Ball hitting effect evaluation method, device and system, electronic equipment and storage medium

Abstract

The embodiment of the invention discloses a ball hitting effect evaluation method, device and system, electronic equipment and a storage medium, and the method comprises the steps: obtaining user ball hitting data in a target space, and the user ball hitting data comprises one or more of the following: a ball hitting drop point position, a ball hitting speed and a ball hitting action track; and performing ball hitting effect evaluation based on the user ball hitting data to obtain a ball hitting effect evaluation result. According to the method, the ball hitting drop point, the ball speed and the action normalization are comprehensively analyzed, the ball hitting effect of multiple athletes is comprehensively evaluated in real time at the same time, the accuracy and comprehensiveness of the evaluation of the ball hitting effect are effectively improved, and therefore more targeted training suggestions are provided for the athletes subsequently.

Description

Technical Field

[0001] This application relates to the field of computer vision technology, and particularly to a method, device, system, electronic device and storage medium for evaluating the hitting effect. Background Art

[0002] In the field of tennis training, the evaluation of the hitting effect of athletes is one of the key links to improve their technical level. Traditional evaluation methods mainly rely on the observation and experience judgment of artificial coaches. Coaches give subjective evaluations and guiding suggestions by observing the movement performance of athletes during the hitting process, the landing position of the ball, and the ball speed, etc. However, the existing technical methods have the following defects. First, the subjectivity of manual evaluation is relatively strong, and the judgment criteria of different coaches may vary, resulting in inaccurate and inconsistent evaluation results. Second, coaches need to pay attention to the performance of multiple athletes simultaneously during the training process, and it is difficult to analyze the hitting effect of each athlete in real time and comprehensively, and some detailed problems are easily overlooked. In addition, manual evaluation cannot provide quantitative data support, and it is difficult to accurately track and analyze the training progress of athletes.

[0003] The foregoing description is for the purpose of providing general background information and does not necessarily constitute prior art. Summary of the Invention

[0004] Embodiments of this application provide a method, device, system, electronic device and storage medium for evaluating the hitting effect, which can simultaneously evaluate the hitting effect of multiple athletes in an all-round and real-time manner, and effectively improve the accuracy and comprehensiveness of the hitting effect evaluation.

[0005] In a first aspect, embodiments of this application provide a method for evaluating the hitting effect, including:

[0006] Obtain user hitting data in a target space, where the user hitting data includes one or more combinations of the following: hitting landing position, hitting ball speed, and hitting motion trajectory;

[0007] Based on the user hitting data, perform an evaluation of the hitting effect to obtain an evaluation result of the hitting effect.

[0008] Optionally, in some embodiments of this application, the obtaining of the user hitting data in the target space includes:

[0009] Obtain the hitting landing position of the target sphere during movement in the target space;

[0010] Obtain the hitting ball speed of the target sphere in the target space;

[0011] Obtain the hitting motion trajectory of the target user in the target space.

[0012] Optionally, in some embodiments of the present application, obtaining the hitting landing point position of the target sphere during movement in the target space includes:

[0013] Collecting the movement trajectory of the target sphere through sensors pre-deployed in the target space;

[0014] Identifying the hitting landing point position of the target sphere based on the movement trajectory.

[0015] Optionally, in some embodiments of the present application, obtaining the hitting ball speed of the target sphere in the target space includes:

[0016] Collecting a movement video of the target sphere during movement through a camera device pre-deployed in the target space;

[0017] Identifying the starting frame number and the sphere starting coordinates corresponding to the starting frame in the movement video, as well as the landing frame number and the landing coordinates where the target sphere falls into the target area in the movement video;

[0018] Calculating the displacement distance of the target sphere based on the sphere starting coordinates and the landing coordinates, and calculating the time difference based on the starting frame number and the landing frame number;

[0019] Calculating the hitting ball speed corresponding to the target sphere based on the displacement distance of the target sphere and the time difference.

[0020] Optionally, in some embodiments of the present application, obtaining the hitting action trajectory of the target user in the target space includes:

[0021] Collecting a hitting action video corresponding to the target user through a camera device pre-deployed in the target space;

[0022] Performing frame-by-frame analysis on the hitting action video to obtain corresponding human key element data and device key element data;

[0023] Performing normalization processing on the human key element data and the device key element data;

[0024] Generating the hitting action trajectory corresponding to the target user based on the normalized human key element data and device key element data.

[0025] Optionally, in some embodiments of the present application, the human key element data includes one or more combinations of the following: human key point data, line data, area data; the device key element data includes one or more combinations of the following: device key point data, line data, area data.

[0026] Optionally, in some embodiments of the present application, the human key element data at least includes the human key element data corresponding to the target user holding the sports device.

[0027] Optionally, in some embodiments of the present application, the device key point data includes one or more combinations of the following: the highest end point data of the sports device, the lowest end point data of the sports device, the leftmost end point data of the sports device, the rightmost end point data of the sports device, and / or the geometric center of gravity point data.

[0028] Optionally, in some embodiments of the present application, the evaluation of the hitting effect based on the user's hitting data to obtain the hitting effect evaluation result includes:

[0029] Calculating the difference between the hitting landing point position of the target sphere and the center coordinates of the target area to obtain the landing deviation value;

[0030] Comparing and analyzing the hitting action trajectory of the target user with the standard action trajectory to obtain the action standardization analysis result;

[0031] Evaluating the hitting effect based on the landing deviation value, the hitting ball speed, and the action standardization analysis result to obtain the hitting effect evaluation result corresponding to the target user.

[0032] Optionally, in some embodiments of the present application, after evaluating the hitting effect based on the user's hitting data to obtain the hitting effect evaluation result, the method further includes:

[0033] Generating corresponding personalized training suggestions based on the hitting effect evaluation result;

[0034] Obtaining the historical evaluation result of the hitting effect of the target user and generating a corresponding training technical report based on the historical evaluation result of the hitting effect;

[0035] Real-time feedback at least one of the hitting effect evaluation result, the personalized training suggestion, and the training technical report to the intelligent mobile terminal of the target user.

[0036] In a second aspect, an embodiment of the present application provides a hitting effect evaluation device, including:

[0037] A data acquisition module, configured to acquire the user's hitting data in the target space, where the user's hitting data includes the hitting landing point position, the hitting ball speed, and the hitting action trajectory;

[0038] An effect evaluation module, configured to evaluate the hitting effect based on the user's hitting data to obtain the hitting effect evaluation result.

[0039] In a third aspect, an embodiment of the present application further provides a hitting effect evaluation system, including a data acquisition device, a tennis service device, and a display device;

[0040] The data acquisition device is configured to obtain user hitting data in a target space and send it to the tennis service device;

[0041] The tennis service device is configured to perform hitting effect evaluation based on the received user hitting data to obtain a hitting effect evaluation result;

[0042] The display device is configured to provide real-time feedback on the hitting effect evaluation result.

[0043] In a fourth aspect, an embodiment of the present application further provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it performs the steps of the hitting effect evaluation method as described in the first aspect.

[0044] In a fifth aspect, an embodiment of the present application further provides a readable storage medium storing a computer program, and when the computer program is executed by a processor, it implements the computer program of the hitting effect evaluation method as described in the first aspect.

