KR20230167984A - Artificial Intelligence based Golf Swing Coaching Service Providing System - Google Patents

Abstract

The artificial intelligence-based golf swing coaching service provision system according to the present invention includes a user device that captures a user's golf swing video and transmits it to the outside, and analyzes the user's golf swing video transmitted from the user device using an artificial neural network model. A coaching service providing server that transmits the analysis results to the user device, wherein the coaching service providing server includes an image extraction unit that extracts a swing posture image for each predetermined swing step from the video frames constituting the user's golf swing video. , an image synthesis unit that synthesizes the swing posture image of the missing step using image frames placed before and after the missing step when there is a missing step as a result of extracting the swing posture image for each swing step, and a swing for each swing step. It is characterized by comprising a swing analysis unit that analyzes the user's golf swing problems step by step by comparing the posture image with the standard swing posture image provided for each step.

Description

Artificial Intelligence based Golf Swing Coaching Service Providing System}

The present invention relates to an artificial intelligence-based golf swing coaching service provision system, and more specifically, to analyze a user's golf swing video transmitted online from the user device using an artificial neural network model, and to provide a golf swing coaching service online according to the analysis results. It relates to an artificial intelligence-based golf swing coaching service providing system that matches the user with a coach suitable for the user.

As golf has rapidly become popular in recent years, it has established itself as a sport that can be enjoyed by people of all ages. It is one of the sports that is quite difficult for general amateurs because it causes many mistakes such as top balls, hooks, slices, etc.

Therefore, it is common for many amateur golfers to practice their swings in designated spaces, such as indoor or outdoor golf practice ranges, to reduce impact errors or ball direction errors. In this case, they use auxiliary devices such as mirrors to correct incorrect swing posture. You can check your swing posture or receive posture correction on site through a professional lesson coach.

However, when using auxiliary devices such as mirrors, there is a disadvantage in that it is difficult to accurately check problems due to limitations in processing the golfer's line of sight and the ability to analyze the cause of a misshot. When using a professional lesson coach, the above-mentioned disadvantages are somewhat eliminated. Although it can be solved, there are inevitable disadvantages such as time constraints for lessons and excessive costs.

In order to solve this problem, recently, as disclosed in [Document 1] and [Document 2] below, a system that provides useful information to golfers by analyzing golfer's swing images using ICT technology has been developed, but these In most cases, the system must be equipped with a separate sensor, marker, or wearable device attached to the golfer or golf club to capture the golfer's movements that occur during the swing, so it costs a lot to configure the device, and in a typical golf driving range, There is a problem that makes it difficult to use.

[Document 1] Korea Patent Publication No. 2009-0105031 (published on October 7, 2009)

[Document 2] Korean Patent Publication No. 2016-0127615 (published on November 4, 2016)

The present invention is intended to solve the problems of the prior art as described above. The purpose of the present invention is to analyze the user's golf swing video transmitted online from the user device using an artificial neural network model, and to analyze the user's golf swing video transmitted online from the user device according to the analysis results. The purpose is to provide an artificial intelligence-based golf swing coaching service provision system that matches the user with a coach suitable for the user online.

In order to achieve the above purpose, the artificial intelligence-based golf swing coaching service providing system according to the present invention includes a user device that captures a user's golf swing video and transmits it to the outside, and an artificial neural network model that transmits the video from the user device. It is configured to include a coaching service providing server that analyzes the user's golf swing video and matches the user with a coach suitable for the user online according to the analysis results, wherein the coaching service providing server records the user's golf swing video. An image extraction unit that extracts a swing posture image for each predetermined swing step from the video frames that constitute it. If there is a missing step as a result of extracting the swing posture image for each swing step, the missing step is used using the video frames placed before and after the missing step. An image synthesis unit that synthesizes swing posture images of each stage of the swing, a swing analysis unit that analyzes the user's golf swing problems step by step by comparing the swing posture images of each swing step with standard swing posture images provided for each step, and the user It is characterized by including a coach matching unit that searches for a coach suitable for the user from a pre-stored coach DB according to the results of analysis of golf swing problems and matches the coach to the user online.

In addition, the image extraction unit extracts the swing posture image for each swing step by comparing the coordinates of at least one feature point detected for the video frame and the standard swing posture image, where the feature points are the head, neck, right shoulder, and left shoulder. , It is characterized by consisting of abdominal core, right elbow, left elbow, grip, right pelvis, left pelvis, right knee, left knee, right ankle, left ankle, and club head.

