutor, extract the relative coordinates of the comparison space of each training device at each monitoring time point within the beat problem analysis time period at each problem monitoring time point of the adapted tutor.

[0051] It should be noted that for the beat problem analysis time period at each problem monitoring time point, if a certain problem monitoring time point is the 1:00 time point of the dance song, then the corresponding beat problem analysis time period is 0:58~1:02. Another example is that if a certain problem monitoring time point is the 2:00 time point of the dance song, then the corresponding beat problem analysis time period is 1:59~2:01. Since there are differences in the speed of movements during the dance process, the durations of the beat problem analysis time periods at different problem monitoring time points are not the same, and are set by the R & D personnel according to the actual situation of each dance song.

[0052] It should also be noted that if the target movement deviation coefficient of the dance trainee at a certain problem monitoring time point is less than the movement deviation coefficient threshold, it indicates that the movement of the dance trainee at this problem monitoring time point is closer to the movement at the monitoring time point of the maximum movement deviation coefficient of the adapted tutor within the beat problem analysis time period, indicating that the dance trainee has a problem of taking the beat too fast or too slow.

[0053] Based on the relative coordinates of the dance space of each training device at each problem monitoring time point of the dance trainee, and according to the method of analyzing the movement deviation coefficient of the dance trainee at each monitoring time point, similarly calculate the movement deviation coefficient of the dance trainee at each problem monitoring time point and the adapted tutor at each monitoring time point within the beat problem analysis time period, extract the maximum movement deviation coefficient of the dance trainee at each problem monitoring time point and the adapted tutor within the beat problem analysis time period, and take it as the target movement deviation coefficient of the dance trainee at each problem monitoring time point.

[0054] If the target action deviation coefficient of a dance student at a certain problem monitoring time point is less than the action deviation coefficient threshold, it is determined that the dance student has a problem of beat error at this problem monitoring time point.

[0055] In a specific embodiment of the present invention, the method for reminding the dance student to adjust the action is as follows: sending the problem types of each problem monitoring time point of the dance student to the display screen of the dance student, and extracting the relative coordinates of the dance space of each training device at each monitoring time point of the dance student according to the relative coordinates of the dance space of each training device at each monitoring time point of the dance student, and visualizing and displaying them on the display screen of the dance student.

[0056] According to the relative coordinates of the comparison space of each training device at each monitoring time point of the matching tutor, extract the relative coordinates of the comparison space of each training device at each action problem monitoring time point of the matching tutor, and visualize and display them on the display screen of the dance student, and recommend that the dance student perform fixed-action practice according to the corresponding actions.

[0057] According to the action deviation coefficient of the dance student at each beat problem monitoring time point and the matching tutor at each monitoring time point during the beat problem analysis period, extract the monitoring time point with the maximum action deviation coefficient of the dance student at each beat problem monitoring time point and the matching tutor during the beat problem analysis period, and use it as the reminder monitoring time point of the dance tutor for the dance student at each beat problem monitoring time point, and remind the dance student that the action performed at each beat problem monitoring time point is the action performed by the dance tutor at the reminder monitoring time point.

[0058] Step 3. Processing of dance training optimization suggestions of the present invention. By specifically analyzing the problem types of each problem monitoring time point of the dance student, the action deviation problems of the dance student are divided into beat error problems and action error problems, which is convenient for the dance student to adjust according to the actual error problems, thereby improving the learning efficiency of the dance student.

[0059] Refer to Figure 2 As shown, the second aspect of the present invention provides an intelligent training system for executing the intelligent training method for virtual dance training described above, including: a dance student and tutor pairing analysis module, a dance student action analysis module, a dance training optimization suggestion processing module, and a local database.

[0060] It should be noted that the dance student and tutor pairing analysis module is connected to the dance student movement analysis module, the dance student movement analysis module is connected to the dance training optimization suggestion processing module, and the local database is connected to the dance student and tutor pairing analysis module, the dance student movement analysis module, and the dance training optimization suggestion processing module.

[0061] The dance student and tutor pairing analysis module is used to, after the dance student wears each training equipment at the corresponding positions on the body, pose each action according to the voice prompt, obtain the spatial relative coordinates of each training equipment of the dance student in each action, and analyze the suitable tutor for the dance student based on this.

[0062] The dance student movement analysis module is used to obtain the dance spatial relative coordinates of each training equipment of the dance student at each monitoring time point when the dance student conducts dance training following the corresponding suitable tutor, and analyze the problem monitoring time points of the dance student.

[0063] The dance training optimization suggestion processing module is used to analyze the problem types at the problem monitoring time points of the dance student, so as to screen the beat problem monitoring time points and action problem monitoring time points of the dance student, and give a reminder for action adjustment to the dance student.