[0045] The present application provides a hitting effect evaluation method, device, system, electronic device, and storage medium. The hitting effect evaluation method includes: obtaining user hitting data in a target space, where the user hitting data includes one or more combinations of the following: hitting landing point position, hitting ball speed, and hitting motion trajectory; performing hitting effect evaluation based on the user hitting data to obtain a hitting effect evaluation result. In the hitting effect evaluation solution provided by the present application, the user hitting data in the target space is automatically and real-time obtained, and the hitting landing point position is comprehensively considered. By comprehensively considering the hitting landing point position, hitting ball speed, and hitting motion trajectory in the user hitting data, real-time and comprehensive hitting evaluation of multiple users in the target space can be performed, avoiding the situation where the manual evaluation method may lead to inaccurate evaluation results and omission of details, effectively improving the accuracy and comprehensiveness of hitting effect evaluation, as well as the efficiency and real-time performance of simultaneously evaluating multiple users, so as to provide more targeted training suggestions for athletes subsequently and improve the user training efficiency; in addition, the present application can implement hitting effect evaluation by using simple devices, without using high-cost and complex hardware devices, reducing the dependence on professional technical personnel and lowering the labor cost and equipment cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] To more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those skilled in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0047] Figure 1 is an application environment diagram of the hitting effect evaluation method provided by an embodiment of the present application;

[0048] Figure 2 is an application environment diagram of the hitting effect evaluation method provided by another embodiment of the present application;

[0049] Figure 3 is a schematic flowchart of the hitting effect evaluation method provided by an embodiment of the present application;

[0050] Figure 4 is a schematic diagram of key points when a target object is performing tennis training provided by an embodiment of the present application;

[0051] Figure 5 is another schematic flowchart of the hitting effect evaluation method provided by an embodiment of the present application;

[0052] Figure 6 is a schematic structural diagram of the hitting effect evaluation device provided by an embodiment of the present application;

[0053] Figure 7 is another schematic structural diagram of the hitting effect evaluation device provided by an embodiment of the present application;

[0054] Figure 8 is a schematic structural diagram of the electronic device provided by an embodiment of the present application. Specific Embodiments

[0055] Here, the exemplary embodiments will be described in detail, and the examples are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are only examples of systems and methods consistent with the examples detailed in the appended claims or some aspects of the present application.

[0056] It should be noted that in this text, descriptions such as "including", "comprising" or any other variants thereof are intended to cover non-exclusive inclusion. Thus, a process, method, article or device that includes a series of elements not only includes those elements, but also includes other elements not explicitly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, article or device that includes such element. In addition, components, features, and elements with the same name in different embodiments of this application may have the same meaning or different meanings, and their specific meanings need to be determined based on their explanations in the specific embodiments or further in combination with the context in the specific embodiments.

[0057] It should be understood that the specific embodiments described herein are only used to explain this application and are not used to limit this application.

[0058] In subsequent descriptions, the use of suffixes such as "module", "component" or "unit" to represent elements is only for the convenience of explaining this application, and they have no specific meaning in themselves. Therefore, "module", "component" or "unit" can be used interchangeably.

[0059] Currently, in ball game training, the existing technical movement evaluation techniques mainly rely on the observation and experience of human coaches, or rely on high-cost multi-camera device systems, professional sensors, complex hardware devices, etc. Although the existing technologies can provide accurate data analysis, due to the high equipment cost, complex operation and reliance on a large amount of hardware support, there are certain limitations in terms of popularity and cost-effectiveness. Therefore, how to comprehensively and accurately evaluate the hitting effect of users during the movement process using simple devices under the premise of controllable costs, so as to provide a data basis for subsequent optimization plans, has become an urgent problem to be solved in the current ball game training field.

[0060] To solve the above technical problems, the embodiments of this application provide a hitting effect evaluation method, device, system, electronic device and storage medium. By comprehensively analyzing the hitting point, ball speed and movement standardization, and simultaneously evaluating the hitting effects of multiple athletes in an all-round and real-time manner, the accuracy and comprehensiveness of the hitting effect evaluation are effectively improved, so as to provide more targeted training suggestions for athletes subsequently.

[0061] Figure 1 It is an application environment diagram of the hitting effect evaluation method in an embodiment. Refer to Figure 1, the hitting effect evaluation method is applied to a hitting effect evaluation system. The hitting effect evaluation system includes a terminal 110 and a server 120. The terminal 110 and the server 120 are connected through a network. The terminal 110 can specifically be a desktop terminal or a mobile terminal, and the mobile terminal can specifically be at least one of a mobile phone, a tablet computer, a laptop computer, etc. The server 120 can be implemented by an independent server or a server cluster composed of multiple servers. The terminal 110 is used to obtain the hitting effect evaluation, and the server 120 is used to obtain the user hitting data in the target space, where the user hitting data includes one or more combinations of the following: hitting landing position, hitting ball speed, and hitting motion trajectory; and perform hitting effect evaluation based on the user hitting data to obtain a hitting effect evaluation result.

[0062] The hitting effect evaluation method provided by the embodiments of the present application can be applied in an application environment such as Figure 1 . Among them, the computer device 110 communicates with the server 120 through the network 130. The computer device 110 is used to obtain the hitting effect evaluation, and the server 120 is used to obtain the user hitting data in the target space, where the user hitting data includes one or more combinations of the following: hitting landing position, hitting ball speed, and hitting motion trajectory; and perform hitting effect evaluation based on the user hitting data to obtain a hitting effect evaluation result. In the present application, by comprehensively analyzing the hitting landing point, ball speed, and action standardization, and simultaneously performing all-round and real-time hitting effect evaluation on multiple athletes, the accuracy and comprehensiveness of the hitting effect evaluation are effectively improved, so as to provide more targeted training suggestions for athletes subsequently. Among them, the computer device 110 can be but is not limited to various smart phones 110-1, tablet computers 110-2, and laptop computers 110-3. The following describes the present application in detail through specific embodiments.

[0063] It should be noted that the hitting effect evaluation method provided by the embodiments of the present application can be applied to a variety of ball games, such as tennis, table tennis, badminton, and golf, etc., and no specific limitation is made here.

[0064] The action evaluation method provided by the embodiments of the present application can be applied in a hitting effect evaluation system as shown in Figure 2 . The hitting effect evaluation system includes a data acquisition device 140, a tennis service device 160, and a display device 170; among them, the data acquisition device 140 obtains the user hitting data of the target object 150 in the target space through the network 130 and sends it to the tennis service device 160; the tennis service device 160 obtains the user hitting data through the network 130 and performs hitting effect evaluation based on the user hitting data to obtain a hitting effect evaluation result; the display device 170 obtains the hitting effect evaluation result from the tennis service device 160 in real time through the network 130 and feeds it back.

[0065] The data acquisition device 140 is configured to acquire the user's hitting data of the target object 150 in the target space and send it to the tennis service device 160;

[0066] Specifically, the data acquisition device 140 is responsible for acquiring the user's hitting data in the target space, including the hitting landing position, hitting ball speed, hitting motion trajectory, etc. The data acquisition device may include sensors (such as radio frequency identification sensors, laser positioning systems) and cameras (for capturing hitting actions and ball speed). These devices are deployed in the target space (such as a tennis court) to collect hitting-related data in real time.

[0067] In addition, the data acquisition device can combine multiple sensors (such as IMU, pressure sensors) and high-frame-rate cameras to enrich the data acquisition dimension. For example, the IMU can be installed on the racket or the athlete to provide acceleration and angular velocity data, further improving the accuracy of motion analysis. Also, an adaptive sensor network is deployed to dynamically adjust the sampling frequency and coverage range of the sensors according to the hitting scenario. For example, during difficult hitting actions, increase the sampling frequency of the sensors to capture more detailed motion data.

[0068] The tennis service device 160 is configured to evaluate the hitting effect based on the received user's hitting data and obtain a hitting effect evaluation result;

[0069] Specifically, the tennis service device is used to receive the hitting data sent by the data acquisition device and perform a hitting effect evaluation to generate an evaluation result. The tennis service device can be a server or a high-performance computing device that runs a hitting effect evaluation algorithm. These algorithms comprehensively analyze the hitting effect based on the multi-dimensional evaluation methods (such as hitting landing deviation, ball speed, motion standardization, etc.) described in the above embodiments.