In addition, the image extraction unit is characterized in that it extracts an image frame in which the coordinates of the standard swing posture image and the feature points for each swing step match within a predetermined error range as the swing posture image for the corresponding swing step.

In addition, the image synthesis unit calculates the trajectory and angular velocity of the club head using the change in coordinate values of the club head based on the head among the feature points in the image frames placed before and after the missing step, and then calculates the trajectory and angular velocity of the club head. The swing posture image of the missing step is synthesized by calculating the coordinates of the feature points so that they match the coordinates of the club head of the standard swing posture image of the head missing step.

In addition, the swing analysis unit is characterized in that it analyzes the user's golf swing problems by comparing the coordinate values of the feature points of the user's swing posture image and the standard swing posture image at each stage.

The artificial intelligence-based golf swing coaching service providing system according to the present invention analyzes the user's golf swing video transmitted online from the user device using an artificial neural network model, and provides a suitable coach for the user online according to the analysis results. Since it is configured to match the user, the user has the advantage of significantly saving the time and cost required for golf swing lessons.

In addition, in the artificial intelligence-based golf swing coaching service providing system according to the present invention, the coaching service providing server analyzes the user's golf swing problems in advance and then searches for the most suitable coach for the user among the coaches stored in the coach DB according to the analysis results. Because it is a matching method, it has the advantage of significantly improving the effectiveness of golf lessons from the user's perspective.

1 is a diagram illustrating the overall configuration of an artificial intelligence-based golf swing coaching service provision system according to an embodiment of the present invention;
Figure 2 is a block diagram for explaining the operation configuration of the artificial intelligence-based golf swing coaching service provision system shown in Figure 1;
Figure 3 is a flowchart for explaining the operation of the artificial intelligence-based golf swing coaching service provision system shown in Figure 1;
Figure 4 is a diagram showing a standard swing posture image for each swing step provided in the artificial intelligence-based golf swing coaching service provision system shown in Figure 1;
Figures 5 to 7 are diagrams for explaining a method of extracting step-by-step swing posture images from a user's golf swing image in the artificial intelligence-based golf swing coaching service provision system shown in Figure 1, and
Figure 8 is a diagram illustrating a method of analyzing problems in a user's golf swing by comparing the user's swing posture image with the standard swing posture image in the artificial intelligence-based golf swing coaching service provision system shown in Figure 1.

Hereinafter, preferred embodiments of the present invention will be described in detail using the accompanying drawings.

Figure 1 is a diagram for explaining the overall configuration of an artificial intelligence-based golf swing coaching service provision system according to an embodiment of the present invention, and Figure 2 is an operational configuration of the artificial intelligence-based golf swing coaching service provision system shown in Figure 1. This is a block diagram to explain.

The artificial intelligence-based golf swing coaching service providing system according to the present invention includes a user device 10 that captures a golf swing video of the user P and transmits it to the outside, and can communicate with the user device 10 through a communication network 30. It is configured to include a coaching service providing server 20 connected to the coaching service providing server 20, and a coach device 40 connected to enable communication between the user device 10 and the coaching service providing server 20 through the communication network 30.

In addition, the user device 10 includes a batting mat (M) equipped with a ball supply device so that the user (P) can practice his golf swing, and a batting mat (M) installed on one side of the batting mat so that the user (P) can practice his golf swing. It is configured to include at least one camera unit (11, 12) that takes pictures.

In this embodiment, as an example, the camera units 11 and 12 are installed on the right side of the user P based on the drawing to capture the side swing posture of the user P and the user P. It is composed of a second camera unit 12 installed in front of the user (P) based on the drawing in order to photograph the front swing posture of the user (P), but the camera is not limited to this and can be used in various directions such as the upper direction of the user (P) as needed. Of course, it can be installed selectively.

In addition, the user device 10 includes a first communication unit 13 for transmitting to the outside the golf swing video of the user P captured by the first and second camera units 11 and 12, and a first communication unit 13 of the user P. As described later, the swing posture, the swing analysis result transmitted from the coaching service providing server 20, the coach matching result, and the coaching content transmitted from the coach device 40 are provided to the user through at least one of text, voice, or video. It further includes a first input/output unit 14 indicated by .

At this time, the user device 10 may be configured to transmit the golf swing video of the user P to the outside in real time or store it in memory, etc. and then transmit it to the outside by the user P's operation of the first input/output unit 14. You can.

To this end, the user device 10 may further include a storage device (not shown) such as a memory, although not shown in the drawing.