[0064] The above content is only an example and illustration of the concept of the present invention. Those skilled in the art of this technology can make various modifications or supplements to the described specific embodiments or use similar ways to replace them. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should fall within the protection scope of the present invention.

Claims

1. An intelligent training method for virtual dance training, characterized in that, Including: Step 1. Dance student and tutor pairing analysis: After a dance student wears each training device at the corresponding position on the body, the student poses each action according to the voice prompt, obtains the spatial relative coordinates of each training device to which the dance student belongs in each action, and analyzes the suitable tutor for the dance student based on this; Step 2. Dance student action analysis: When the dance student follows the corresponding suitable tutor for dance training, obtain the dance spatial relative coordinates of each training device of the dance student at each monitoring time point, and analyze the problem monitoring time points of the dance student; Step 3. Processing of dance training optimization suggestions: Analyze the problem types of each problem monitoring time point of the dance student, so as to screen out the beat problem monitoring time points and action problem monitoring time points of the dance student, and give a reminder for action adjustment to the dance student.

2. The intelligent training method for virtual dance training according to claim 1, wherein The specific analysis method for obtaining the spatial relative coordinates of each training device to which the dance student belongs in each action is as follows: Obtain the target training device and each remaining training device from the local database, obtain the spatial geographical coordinates of the target training device to which the dance student belongs in each action, take the spatial geographical coordinates of the target training device to which the dance student belongs as the origin, establish a spatial rectangular coordinate system, record the spatial relative coordinates of the target training device to which the dance student belongs in each action as (0, 0, 0), and obtain the spatial coordinates of each remaining training device to which the dance student belongs relative to the target training device in each action in the spatial rectangular coordinate system through a three-dimensional space sensor, and mark them as the spatial relative coordinates of each remaining training device to which the dance student belongs in each action; Summarize the spatial relative coordinates of each training device to which the dance student belongs in each action.

3. The intelligent training method for virtual dance training according to claim 2, characterized in that, The specific analysis method for analyzing the suitable tutor for the dance student is as follows: Obtain each training tutor and the spatial relative coordinates of their respective training devices in each action from the local database, and analyze the action similarity coefficient between the dance student and each training tutor based on the spatial relative coordinates of each training device to which the dance student belongs in each action; Take the training tutor with the largest action similarity coefficient as the suitable tutor for the dance student.

4. The intelligent training method for virtual dance training according to claim 3, characterized in that The specific analysis method for analyzing the action similarity coefficient between the dance student and each training tutor is as follows: Extract the X-axis relative coordinate values of the spatial positions of each training device to which the dance student belongs based on the spatial relative coordinates of each training device to which the dance student belongs in each movement and the Y-axis relative coordinate values and the Z-axis relative coordinate values , where n represents the number of each training device, , m is a positive integer greater than 2, i represents the number of each movement, , and j is a positive integer greater than 2; Extract the X-axis relative coordinate values of the spatial positions of the training devices of each training instructor for each movement, based on the spatial relative coordinates of each training instructor's training devices for each movement. , the Y-axis relative coordinate values and the Z-axis relative coordinate values , where p represents the number of each training instructor, , q is a positive integer greater than 2; Calculate the action similarity coefficient between the dance trainees and each training instructor , where e represents the natural constant.

5. The intelligent training method for virtual dance training according to claim 4, characterized in that, The specific analysis method for analyzing the problem monitoring time points of the dance student is as follows: Based on the dance spatial relative coordinates of each training device of the dance student at each monitoring time point, analyze the action deviation coefficient of the dance student at each monitoring time point; Obtain the action deviation coefficient threshold from the local database. If the action deviation coefficient of the dance student at a certain monitoring time point is greater than the action deviation coefficient threshold, mark this monitoring time point as a problem monitoring time point, so as to screen out the problem monitoring time points of the dance student.

6. The intelligent training method for virtual dance training according to claim 5, wherein, The specific analysis method for analyzing the action deviation coefficient of the dance student at each monitoring time point is as follows: Obtain the comparison space relative coordinates of the adapted tutor for each training device at each monitoring time point from the local database, and extract the X-axis comparison space relative coordinates of the adapted tutor for each training device at each monitoring time point , where t represents the number of each monitoring time point , and s is a positive integer greater than 2 According to the relative dance space coordinates of each training device for the dance trainees at each monitoring time point, extract the relative X-axis dance space coordinates of each training device for the dance trainees at each monitoring time point ; Based on the action similarity coefficient between the dance student and each training tutor, extract the action similarity coefficient between the dance student and the suitable tutor; Obtain the X-axis action allowable deviation values at each monitoring time point corresponding to each action similarity coefficient interval from the local database, and map to obtain the X-axis action allowable deviation values of the dance student and the matching tutor at each monitoring time point ; Calculate the X-axis motion deviation coefficient of dance trainees at each monitoring time point ; Similarly, calculate the Y-axis movement deviation coefficient of the dance trainees at each monitoring time point and the Z-axis movement deviation coefficient , and calculate the movement deviation coefficient of the dance trainees at each monitoring time point .