[0070] In addition, deep learning models (such as CNN, RNN) can be integrated into the tennis service device to automatically identify hitting actions, calculate ball speed, and evaluate motion standardization. For example, by training the model to identify standard hitting actions, automatically score the athlete's actions. And utilize the powerful computing power of cloud computing to process complex data analysis tasks, while achieving fast real-time feedback through edge computing. For example, allocate some data processing tasks to edge devices close to the data source to reduce latency.

[0071] The display device 170 is configured to provide real-time feedback on the hitting effect evaluation result;

[0072] Specifically, the display device is used to provide real-time feedback on the hitting effect evaluation result, enabling the user to intuitively understand their hitting performance. The display device can be a screen, a mobile terminal, or other visualization devices, and the feedback forms can include graphical interfaces, real-time scoring, voice prompts, etc.

[0073] In addition, the display device can incorporate AR / VR technology to provide athletes with an immersive training experience. For example, it can display the evaluation results of the hitting effect in real time through AR glasses, or simulate different hitting scenarios in a VR environment to help athletes adapt to various competition environments. At the same time, according to the training goals and historical data of the athletes, a personalized feedback interface is generated. For example, more detailed action guidance is provided for beginners, and more accurate technical analysis is provided for advanced athletes.

[0074] In a specific embodiment, the hitting effect evaluation system can be integrated with the Internet of Things platform to achieve seamless communication and data sharing between devices. For example, the device status is monitored in real time through the IoT platform to ensure the stable operation of the system. The system is designed to adapt to various training scenarios, such as standard tennis courts, serving machine training grounds, AR / VR virtual training environments, etc. For example, for the serving machine training ground, the evaluation algorithms for ball speed and landing point are optimized.

[0075] In this embodiment, through multi-modal data acquisition and deep learning algorithms, the system can comprehensively and accurately evaluate the hitting effect, covering multiple dimensions such as hitting landing point, ball speed, and action standardization; the combination of the intelligent sensor network and the high-frame-rate camera further improves the accuracy of data acquisition; combined with edge computing and AR / VR technology, the system can provide real-time feedback on the evaluation results of the hitting effect to help athletes adjust their actions immediately; the personalized feedback interface and immersive training experience enhance the interactivity and user experience of the system. At the same time, the application of deep learning models and cloud computing technology enables the system to automatically identify hitting actions and generate evaluation results, reducing manual intervention, and the self-adaptive ability of the system enables it to dynamically adjust data acquisition and processing strategies according to the training scenario.

[0076] Please refer to Figure 3 , Figure 3 which is a schematic flowchart of the hitting effect evaluation method provided by an embodiment of the present application. In this embodiment, the hitting effect evaluation method is mainly exemplified by being applied to a computer device. The hitting effect evaluation method provided by an embodiment of the present application includes the following steps:

[0077] S1. Obtain user hitting data in the target space, where the user hitting data includes one or more combinations of the following: hitting landing point position, hitting ball speed, and hitting action trajectory;

[0078] Specifically, for step S1, user hitting data of a target user in a target space during movement is obtained through a single sensor and a camera device, where the user hitting data may specifically include one or more of the hitting landing point position, hitting ball speed, and hitting action trajectory. By simultaneously collecting at least one of the three key index data of the hitting landing point position, hitting ball speed, and hitting action trajectory, comprehensive data support is provided for the subsequent comprehensive evaluation of the hitting effect.

[0079] S2. Evaluate the hitting effect based on the user hitting data to obtain a hitting effect evaluation result;

[0080] Specifically, for step S2, it is mainly to comprehensively evaluate the hitting effect of the user during the current movement process in all aspects according to the hitting landing point position, hitting ball speed, and hitting action trajectory obtained in step S1, combined with the user's current technical level and a preset training goal, so as to obtain a hitting effect evaluation result. This helps the user fully understand the technical condition of this hitting movement, and subsequently provide technical improvement suggestions for the user, helping the user adjust the action in time and improve the training efficiency.

[0081] It can be seen that the hitting effect evaluation method provided in this embodiment avoids the use of a high-cost multi-camera device system and complex hardware devices by using a single camera device and a sensor, significantly reducing the equipment procurement and maintenance costs. At the same time, it simplifies the operation process of the equipment, enabling ordinary coaches and athletes to independently complete the installation, debugging, and use of the equipment without professional technical personnel, reducing the dependence on professional technical personnel and further reducing the labor cost. And by comprehensively analyzing the three key indexes of the hitting landing point, ball speed, and action standardization of the user during this movement process, it can simultaneously conduct all-round and real-time hitting effect evaluations on multiple athletes, not only effectively improving the accuracy and comprehensiveness of the hitting effect evaluation, but also improving the efficiency of the multi-user hitting effect evaluation.

[0082] Optionally, in some embodiments, step S1 "obtain user hitting data in a target space" may specifically include:

[0083] S11. Obtain the hitting landing point position of a target sphere in a target space during movement;

[0084] S12. Obtain the hitting ball speed of the target sphere in the target space;

[0085] S13. Obtain the hitting action trajectory of the target user in the target space;

[0086] Specifically, for step S1, the position data of the ball in the air, especially the landing point of the ball after hitting, is collected in real time by sensors (such as radio frequency identification sensors, laser positioning systems, etc.) pre-deployed in the target space. Among them, the sensors can be installed at different positions on the court, and the installation positions can be set according to the actual scenario requirements. At the same time, a high-frame-rate imaging device is used to capture the position information of the tennis ball during the hitting process, form the flight trajectory of the tennis ball in the air, and thus calculate the hitting speed of the target sphere in the target space. In addition, the hitting action of the athlete is also captured and analyzed in real time by the imaging device, so as to analyze the hitting action trajectory of the target user in the target space.

[0087] In this embodiment, by using a single imaging device and sensors, the use of high-cost multi-camera systems and complex hardware devices is avoided, and the equipment procurement and maintenance costs are significantly reduced; the combined use of sensors and high-frame-rate imaging devices can accurately capture the flight trajectory, landing point position and hitting speed of the ball, ensuring the accuracy of the evaluation data.

[0088] Optionally, in some embodiments, step S11, "obtain the hitting landing point position of the target sphere in the target space during the movement process", may specifically include:

[0089] S111. Collect the movement trajectory of the target sphere through sensors pre-deployed in the target space;

[0090] Specifically, for step S111, first, sensors are deployed at different locations in the target space. The types of sensors can be radio frequency identification sensors (RFID), laser positioning systems, infrared sensors, etc. The sensors can be installed at different positions on the court, such as net posts, baselines, sidelines, etc., to ensure full coverage of the ball's flight trajectory. In the actual scenario, the layout of the sensors needs to consider the geometric shape of the court and the competition rules to ensure that hits at different positions and in different directions can be accurately captured. For example, one sensor can be installed at each of the four corners and the net posts of the court to form a three-dimensional sensor network. The sensors record the flight trajectory of the ball in the air in real time, especially the landing point of the ball after hitting. The sensors capture the position information of the ball through high-frequency signals and transmit this position information to the central processing unit. In addition, the data collection frequency needs to meet the preset conditions to ensure that every position change of the ball can be accurately captured.

[0091] S112. Identify the hitting landing point position of the target sphere based on the movement trajectory;

[0092] Specifically, for step S112, the received sensor data is analyzed to identify the final landing position of the ball. For example, through data processing algorithms such as Kalman filtering and particle filtering, the sensor data is filtered and fused to improve the accuracy and reliability of the data. During the process of landing point identification, machine learning algorithms such as support vector machine (SVM) and neural network can be used to analyze the processed data to identify the landing position of the ball. Through machine learning algorithms, the landing point characteristics of the ball under different flight trajectories can be learned to improve the accuracy of identification. In addition, according to the preset target area (such as the serving area, the baseline area, etc.), the target area is calibrated by detecting the key point coordinates of the target area. The calibration of the target area can use manual calibration or automatic calibration methods to ensure the accuracy of the target area.