In addition, the user (P) transmits inquiries, etc. to the coach device 40 used by the coach matched by the coaching service providing server 20 through the first input/output unit 14, as described later, or Evaluation opinions or ratings for coaches whose lessons have been completed may be transmitted to the coaching service providing server 20.

In addition, among the user devices 10, the first and second camera units 11 and 12, the first communication unit 13, and the first input/output unit 14 are, for example, a smartphone fixed to one side of the batting mat M. It may be configured as a mobile device, in which case the operation of the first and second camera units 11 and 12, the first communication unit 13, and the first input/output unit 14 is performed by executing an application installed on the mobile device. It can be done.

Meanwhile, the coaching service providing server 20 analyzes the user's golf swing video transmitted from the user device 10 through the communication network 30 using an artificial neural network model, and uses the analysis result to determine the user ( It performs a function of matching a suitable coach for P) and transmitting the analysis results to the user device 10 and/or the coach device 40.

At this time, the communication network 30 may be composed of various wired or wireless communication networks such as a local area network (LAN), a metropolitan area network (MAN), and a wide area network (WAN), for example. Known as Internet or World Wide Web (WWW), WiFi communication, WiFi-Direct communication, Long Term Evolution (LTE) communication, 5G communication, 6G communication, Bluetooth communication , it may be composed of a communication network using any one of infrared communication, ultrasonic communication, and LiFi (Light Fidelity) communication.

For this purpose, the coaching service providing server 20 includes a second communication unit 21 that communicates with the first communication unit 13 of the user device 10, and a golf game of the user P received from the second communication unit 21. It includes a control unit 22 that analyzes the golf swing of the user (P) using the swing video, and a memory unit 23 that stores data necessary for the control unit 22 to analyze the golf swing video of the user (P). It is composed by:

In addition, the coaching service providing server 20 includes an image extraction unit 24 that extracts a plurality of swing posture images using the golf swing video of the user P according to a control signal from the control unit 22, as described later. and an image synthesis unit 25 that synthesizes a swing posture image that cannot be extracted by the image extraction unit 24 using the golf swing video of the user P.

In addition, the coaching service providing server 20 includes a swing analysis unit that analyzes problems using the golf swing posture image of the user (P) extracted or synthesized by the image extraction unit 24 and the image synthesis unit 25 ( 26), and a coach matching unit 27 that searches for a coach suitable for the user from the coach DB pre-stored in the memory unit 23 according to the results of analysis of the user's golf swing problem and matches it to the user. do.

In addition, the coach device 40 includes a third communication unit 43 for communicating with the user device 10 and the coaching service providing server 20, and a user ( A product that displays P)'s golf swing video, step-by-step swing posture images, swing analysis results, coach matching results, and query contents transmitted from the user device 10 to the coach in at least one of text, voice, and video. It further includes two input/output units (44).

In addition, a coach using the coaching device 40 can transmit coaching content for correcting the user's swing problem to the user device 10 through the second input/output unit 44, and the coaching content is text. , video, audio, etc.

Next, the golf swing analysis method of the artificial intelligence-based golf swing coaching service providing system according to the present invention configured as described above will be described in detail with reference to FIGS. 3 to 8.

Figure 3 is a flowchart for explaining the operation of the artificial intelligence-based golf swing coaching service provision system shown in Figure 1, and Figure 4 is a standard swing for each swing provided in the artificial intelligence-based golf swing coaching service provision system shown in Figure 1. This is a drawing showing the posture image.

In addition, Figures 5 to 7 are diagrams for explaining a method of extracting step-by-step swing posture images from a user's golf swing image in the artificial intelligence-based golf swing coaching service provision system shown in Figure 1, and Figure 8 is shown in Figure 1. This is a diagram to explain how to analyze problems in a user's golf swing by comparing the user's swing posture image with the standard swing posture image in an artificial intelligence-based golf swing coaching service provision system.

First, the control unit 22 receives the golf swing video of the user P from the user device 10 (S10), and the golf swing video includes (1) to (1) as exemplarily shown in FIG. 5. It consists of a plurality of consecutive swing posture image frames (i.e. video frames) shown in 12).

Looking at this separately by golf swing section, swing posture image frames (1) to (5) correspond to the "backswing section" from the address action to the backswing top action, and swing posture image frames (6) to (9) are the down swing section. It corresponds to the “down swing section” from the swing action to the impact action, and swing posture image frames (10) to (12) correspond to the “follow swing section” from the release action to the finish action.