7. The intelligent training method for virtual dance training according to claim 5, characterized in that, The specific analysis method for analyzing the problem types of each problem monitoring time point of the dance student is as follows: According to the relative dance space coordinates of each training device for the dance trainee at each monitoring time point, extract the relative dance space coordinates of each training device for the dance trainee at each problem monitoring time point, and determine whether there is a problem of beat error for the dance trainee at each problem monitoring time point. If there is a problem of beat error for the dance trainee at a certain problem monitoring time point, then take the beat error as the problem type at this problem monitoring time point. Otherwise, take the movement error as the problem type at this problem monitoring time point, and summarize the problem types of each problem monitoring time point for the dance trainee.

8. The intelligent training method for virtual dance training according to claim 7, wherein, The specific method for determining whether there is a problem of beat error for the dance trainee at each problem monitoring time point is as follows: Obtain the beat problem analysis time period for each problem monitoring time point from the local database; According to the relative comparison space coordinates of each training device for the matching tutor at each monitoring time point, extract the relative comparison space coordinates of each training device for the matching tutor at each monitoring time point within the beat problem analysis time period for each problem monitoring time point; According to the relative dance space coordinates of each training device for the dance trainee at each problem monitoring time point, and according to the method of analyzing the movement deviation coefficient of the dance trainee at each monitoring time point, similarly calculate the movement deviation coefficient of the dance trainee at each problem monitoring time point and the matching tutor at each monitoring time point within the beat problem analysis time period, extract the maximum movement deviation coefficient of the dance trainee at each problem monitoring time point and the matching tutor within the beat problem analysis time period, and take it as the target movement deviation coefficient of the dance trainee at each problem monitoring time point; If the target movement deviation coefficient of the dance trainee at a certain problem monitoring time point is less than the movement deviation coefficient threshold, it is determined that there is a problem of beat error for the dance trainee at this problem monitoring time point.

9. The intelligent training method for virtual dance training according to claim 8, wherein, The specific reminder method for making movement adjustment reminders for the dance trainee is as follows: Send the problem types of each problem monitoring time point of the dance trainee to the display screen of the dance trainee. According to the relative dance space coordinates of each training device for the dance trainee at each monitoring time point, extract the relative dance space coordinates of each training device for the dance trainee at each beat problem monitoring time point and each movement problem monitoring time point, and visually display them on the display screen of the dance trainee; According to the relative comparison space coordinates of each training device for the matching tutor at each monitoring time point, extract the relative comparison space coordinates of each training device for the matching tutor at each movement problem monitoring time point, and visually display them on the display screen of the dance trainee, and recommend that the dance trainee perform fixed movement exercises according to the corresponding movements; According to the movement deviation coefficient of the dance trainee at each beat problem monitoring time point and the matching tutor at each monitoring time point within the beat problem analysis time period, extract the monitoring time point of the maximum movement deviation coefficient of the dance trainee at each beat problem monitoring time point and the matching tutor within the beat problem analysis time period, and take it as the reminder monitoring time point of the dance tutor for the dance trainee at each beat problem monitoring time point, and remind the dance trainee that the movement made at each beat problem monitoring time point is the movement made by the dance tutor at the reminder monitoring time point.

10. An intelligent training system for performing the intelligent training method for virtual dance training according to any one of claims 1-9, characterized in that, Including: The dance student and tutor pairing analysis module is used for the dance student to wear each training equipment at the corresponding position on the body, and then pose each movement according to the voice prompt, obtain the spatial relative coordinates of each training equipment of the dance student in each movement, and analyze the suitable tutor for the dance student based on this; The dance student movement analysis module is used for obtaining the dance space relative coordinates of each training equipment of the dance student at each monitoring time point when the dance student is undergoing dance training following the corresponding suitable tutor, and analyzing the problem monitoring time points of the dance student; The dance training optimization suggestion processing module is used for analyzing the problem types of each problem monitoring time point of the dance student, so as to screen out the problem monitoring time points of each beat and each movement of the dance student, and give a reminder for the dance student to adjust the movement.

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