[0093] In this embodiment, by using sensors, the flight trajectory of the ball can be accurately captured to ensure the accuracy of the landing position; through a reasonable sensor layout, the entire court is covered to avoid detection blind spots and improve the integrity of the data; after obtaining the sensor data, through data processing and machine learning algorithms, the landing position of the ball can be accurately identified to improve the accuracy of the evaluation.

[0094] Optionally, in some embodiments, step S12, "obtaining the hitting ball speed of the target sphere in the target space", may specifically include:

[0095] S121. Collect the motion video of the target sphere during its movement through a camera device pre-deployed in the target space;

[0096] S122. Identify the starting frame number and the starting coordinates of the sphere corresponding to the starting frame in the motion video, as well as the landing frame number and landing coordinates of the target sphere falling into the target area in the motion video;

[0097] S123. Calculate the displacement distance of the target sphere based on the starting coordinates and the landing coordinates of the sphere, and calculate the time difference based on the starting frame number and the landing frame number;

[0098] S124. Calculate the hitting ball speed corresponding to the target sphere based on the displacement distance and the time difference of the target sphere.

[0099] Specifically, for step S12, first, a high-frame-rate imaging device is used to collect the motion video of the target sphere in the target space. For example, an industrial-grade imaging device with 240 fps or higher is used to obtain the video, ensuring that every detail of the ball during high-speed movement can be captured. The imaging device can be installed at multiple angles on the court to ensure comprehensive capture of the ball's flight trajectory. The layout of the imaging device also needs to consider the geometric shape of the court and the competition rules to ensure that shots at different positions and in different directions can be accurately captured. For example, an imaging device can be installed on each side and at the rear of the court to form a three-dimensional imaging device network. The position information of the tennis ball during the hitting process is captured at a high frame rate (such as 240 fps or higher) by the high-frame-rate imaging device to form a video of the ball's flight trajectory in the air.

[0100] Then, the video data is transmitted in real-time to the central processing unit for analysis. Image processing algorithms, such as background subtraction method, optical flow method, etc., are used to identify the starting frame of the ball in the motion video. The starting frame refers to the moment when the ball is hit. The algorithm determines the starting frame by detecting the sudden appearance and movement changes of the ball. Similarly, image processing algorithms are used to identify the landing frame where the ball falls into the target area. The landing frame refers to the moment when the ball touches the ground or the target area. The algorithm determines the landing frame by detecting the stop of the ball's movement and the changes when it touches the ground.

[0101] After identifying the starting frame and the landing frame, the coordinate positions of the ball in these video frames are extracted. Coordinate extraction can use image recognition techniques, such as feature point detection, template matching, etc., to ensure the accuracy of the coordinate positions.

[0102] Next, the Euclidean distance formula is used to calculate the displacement distance between the starting coordinates and the landing coordinates of the sphere. The displacement distance d can be calculated by the following formula:

[0103]

[0104] where (x1, y1, z1) and (x2, y2, z2) are the starting coordinates and the landing coordinates respectively;

[0105] The time difference between the starting frame number and the landing frame number is calculated. The time difference t can be calculated by the following formula:

[0106] t = (landing frame number - starting frame number) / frame rate;

[0107] where the frame rate is the frame rate of the imaging device, such as 240 fps.

[0108] Finally, the ball speed is calculated using the displacement distance and the time difference. The ball speed v can be calculated by the following formula:

[0109] v = d / t;

[0110] Where d is the displacement distance and t is the time difference.

[0111] The ball speed is scored according to the set athlete grading. The athlete ability grading can be divided into poor (ball speed [0 - 40]), average (ball speed [40 - 80]), and good (ball speed [80 - 120]). The ball speeds under different gradings are finally normalized to the scoring range of [0 - 100].

[0112] In this embodiment, the high - frame - rate imaging device can accurately capture the flight trajectory of the ball to ensure the accuracy of ball speed measurement; through the image - processing algorithm, the starting frame and the landing frame can be accurately identified to ensure the accuracy of the coordinate position; through the calculation using the Euclidean distance formula and the time difference, the displacement distance and the flight time of the ball can be accurately calculated to ensure the accuracy of ball speed calculation; by accurately calculating the ball speed, the hitting force and speed of the athlete can be accurately evaluated to provide a detailed and accurate ball speed score.

[0113] Optionally, in some embodiments, step S13, "acquire the hitting action trajectory of the target user in the target space", may specifically include:

[0114] S131. Collect the hitting action video of the target user through the imaging device pre - deployed in the target space;

[0115] S132. Analyze the hitting action video frame by frame to obtain the corresponding human key element data and device key element data;

[0116] S133. Perform normalization processing on the human key element data and the device key element data;

[0117] S134. Generate the hitting action trajectory of the target user based on the normalized human key element data and device key element data.

[0118] Specifically, for step S13, first, use a high - frame - rate imaging device to obtain the hitting action video of the target user in the target space during this ball game. An industrial - grade imaging device such as 240fps or higher can be used to ensure that every detail of the athlete's hitting action can be captured. The layout of the imaging device needs to consider the geometry of the court and the game rules to ensure that hitting actions in different positions and directions can be accurately captured. For example, one imaging device can be installed on each side and at the rear of the court to form a three - dimensional imaging device network. The high - frame - rate imaging device captures the hitting action video of the athlete at a high frame rate (such as 240fps or higher) to form a detailed action trajectory video. The video data is transmitted to the central processing unit in real time for analysis.

[0119] Then, computer vision technologies such as OpenPose and AlphaPose are used to analyze the key points of the human body (such as the hips, shoulders, elbows, wrists, etc.) and the key element data of the device frame by frame. Through computer vision technologies, the key points of the human body and the racket can be identified and tracked in real time, and the key point coordinates of each frame can be generated. The coordinate data of the key points of the human body and the key elements of the device are extracted in each frame to form a structure array, and the member variables include the array of key points of the human body and the array of key elements of the device. The array of key points of the human body and the array of key elements of the device will be used for subsequent action trajectory generation and standardization evaluation.

[0120] Next, calculate the Euclidean distance from the top of the head to the bottom of the foot, and normalize the key points of the human body and the key elements of the device according to the Euclidean distance. The normalization process can eliminate the influence of individual differences such as human height and arm length, making the action data of different athletes comparable. Through the normalization process, the key element data is standardized into a unified coordinate system to ensure that the action data of different athletes can be evaluated under the same standard.

[0121] Use curve fitting methods (such as spline curve fitting) to connect the normalized key element data of the human body and the key element data of the device into a smooth curve to generate the entire hitting action trajectory, so as to intuitively display the hitting action of the athlete and facilitate subsequent standardization evaluation.

[0122] Finally, by analyzing the generated hitting action trajectory, evaluate the smoothness, accuracy, and standardization degree of the athlete's actions. For example, metrics such as IoU (Intersection over Union) can be used to compare the athlete's action trajectory with the standard action trajectory to generate an action standardization score.

[0123] Exemplarily, as Figure 4 shown, when the target object is undergoing tennis training, the identified key points of the human body and the device can specifically include the head key point a11, neck key point a12, left shoulder key point a13, right shoulder key point a14, left elbow key point a15, left wrist key point a16, left hip key point a17, right hip key point a18, right elbow key point a19, right wrist key point a20, the top key point a21 of the racket handle, the top key point a22 of the racket head, the bottom key point a24 of the racket head, right knee key point a25, left knee key point a26, left ankle key point a27, and right ankle key point a28. Among them, a23 is the key area of the badminton racket, and the top key point a21 of the racket handle, the top key point a22 of the racket head, and the bottom key point a24 of the racket head, that is, the target key points, can be identified through the detected key area of the tennis racket.