When step S10 is completed, the control unit 22 uses the image extractor 24 to select a predetermined image frame from a plurality of image frames (frames (1) to (12) in this embodiment) constituting the user's golf swing video. Swing posture images for each swing stage are extracted (S20).

For this purpose, the memory unit 23 pre-stores standard swing posture images for each stage as exemplarily shown in Figure 4. The standard swing posture images are images extracted from swing images of professional players or golf swing images. It may be a staged or synthesized image for the lesson.

In the case of this embodiment, as an example, the standard swing posture image was composed of an image synthesized using computer graphics by analyzing the swing strengths of various domestic and foreign professional players.

In addition, for convenience of explanation, in this embodiment, the standard swing posture images are sequentially "address (a)", "takeback (b)", "backswing top (c)", "down swing (d)", It consists of eight stages: “Impact (e)”, “Release (f)”, “Follow Throw (g)”, and “Finish (h)”.

At this time, the image extraction unit 24 extracts swing posture images corresponding to the standard swing posture images for each stage from the user golf swing video by using an image processing technique using an artificial neural network model stored in the memory unit 23. is extracted. In the detailed description of the invention and the entire scope of the patent claims in this specification, the term "artificial neural network model" is a term that encompasses all types of machine learning models such as CNN and RNN, which are designed to imitate the human neural structure.

In addition, in this embodiment, for convenience of explanation, the case of extracting the user's frontal swing posture image using the frontal standard swing posture image is described as an example, but the user's frontal swing posture image is extracted using the side standard swing posture image previously stored in the same manner. Side swing posture images can be extracted.

In step S20, first, the image extraction unit 24 edits the entire swing posture image frame included in the received user's golf swing video into an image of a predetermined size. In this case, as described later, a standard swing posture image For contrast, it is desirable to edit the part containing the user's entire body to the same size as the golfer's body size included in the standard swing posture image.

In this way, when the size editing of the swing posture image frame is completed, the image extraction unit 24 uses an artificial neural network model to extract the standard swing posture image for each stage from the swing posture image frame as shown in Figures 5 and 7. The corresponding image is extracted.

At this time, the image extraction unit 24 extracts the swing posture image of the user (P) at each stage based on a pose estimation algorithm such as OpenPose, MoveNet, BodyPoseNet, etc., as known in the case of the above algorithm. Likewise, the human body's joint detection artificial intelligence algorithm detects multiple feature points (or node points) corresponding to the human body's joints and analyzes the posture.

In this embodiment, as an example, the artificial neural network model has head (a1), neck (a2), right shoulder (a3), left shoulder (a4), abdominal core (a5), and right shoulder as shown in Figures 6 and 8. Elbow (a6), left elbow (a7), grip (a8), right pelvis (a9), left pelvis (a10), right knee (a11), left knee (a12), right ankle (a13), left ankle (a14) ), and is configured to detect a total of 15 feature points (node points) consisting of the club head (a15).

Using this artificial neural network model, the image extraction unit 24 detects the coordinates of the 15 feature points for each swing posture image frame, and then calculates the coordinates of the 15 feature points detected in the standard swing posture image for each stage and By comparison, the swing posture image frame in which the coordinates of the standard swing posture image and 15 feature points match within a predetermined error range is extracted as the swing posture image of the corresponding stage.

In this embodiment, as an example, a case where the image extraction unit 24 extracts the swing posture image for each stage in the form of a skeleton is explained in order to reduce the computational load of the server, but the case is not limited to this, and actual Swing posture images can also be extracted in the form of captured videos.

When step S20 is completed, the control unit 22 searches the user's swing posture image extracted corresponding to the standard swing posture image for each step and determines whether there is a step missing from the swing posture image extraction (S30) .

Generally, in the case of mobile devices such as smartphones, the frame rate (FPS, Frames Per Second) of the camera is set to 30fps to 60fps when shooting video, and the backswing section (frames (1) to (5) in Figure 5) is relatively fast. Because the swing speed is slow, the chances of missing a step are very slim.

However, in the down swing section or the follow swing section, there are differences depending on the user, but in most cases, the swing speed is greatly accelerated, so due to the limitation of the camera frame rate, some of the predetermined swing steps are omitted, resulting in the user's overall golf golf. There may be cases where swing analysis is difficult.