[0124] In this embodiment, a high - frame - rate imaging device is used to accurately capture the hitting actions of athletes, ensuring the accuracy of the action trajectories. Through computer vision technology, key points of the human body and the racket can be accurately identified and tracked. Through normalization processing, the key element data is standardized into a unified coordinate system, ensuring that the action data of different athletes can be evaluated under the same standard. And through the curve fitting method, a smooth and accurate hitting action trajectory can be generated, ensuring the accuracy of action evaluation.

[0125] Optionally, in some embodiments, the human body key element data includes one or more combinations of the following: human body key point data, line data, and region data; the device key element data includes one or more combinations of the following: device key point data, line data, and region data.

[0126] Specifically, the human body key element data refers to the key information used to describe the physical state and actions of athletes in the analysis of hitting actions. The human body key element data is extracted from the video frames captured by the camera and mainly includes one or more combinations of the following types:

[0127] Human body key point data: Refers to the coordinate information of the key parts of the athlete's body, such as the shoulders, elbows, wrists, knees, ankles, etc. These key points are the basis for analyzing hitting actions and can reflect the body posture and action accuracy of the athlete. For example, by analyzing the movement trajectory of the wrist, it can be judged whether the racket face angle is correct at the moment of hitting the ball.

[0128] Human body key line data: Refers to the line segments connecting the human body key points, used to describe the relative positions and movement trajectories of various parts of the body. For example, the line connecting the shoulder to the wrist can reflect the extension degree of the arm, and the line connecting the knee to the ankle can analyze the leg's force application.

[0129] Human body key region data: Refers to the specific regions around the human body key points or key parts, used to analyze the range and stability of body actions. For example, analyzing the region around the wrist can judge the stability and flexibility at the moment of hitting the ball.

[0130] Specifically, the device key element data refers to the key information related to the hitting device (such as a racket). These data are also extracted from the video frames captured by the camera and mainly include one or more combinations of the following types:

[0131] Device key point data: Refers to the coordinate information of the key parts of the hitting device (such as a racket), such as the highest point, lowest point, left - most point, right - most point, and geometric center of gravity point of the racket, etc. These key points are used to analyze the movement trajectory of the racket and the device state at the moment of hitting the ball. For example, by analyzing the position of the center of gravity point of the racket, the stability and accuracy of hitting the ball can be judged.

[0132] Device key line data: It refers to the line segment connecting key points of the device, which is used to describe the movement trajectory and posture of the device. For example, the line connecting the highest point to the lowest point of the racket can reflect the swinging trajectory of the racket, and the line connecting the center of gravity point of the racket to the hitting point can analyze the direction of the hitting force.

[0133] Device key area data: It refers to a specific area around the key points or key parts of the device, which is used to analyze the movement range and stability of the device. For example, analyzing the area around the racket head can determine the stability of the device at the moment of hitting the ball.

[0134] In this embodiment, by combining human key element data and device key element data, it is possible to comprehensively analyze the hitting actions of athletes, including not only body postures but also the usage of hitting devices, providing more comprehensive evaluation results, applicable to various training scenarios, including standard courts, serving machine training grounds, and virtual training environments, with wide applicability.

[0135] Optionally, in some embodiments, the human key element data at least includes the human key element data corresponding to the target user holding the sports device.

[0136] Specifically, in this embodiment, human key element data refers to the key information of the body parts related to the hitting actions of athletes, which is used to analyze the standardization, fluency, and hitting effect of athletes' actions. Human key element data can specifically include the key element data of the body parts related to holding the sports device (such as a tennis racket). Specifically, it includes the following aspects:

[0137] Body parts in direct contact with the sports device: For example, the athlete's hand (wrist, fingers), arm (elbow, shoulder), etc. These parts are directly involved in the execution of the hitting action.

[0138] Body postures related to the sports device: For example, the position of the athlete's body center of gravity and the leg support situation (knees, ankles) at the moment of hitting the ball. Although these parts do not directly contact the sports device, they have a direct impact on the hitting effect.

[0139] This embodiment can more accurately capture and evaluate the hitting actions of athletes, especially the standardization of the actions of the body parts directly related to the sports device, through refined data collection and in-depth action analysis.

[0140] Optionally, in some embodiments, the device key point data includes one or more of the following combinations: the highest endpoint data of the sports device, the lowest endpoint data of the sports device, the leftmost endpoint data of the sports device, the rightmost endpoint data of the sports device, and / or the geometric center of gravity point data.

[0141] Specifically, the key point data of the device in this embodiment refers to the geometric features and motion state data related to the hitting device (such as a tennis racket), which are mainly used to analyze the position, posture, and motion trajectory of the device during the hitting process, so as to evaluate the accuracy and standardization of the hitting effect. Specifically, it can include the following types:

[0142] Highest endpoint data: The highest point position of the device in the vertical direction, which is used to analyze the posture of the device and the swing trajectory at the moment of hitting the ball.

[0143] Lowest endpoint data: The lowest point position of the device in the vertical direction, which is used to evaluate the motion range and stability of the device.

[0144] Leftmost endpoint data and rightmost endpoint data: The leftmost and rightmost point positions of the device in the horizontal direction, which are used to analyze the lateral motion trajectory of the device and the posture of the device at the moment of hitting the ball.

[0145] Geometric center of gravity point data: The center of gravity position of the device, which is used to evaluate the stability of hitting the ball and the efficiency of force transmission.

[0146] The key point data of the device in this embodiment is collected by a camera or other sensors and analyzed in combination with computer vision technology, providing an important basis for evaluating the hitting effect.

[0147] Optionally, in some embodiments, step S2, "evaluating the hitting effect based on the user's hitting data to obtain the hitting effect evaluation result", may specifically include:

[0148] S21. Calculate the difference between the hitting landing position of the target sphere and the center coordinates of the target area to obtain the landing deviation value;

[0149] Specifically, for step S21, first preset a target area, such as a service area, a baseline area, etc., and calibrate the center coordinates of the target area through key point coordinate detection. The calibration of the target area can use manual calibration or automatic calibration methods to ensure the accuracy of the target area. The landing position of the target sphere collected by a sensor or a camera device is used to identify the final landing coordinates of the ball. Calculate the difference between the landing coordinates and the center coordinates of the target area to obtain the landing deviation value. The landing deviation value can be calculated by the Euclidean distance formula:

[0150]

[0151] Wherein, (x 落点 , y 落点 ) are the landing coordinates of the ball, and (x 中心 , y 中心 ) are the center coordinates of the target area.

[0152] Map the landing point deviation value to the scoring range of [0 - 100]. The smaller the landing point deviation value, the higher the score. For example, linear mapping or non-linear mapping methods can be used to convert the deviation value into a score.

[0153] S22. Compare and analyze the hitting action trajectory of the target user with the standard action trajectory to obtain the analysis result of action standardization;

[0154] Specifically, for step S22, preset the standard action trajectory. The standard action trajectory can be the action trajectory demonstrated by a professional coach or a model trained with the action data of a large number of professional athletes. Compare and analyze the hitting action trajectory of the target user with the standard action trajectory. For example, indicators such as IoU (Intersection over Union) can be used to compare the action trajectory of the trainee with the standard action trajectory to generate an action standardization score. The swing action trajectories of the trainee and the coach are converted into closed polygons through curve fitting methods (such as spline curve fitting). During the conversion process, the discrete points of the trajectory are connected into a smooth curve through interpolation or approximation methods, and then a closed polygon is constructed. Use computational geometry algorithms (such as convex hull algorithm, Monte Carlo algorithm, etc.) to calculate the intersection and union of the two polygons. The intersection represents the overlapping part of the two trajectories in space, and the union represents the total area covered by the two trajectories. The IoU value is calculated by the following formula:

[0155]

[0156] where A 交 is the area of the intersection, A 并 is the area of the union. The larger the IoU value, the higher the coincidence degree of the two trajectories, indicating that the action of the trainee is closer to the standard trajectory. Normalize the IoU value to the scoring range of [0 - 100] to generate an action standardization score. The higher the IoU value, the higher the score.

[0157] S23. Evaluate the hitting effect based on the landing point deviation value, hitting ball speed, and the analysis result of action standardization to obtain the hitting effect evaluation result corresponding to the target user.

[0158] Specifically, for step S23, perform weighted analysis on the landing point deviation value, hitting ball speed, and the analysis result of action standardization. According to the technical level and training objectives of the athlete, different weight coefficients are assigned to each dimension. For example, for beginners, more attention may be paid to action standardization, while for advanced athletes, more attention may be paid to ball speed and landing point accuracy. Generate a comprehensive score based on the weighted analysis result. The comprehensive score can be calculated by the following formula:

[0159] Comprehensive score = w1 × landing point score + w2 × ball speed score + w3 × action standardization score;

[0160] Among them, w1, w2, and w3 are weight coefficients, and w1 + w2 + w3 = 1.

[0161] Finally, generate the evaluation results of the hitting effect, including the comprehensive score, the landing point score, the ball speed score, and the action standardization score. In addition, the evaluation results can be fed back to the athlete in real time through means such as the screen and voice.

[0162] This embodiment can accurately evaluate the landing accuracy of the ball by precisely calculating the landing point deviation value, and provide a detailed landing point score; accurately evaluate the action standardization of the athlete through indicators such as the IoU value, and provide detailed action improvement suggestions; comprehensively consider the three key indicators of the landing point deviation value, the hitting ball speed, and the action standardization, provide a comprehensive evaluation of the hitting effect, and help the athlete fully understand their technical status; quickly generate the comprehensive score and detailed evaluation results to ensure that the evaluation results can be fed back to the athlete in real time to help them adjust their actions in a timely manner.

[0163] Optionally, as Figure 5 shown, in some embodiments, after step S2 "evaluate the hitting effect based on the user's hitting data to obtain the evaluation results of the hitting effect", it may specifically further include:

[0164] S3. Generate corresponding personalized training suggestions based on the evaluation results of the hitting effect;

[0165] Specifically, for step S3, analyze the athlete's performance in terms of hitting landing point, ball speed, and action standardization according to the evaluation results of the hitting effect. The evaluation results include the comprehensive score, the landing point score, the ball speed score, and the action standardization score. Then, generate personalized training suggestions according to the evaluation results. For example, if the athlete has a large deviation in the landing point, it is recommended to strengthen the hitting practice in the target area; if the ball speed is slow, it is recommended to carry out strength training; if the action standardization score is low, it is recommended to carry out action correction training.

[0166] In addition, the training suggestions can be refined to specific practice methods, practice frequencies, and practice durations. For example, it is recommended that the athlete carry out 30 minutes of serving landing point practice every day, carry out strength training twice a week, and each time for 45 minutes.

[0167] The personalized training suggestions generated according to the evaluation results in this embodiment can specifically help the athlete improve technical problems and improve training efficiency; the training suggestions can be fed back to the athlete in real time to help them adjust the training plan in a timely manner to ensure the training effect; through the personalized training suggestions, the athlete can discover and improve technical problems faster, significantly improve the hitting quality, and accelerate the technical progress.

[0168] S4. Obtain the historical evaluation results of the hitting effect of the target user, and generate the corresponding training technology report based on the historical evaluation results of the hitting effect;

[0169] Specifically, for step S4, record the evaluation results of the hitting effect of the target user for each training, including the comprehensive score, landing point score, ball speed score, and action standardization score, and store these data in the database to form the training history record of the athlete. Generate a detailed training technology report based on the historical evaluation results. The report content includes: the comprehensive score and scores of each dimension for each training; the change trend of the scores, such as progress or regression; the implementation situation and effect evaluation of personalized training suggestions; the next training plan and suggestions. Among them, the generation of the technology report can be presented in the form of charts, text descriptions, and data analysis to ensure the intuitiveness and readability of the report.

[0170] In a specific embodiment, through data recording and analysis, provide long-term training tracking services for athletes. A technology report will be generated after each training, recording the hitting effect of the athlete, including the accuracy of the hitting landing point, the improvement of the ball speed, the improvement of the action standardization, etc., to help coaches and athletes formulate subsequent training plans.

[0171] This embodiment can provide long-term training tracking services for athletes by recording and analyzing historical evaluation results, helping coaches and athletes understand the training progress; the technology report provides a scientific decision-making basis for coaches, helping them formulate more reasonable training plans and optimize training methods; by analyzing historical data, coaches and athletes can adjust the training plan in a timely manner to ensure the continuous improvement of training effects.

[0172] S5. Real-time feedback at least one of the hitting effect evaluation result, personalized training suggestion, and training technology report to the intelligent mobile terminal of the target user;

[0173] Specifically, for step S5, send the hitting effect evaluation result, personalized training suggestion, and training technology report to the intelligent mobile terminal of the athlete (such as mobile phones, tablets, smart wearable devices, etc.) in real time through the network. The feedback can be in various forms, such as screen display, voice broadcast, SMS notification, etc. The screen display can include detailed score and suggestion pages, the voice broadcast can be used for real-time guidance during training, and the SMS notification can be used to remind athletes to view the detailed training report. The application program on the intelligent mobile terminal can provide a user interaction interface, and athletes can view detailed evaluation results, training suggestions, and technology reports, and can also set training goals and feedback preferences.

[0174] This embodiment ensures that athletes can timely understand their training effects and adjust the training plan in a timely manner through real-time feedback; they can view training results and suggestions anytime and anywhere, improving the convenience and flexibility of training; the user interaction interface enhances the athlete's sense of participation and satisfaction, stimulating their training enthusiasm.

[0175] It should be noted that this embodiment can adapt to different training scenarios, for example:

[0176] Set target areas on a standard tennis court through sensors to collect ball landing data; combine the position and ball speed set by the tennis serving machine in the tennis serving machine training ground to conduct special ball speed evaluation; and, provide an AR / VR training platform to combine virtual training scenarios and camera devices to achieve action evaluation and landing point analysis.

[0177] In summary, the hitting effect evaluation method provided in this embodiment obtains user hitting data in the target space, where the user hitting data includes one or more combinations of the following: hitting landing point position, hitting ball speed, and hitting action trajectory; based on the user hitting data, conduct hitting effect evaluation to obtain the hitting effect evaluation result. In the hitting effect evaluation solution provided in this embodiment, automatically and real-time obtain user hitting data in the target space, comprehensively consider the hitting landing point position, and by comprehensively considering the hitting landing point position, hitting ball speed, and hitting action trajectory in the user hitting data, it is possible to conduct real-time and all-round hitting evaluation on multiple users in the target space, avoid the situation that the manual evaluation method may lead to inaccurate evaluation results and omission of details, effectively improve the accuracy and comprehensiveness of the hitting effect evaluation, as well as improve the efficiency and real-time performance of simultaneously evaluating multiple users, so as to provide more targeted training suggestions for athletes in the future and improve the user training efficiency; in addition, this embodiment can achieve hitting effect evaluation by using simple devices, without using high-cost and complex hardware devices, reduce the dependence on professional technical personnel, and reduce labor costs and equipment costs.