The present invention is characterized by enabling swing analysis of all stages by supplementing the missing swing postures on the basis of artificial intelligence when some of the swing postures of the plurality of stages required for swing analysis are missing in the user's golf swing video. Do it as

To this end, if there is a missing step as a result of the determination in step S30, the control unit 22 synthesizes the swing posture image of the missing step using the image synthesis unit 25 (S40). In this case, the image synthesis The unit 25 synthesizes the swing posture image of the missing step using image frames placed before and after the missing step.

In the case of this embodiment, as a result of performing step S20, as shown in Figures 5 and 7, the swing posture extraction corresponding to the "impact (e)" stage among the standard swing posture images of a plurality of predetermined stages is missing, which is previously described. As explained, this phenomenon occurs because the swing speed in the down swing section exceeds the camera frame rate.

In this case, the image synthesis unit 25 performs pose estimation using frames placed before and after the missing “impact (e)” step, that is, frames (9) and (10) in this embodiment. estimation) The swing posture image at the impact stage is estimated and synthesized by an algorithm-based artificial neural network model.

In the case of this embodiment, the image synthesis unit 25 is an example of the user's head (a1, a1'), which is a feature point whose coordinates are relatively fixed in frames (9) and (10), as shown in FIG. 6. ) is calculated based on the change in coordinate values of the club head (a15, a15'), and information such as the club head's trajectory, speed, moving distance, and angular velocity is first calculated.

At this time, the angular velocity of the club head is the angle formed by the imaginary line connecting the head (a1, a1') and the club head (a15, a15') with respect to the reference line extending perpendicularly from the head (a1, a1') to the ground. It means the angular velocity, and the speed and angular velocity can be obtained using the moving distance of the club head (a15, a15'), the angle change amount, and the frame speed (time interval between each frame), respectively.

When the angular velocity of the club head is obtained in this way, the image synthesis unit 25 combines the club head of the user's swing posture image at the impact stage to match the angle formed between the golfer's head and the club head at the impact stage of the standard swing posture image. (b15) coordinates are calculated, and the calculation can be calculated using the trajectory and angular velocity of the club head (a1, a1') obtained from frames (9) and (10).

In addition, when the coordinates of the club head (b15) of the user's swing posture image in the missing impact stage are calculated as described above, the image synthesis unit 25 calculates the impact of each of the remaining feature points (b1 to b14) by the posture estimation algorithm. By calculating the coordinates at each stage, the user's swing posture image at that stage is synthesized.

When the user's swing posture image for all predetermined swing steps is secured as a result of performing step S40, the control unit 22 analyzes problems in the user's golf swing using the swing analysis unit 26 (S50).

In this case, the swing analysis unit 26 analyzes the user's golf swing problems step by step by comparing the swing posture image of the user's swing step with the standard swing posture image provided for each step. Specifically, the user's golf swing problem is analyzed by step. The user's golf swing problems are analyzed by comparing coordinate values.

Figure 8 shows an example of analyzing problems in the user's swing in the "takeback" stage, where (a) is a standard swing posture image, (b) is the user's swing posture image, and (c) is the (a) ),(b) This is an image comparing the coordinates of each feature point detected in the image.

In the case of Figure 8, each feature point of the standard swing posture image and the user's swing posture image was found to match very well. In this case, the swing analysis unit 26 analyzed that there was no problem with the user's golf swing in the takeback stage. I do it.

On the other hand, although not shown in the drawing, if the characteristic points of the standard swing posture image and the user's swing posture image do not match at each stage, the swing analysis unit 26 uses the swing analysis artificial neural network stored in the memory unit 23. Using the model, various problems in the user's golf swing (sway, early extension, casting, heads-up, scooping, etc.) are analyzed.

For example, if the user's upper body feature points (head, neck, both shoulders) are located to the left of the upper body feature points of the standard swing posture image during the backswing section, the swing analysis unit 26 The "upper body sway phenomenon" is analyzed as a swing problem, and in the down swing section or follow throw section, the user's upper body feature points (head, neck, both shoulders) are located above or to the right of the upper body feature points in the standard swing posture image. In this case, “head up phenomenon at impact” or “upper body sway phenomenon at impact” are analyzed as swing problems.

In this embodiment, for convenience of explanation, the golf swing analysis of the driver swing among various golf clubs is described as an example, but if necessary, it can be used for other golf clubs such as putter, wedge, middle iron, long iron, utility, and wood. It can also be applied.

In this case, the user can select the type of golf club through the first input/output unit 14 of the user device 10 before requesting swing analysis, and the coaching service providing server 20 may display a standard swing for each golf club. It is desirable to have a posture image.

Meanwhile, if there are no missing steps as a result of the determination in step S30, the control unit 22 performs step S50 described above.