[0178] It should be understood that although Figure 2 and Figure 3 the steps in the flowcharts of Figure 2 and Figure 3 are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover,

[0179] To facilitate better implementation of the hitting effect evaluation method of the embodiments of the present application, the embodiments of the present invention also provide a hitting effect evaluation device based on the above hitting effect evaluation method. The meanings of the nouns are the same as those in the above hitting effect evaluation method, and the specific implementation details can refer to the description in the method embodiments.

[0180] Please refer to Figure 6 , Figure 6 , which is a schematic structural diagram of the hitting effect evaluation device provided by the embodiment of the present application. The hitting effect evaluation device may specifically include a data acquisition module 201 and an effect evaluation module 202, which are specifically as follows:

[0181] The data acquisition module 201 is used to acquire user hitting data in the target space. The user hitting data includes one or more combinations of the following: hitting landing point position, hitting ball speed, and hitting action trajectory;

[0182] The effect evaluation module 202 is used to evaluate the hitting effect based on the user hitting data to obtain the hitting effect evaluation result.

[0183] Optionally, in some embodiments, the data acquisition module 201 may specifically include:

[0184] The landing point position acquisition unit is used to acquire the hitting landing point position of the target sphere during movement in the target space;

[0185] The hitting ball speed acquisition unit is used to acquire the hitting ball speed of the target sphere in the target space;

[0186] The action trajectory acquisition unit is used to acquire the hitting action trajectory of the target user in the target space.

[0187] Optionally, in some embodiments, the landing point position acquisition unit is specifically used for:

[0188] Collect the movement trajectory of the target sphere through sensors pre-deployed in the target space;

[0189] Identify the hitting landing point position of the target sphere based on the movement trajectory.

[0190] Optionally, in some embodiments, the hitting ball speed acquisition unit is specifically used for:

[0191] Collect the movement video of the target sphere during movement through a camera device pre-deployed in the target space;

[0192] Identify the starting frame number and sphere starting coordinates corresponding to the starting frame in the movement video, as well as the landing frame number and landing coordinates where the target sphere falls into the target area in the movement video;

[0193] Calculate the displacement distance of the target sphere based on the sphere starting coordinates and landing coordinates, and calculate the time difference based on the starting frame number and landing frame number;

[0194] Calculate the hitting ball speed corresponding to the target sphere based on the displacement distance and time difference of the target sphere.

[0195] Optionally, in some embodiments, the action trajectory acquisition unit is specifically configured to:

[0196] Collect a hitting action video of the target user through a camera device pre-deployed in the target space;

[0197] Analyze the hitting action video frame by frame to obtain corresponding human key element data and device key element data;

[0198] Normalize the human key element data and the device key element data;

[0199] Generate a hitting action trajectory corresponding to the target user based on the normalized human key element data and device key element data.

[0200] Optionally, in some embodiments, the human key element data includes one or more combinations of the following: human key point data, line data, and region data; the device key element data includes one or more combinations of the following: device key point data, line data, and region data.

[0201] Optionally, in some embodiments, the human key element data at least includes the human key element data corresponding to the target user holding the sports device.

[0202] Optionally, in some embodiments, the device key point data includes one or more combinations of the following: the highest endpoint data of the sports device, the lowest endpoint data of the sports device, the leftmost endpoint data of the sports device, the rightmost endpoint data of the sports device, and / or the geometric center of gravity point data.

[0203] Optionally, in some embodiments, the effect evaluation module 202 may specifically include:

[0204] The landing point deviation calculation unit is configured to calculate the difference between the hitting landing point position of the target sphere and the center coordinates of the target area to obtain a landing point deviation value;

[0205] The standardization analysis unit is configured to perform a comparison and analysis based on the hitting action trajectory of the target user and the standard action trajectory to obtain an action standardization analysis result;

[0206] The comprehensive evaluation unit is configured to perform a hitting effect evaluation on the landing point deviation value, the hitting ball speed, and the action standardization analysis result to obtain a hitting effect evaluation result corresponding to the target user.

[0207] Optionally, as Figure 7 shown, in some embodiments, the hitting effect evaluation device may specifically further include:

[0208] A suggestion module 203, configured to generate corresponding personalized training suggestions based on the evaluation results of the hitting effect;

[0209] A report module 204, configured to obtain the historical evaluation results of the hitting effect of the target user, and generate a corresponding training technology report based on the historical evaluation results of the hitting effect;

[0210] A feedback module 205, configured to feedback at least one of the hitting effect evaluation results, personalized training suggestions, and training technology reports to the intelligent mobile terminal of the target user in real time.

[0211] For the specific limitations of the hitting effect evaluation device, reference can be made to the limitations of the hitting effect evaluation method in the above text, which will not be elaborated here. Each module in the above hitting effect evaluation device can be implemented in whole or in part by software, hardware, and their combinations. The above modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to the above modules.

[0212] The hitting effect evaluation device provided in this embodiment obtains the user's hitting data in the target space through the data acquisition module 201. The user's hitting data includes one or more combinations of the following: the hitting landing position, the hitting ball speed, and the hitting motion trajectory; the effect evaluation module 202 evaluates the hitting effect based on the user's hitting data to obtain the hitting effect evaluation result. This embodiment automatically and real-time obtains the user's hitting data in the target space and comprehensively considers the hitting landing position. By comprehensively considering the hitting landing position, the hitting ball speed, and the hitting motion trajectory in the user's hitting data, it can perform real-time and all-round hitting evaluations on multiple users in the target space, avoiding the situation that the manual evaluation method may lead to inaccurate evaluation results and omission of details, effectively improving the accuracy and comprehensiveness of the hitting effect evaluation, as well as improving the efficiency and real-time performance of simultaneously evaluating multiple users, so as to provide more targeted training suggestions for athletes in the future and improve the user training efficiency; in addition, this embodiment can implement the hitting effect evaluation by using simple devices, without using high-cost complex hardware devices, reducing the dependence on professional technical personnel and lowering the labor cost and equipment cost.

[0213] In addition, an embodiment of the present application further provides an electronic device, as Figure 8 shown, which shows the structural schematic diagram of the electronic device involved in the embodiment of the present application. Specifically:

[0214] The electronic device may include a processor 301 with one or more processing cores, a memory 302 with one or more computer-readable storage media, a power supply 303, an input unit 304, and other components. Those skilled in the art can understand, Figure 8The structure of the electronic device shown does not limit the electronic device, and it may include more or fewer components than shown, or combine certain components, or have different component arrangements. Among them:

[0215] The processor 301 is the control center of the electronic device, connecting various parts of the entire electronic device through various interfaces and circuits. By running or executing software programs and / or modules stored in the memory 302, and by invoking the data stored in the memory 302, it executes various functions of the electronic device and processes data, thereby monitoring the electronic device as a whole. Optionally, the processor 301 may include one or more processing cores; preferably, the processor 301 may integrate an application processor and a modem processor. Among them, the application processor mainly processes the operating system, user interface, application programs, etc., and the modem processor mainly processes wireless communication. It can be understood that the above-mentioned modem processor may not be integrated into the processor 301.

[0216] The memory 302 can be used to store software programs and modules. The processor 301 executes various functional applications and the hitting effect evaluation method by running the software programs and modules stored in the memory 302. The memory 302 mainly includes a program storage area and a data storage area. Among them, the program storage area can store the operating system, application programs required for at least one function (such as the sound playback function, image playback function, etc.); the data storage area can store the data created according to the use of the electronic device. In addition, the memory 302 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage devices. Correspondingly, the memory 302 may also include a memory controller to provide the processor 301 with access to the memory 302.

[0217] The electronic device further includes a power supply 303 for supplying power to each component. Preferably, the power supply 303 can be logically connected to the processor 301 through a power management system, so as to realize functions such as management of charging, discharging, and power consumption management through the power management system. The power supply 303 may also include any components such as one or more DC or AC power supplies, a recharge system, a power failure detection circuit, a power converter or inverter, and a power status indicator.

[0218] The electronic device may further include an input unit 304, which can be used to receive input digital or character information, and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function controls.

[0219] Although not shown, the electronic device may further include a display unit and the like, which will not be elaborated here. Specifically, in this embodiment, the processor 301 in the electronic device will load the executable files corresponding to the processes of one or more application programs into the memory 302 according to the following instructions, and the processor 301 will run the application programs stored in the memory 302 to implement various functions as follows:

[0220] Obtain user hitting data in the target space, where the user hitting data includes one or more combinations of the following: hitting landing position, hitting ball speed, and hitting motion trajectory; perform a hitting effect evaluation based on the user hitting data to obtain a hitting effect evaluation result.

[0221] For the specific implementation of each of the above operations, reference may be made to the previous embodiments, which will not be elaborated here.

[0222] In the embodiment of the present application, the user hitting data in the target space is automatically and real-time obtained, and the hitting landing position is comprehensively considered. By comprehensively considering the hitting landing position, hitting ball speed, and hitting motion trajectory in the user hitting data, it is possible to perform real-time and all-round hitting evaluations on multiple users in the target space, avoiding the situation where the manual evaluation method may lead to inaccurate evaluation results and omission of details, effectively improving the accuracy and comprehensiveness of the hitting effect evaluation, as well as improving the efficiency and real-time performance of simultaneously evaluating multiple users, so as to provide more targeted training suggestions for athletes subsequently and improve the user training efficiency; in addition, the embodiment of the present application can achieve the hitting effect evaluation by using simple devices, without the need to use high-cost and complex hardware devices, reducing the dependence on professional technical personnel and lowering the labor cost and equipment cost.

[0223] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructions, or by controlling relevant hardware through instructions. The instructions can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0224] Therefore, the embodiment of the present application provides a storage medium, which stores multiple instructions that can be loaded by a processor to execute the steps in any one of the hitting effect evaluations provided by the embodiment of the present application. For example, the instructions can execute the following steps:

[0225] Obtain user hitting data in the target space, where the user hitting data includes one or more combinations of the following: hitting landing position, hitting ball speed, and hitting motion trajectory; perform a hitting effect evaluation based on the user hitting data to obtain a hitting effect evaluation result.

[0226] For the specific implementation of each of the above operations, reference may be made to the previous embodiments, which will not be elaborated here.

[0227] Among them, the storage medium may include: read-only memory (ROM, Read Only Memory), random access memory (RAM, Random Access Memory), magnetic disk, optical disc, etc.

[0228] Since the instructions stored in the storage medium can execute the steps in any one of the batting effect evaluation methods provided in the embodiments of the present application, the beneficial effects achievable by any one of the batting effect evaluation methods provided in the embodiments of the present application can be achieved. For details, see the previous embodiments and will not be elaborated here.

[0229] The above has introduced in detail a batting effect evaluation method, device, system, electronic device, and storage medium provided by the embodiments of the present application. Specific examples are used in this article to elaborate on the principle and implementation manner of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application; at the same time, for those skilled in the art, according to the idea of the present application, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present application.

Claims

1. A method for evaluating a hitting effect, characterized in that: The steps include: Acquire the user's hitting data in the target space, wherein the user's hitting data includes one or more combinations of the following: hitting point position, hitting ball speed and hitting action trajectory; A batting effect evaluation is performed based on the user's batting data to obtain a batting effect evaluation result.

2. The method for evaluating the hitting effect according to claim 1, characterized in that: The step of obtaining the user's hitting data in the target space includes: Obtain the hitting point position of the target ball in the target space during the movement; Obtain the hitting ball speed of the target ball in the target space; Get the batting motion trajectory of the target user in the target space.

3. The method for evaluating the hitting effect according to claim 2, characterized in that: The step of obtaining the hitting point position of the target ball in the target space during the movement process includes: Collecting the motion trajectory of the target sphere by using sensors pre-deployed in the target space; The hitting point position of the target ball is identified based on the motion trajectory.

4. The method for evaluating the hitting effect according to claim 2, characterized in that: The step of obtaining the hitting ball speed of the target ball in the target space includes: Collecting motion video of the target sphere during its motion by means of a camera device pre-deployed in the target space; Identify the starting frame number and the starting coordinates of the sphere corresponding to the starting frame in the motion video, and the falling frame number and the falling coordinates of the target sphere falling into the target area in the motion video; Calculating the displacement distance of the target sphere based on the sphere starting coordinates and the landing point coordinates, and calculating the time difference based on the starting frame number and the landing point frame number; Based on the displacement distance of the target ball and the time difference, the hitting ball speed corresponding to the target ball is calculated.

5. The method for evaluating the hitting effect according to claim 2, characterized in that: The step of obtaining the hitting action trajectory of the target user in the target space includes: Capturing a batting action video corresponding to the target user by using a camera device pre-deployed in the target space; Analyze the batting action video frame by frame to obtain corresponding human key element data and equipment key element data; Normalizing the human body key element data and the equipment key element data; Based on the normalized human body key element data and equipment key element data, a ball hitting action trajectory corresponding to the target user is generated.

6. The method for evaluating the hitting effect according to claim 5, characterized in that: The human body key element data includes one or more combinations of the following: human body key point data, line data, and area data; the equipment key element data includes one or more combinations of the following: equipment key point data, line data, and area data.

7. The method for evaluating the hitting effect according to claim 6, characterized in that: The human body key element data at least includes the human body key element data corresponding to the target user holding the sports equipment.

8. The method for evaluating a motor action according to claim 6, wherein: The device key point data includes one or more combinations of the following: the highest endpoint data of the motion device, the lowest endpoint data of the motion device, the leftmost endpoint data of the motion device, the rightmost endpoint data of the motion device and / or geometric center of gravity data.

9. The method for evaluating the hitting effect according to any one of claims 1 to 8, characterized in that: The step of performing a batting effect evaluation based on the user's batting data to obtain a batting effect evaluation result includes: Calculating the difference between the hitting ball landing point position of the target sphere and the center coordinates of the target area to obtain a landing point deviation value; Comparing and analyzing the target user's batting motion trajectory with the standard motion trajectory, obtaining a motion normative analysis result; The hitting effect evaluation is performed on the landing point deviation value, the hitting ball speed and the action normative analysis result to obtain the hitting effect evaluation result corresponding to the target user.

10. The method for evaluating the hitting effect according to claim 1, characterized in that: After performing the batting effect evaluation based on the user's batting data to obtain the batting effect evaluation result, the method further includes: Based on the batting effect evaluation result, generating corresponding personalized training suggestions; Obtaining a historical evaluation result of a target user's hitting effect, and generating a corresponding training technique report based on the historical evaluation result of the hitting effect; At least one of the hitting effect evaluation result, the personalized training suggestion and the training technology report is fed back to the smart mobile terminal of the target user in real time.

11. A ball hitting effect evaluation device, characterized in that: include: A data acquisition module, used to acquire the user's hitting data in the target space, wherein the user's hitting data includes the hitting point position, the hitting ball speed and the hitting action trajectory; The effect evaluation module is used to evaluate the batting effect based on the user's batting data to obtain a batting effect evaluation result.

12. A system for evaluating the effect of hitting a ball, characterized in that: Including data acquisition equipment, tennis service equipment and display equipment; The data acquisition device is used to obtain the user's hitting data in the target space and send it to the tennis service device; The tennis service device is used to evaluate the hitting effect based on the received hitting data of the user to obtain a hitting effect evaluation result; The display device is used to provide real-time feedback on the batting effect evaluation result.

13. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the steps of the ball hitting effect evaluation method as described in any one of claims 1-10.

14. A storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the ball hitting effect evaluation method as described in any one of claims 1-10.

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