When step S50 is completed, the control unit 22 uses the coach matching unit 27 to select a coach suitable for the user from the coach DB pre-stored in the memory unit 23 according to the result of analyzing the user's swing problem in step S50. A step of searching and matching with the user is performed (S60).

At this time, the coach DB stores information such as the names or IDs, gender, strengths and weaknesses, ratings for coaching content, and coaching available time slots of coaches registered on the coaching service provision server 20. The coaching content can be changed as needed. The ratings can be stored separately by swing problem type.

Therefore, as an example, the coach matching unit 27 ensures that a user who has a problem with the swing posture in the backswing section is matched in the order of the coach with the highest coaching rating in the relevant field (i.e., the backswing field), and the follow throw section. Users who have problems with their swing posture can be matched in the order of the coach with the highest coaching rating in that field (i.e., follow throw field).

In addition, the coaching ratings of each coach stored in the coach DB may be stored separately according to the type of golf club. In this case, the coach matching unit 27 also detects problems with the swing posture of a long iron club as an example. Users who have a problem with driver swing posture can be matched in the order of coaches with the highest coaching rating in the field.

When step S60 is completed, the control unit 22 transmits the coach matching result to the user and the coach through the user device 10 and the coach device 40, respectively. In this case, the control unit 22 sends the coach matching result to the user and the coach, respectively. Information about the matched coach is sent to the coach, and information about the matched user is sent to the coach.

In addition, the control unit 22 sends the user's swing video, step-by-step swing posture images of the user, swing problem analysis results, etc. to the matched coach so that coaching on the golf swing between the matched user and the coach can be done online at a later stage. It is transmitted (S70).

As described above, when steps S60 and S70 are completed, the user device 10 and the coach device 40 are connected through the communication network 30, so that coaching to solve golf swing problems is performed online.

In addition, the artificial intelligence-based golf swing coaching service provision system according to the present invention may further include a module for membership registration and authentication of the user group and the coach group, and a billing payment module for settling the coaching fee. The modules include general Since this is content, detailed explanation will be omitted here.

10: User device 11, 12: First and second camera units
20: Coaching service provision server 22: Control unit
24: image extraction unit 25: image synthesis unit
26: swing analysis unit 40: coach device

Claims (5)

A user device that captures a video of the user's golf swing and transmits it to an external source; and
It is configured to include a coaching service providing server that analyzes the user's golf swing video transmitted from the user device using an artificial neural network model and matches the user with a coach suitable for the user according to the analysis results,
The coaching service providing server,
an image extraction unit that extracts a swing posture image for each predetermined swing step from the video frames constituting the user's golf swing video;
If there is a missing step as a result of extracting the swing posture image for each swing step, an image synthesis unit that synthesizes the swing posture image of the missing step using image frames placed before and after the missing step;
A swing analysis unit that analyzes the user's golf swing problems step by step by comparing the swing posture image for each swing step with a standard swing posture image provided for each step; and
An artificial intelligence-based golf swing coaching service providing system comprising a coach matching unit that searches for a coach suitable for the user from a pre-stored coach DB according to the results of analysis of the user's golf swing problem and matches it to the user. In paragraph 1:
The image extraction unit extracts the swing posture image for each swing step by comparing the coordinates of at least one feature point detected for the video frame and the standard swing posture image,
The feature points include the head, neck, right shoulder, left shoulder, abdominal core, right elbow, left elbow, grip, right pelvis, left pelvis, right knee, left knee, right ankle, left ankle, and club head. Artificial intelligence-based golf swing coaching service provision system. In paragraph 2,
The image extractor extracts an image frame in which the coordinates of the standard swing posture image and the feature points match within a predetermined error range for each swing step as a swing posture image for the corresponding swing step. Artificial intelligence-based golf swing coaching Service delivery system. In paragraph 3,
The image synthesis unit calculates the trajectory and angular velocity of the club head using the change in coordinate values of the club head based on the head among the feature points in the image frames placed before and after the missing step, and then calculates the trajectory and angular velocity of the club head. An artificial intelligence-based golf swing coaching service providing system that synthesizes the swing posture image of the missing step by calculating the coordinates of the feature points to match the coordinates of the club head of the standard swing posture image of the missing step. In paragraph 4,
The swing analysis unit analyzes the user's golf swing problems by comparing the coordinate values of the feature points of the user's swing posture image and the standard swing posture image at each stage. An artificial intelligence-based golf swing coaching service providing system.