Football training method and system based on VR technology

Abstract

The present application belongs to the technical field of file data management and the field of virtual reality, and particularly relates to a football training method and system based on VR technology, which comprises a football training experiment framework design method based on VR technology, a football training experiment architecture designed based on VR technology, a human motion posture recognition method for accurately estimating the motion posture of athletes and providing a basis for VR three-dimensional virtual modeling, and a football movement trajectory analysis and simulation method for trajectory analysis and mathematical modeling of the football movement trajectory, virtual presentation in a VR scene, and improvement of the reliability and accuracy of the football training method based on VR technology; and further provides a football training system based on VR technology for providing necessary hardware support for the football training method based on VR technology. The present application effectively combines VR technology and football training, provides an efficient, reliable and real VR football training scheme, improves the efficiency of football training, and reduces the labor cost.

Description

Technical Field

[0001] This invention belongs to the field of virtual reality technology, and in particular relates to a football training method and system based on VR technology. Background Technology

[0002] VR technology can greatly improve training effectiveness and efficiency by simulating various complex and realistic training environments. The importance of this research lies in two aspects: First, VR technology allows football training to be unrestricted by field and weather conditions. VR devices can simulate various scenarios in indoor environments, such as heavy rain, strong winds, and nighttime, helping players train without time and space constraints. Second, VR technology can accurately understand athletes' technical movements. Through human motion analysis, it can help athletes establish a connection between virtual and reality, allowing the movements performed by athletes in reality to be fully transmitted to the football in the virtual environment, thereby obtaining an accurate football trajectory. This feedback to the athlete's perspective allows them to understand the movement of the football under this technical movement, thus achieving linkage between virtual and virtual reality.

[0003] Compared to traditional teaching methods, VR technology can generate personalized training plans based on players' specific performance and characteristics. By analyzing data on players' performance in different environments and situations, coaches can tailor training plans for each player, focusing on improving their abilities under specific conditions, such as ball control in windy weather or decision-making under high pressure. Personalized training plans help players develop in a balanced way in all aspects, especially by strengthening weaknesses, thereby improving their overall competitive level.

[0004] The research on the application of VR technology in football training not only provides a scientific basis for improving training effectiveness and developing personalized training programs, but also lays the foundation for promoting the widespread application of technology in the sports field. The significance of this research is not limited to football itself, but also has important demonstration effects and promotional value for the innovation of training methods in the entire sports industry. This research is expected to promote the development of traditional sports training models towards digitalization and intelligence, and further improve athletes' competitive level and performance.

[0005] Currently, virtual reality technology is widely used abroad in military education, sports training, and medicine, providing educators with a relatively ideal and effective teaching method. As the birthplace of virtual reality technology and a leader in the virtual reality industry, the United States has taken the lead in applying it to the military field and has now established virtual reality systems in various fields, including a virtual reality education system available nationwide.

[0006] As the birthplace of virtual reality (VR) technology and the most authoritative country in the field, the United States is considered by many research institutions and media outlets to directly represent the world's VR technology development level. VR research in the US can be traced back to the 1940s. Initial research and applications focused primarily on simulation training for pilots and astronauts by the US military. In the 1980s, NASA and the US Department of Defense organized a series of research projects on VR technology, achieving remarkable results. NASA's Ames Laboratory was dedicated to an experimental program called "Virtual Planetary Exploration" (VPE). NASA has now established VR training systems for aviation and satellite maintenance, VR training systems for space stations, and a nationwide VR education system. The Computer Science Department at the University of North Carolina is one of the earliest and most renowned universities to conduct VR research. Their research focuses on molecular modeling, flight piloting, surgical simulation, and architectural simulation. Major League Baseball (MLB) has incorporated VR training into its team's daily practice to improve batters' hitting abilities, representing a successful integration of VR technology with sports training. Andre Drummond, an NBA star with the Detroit Pistons, has improved his soccer skills with the help of virtual reality technology.

[0007] In Europe, the UK is leading in some aspects of the development of virtual reality technology, particularly in distributed parallel processing, auxiliary equipment (including haptic feedback) design and application research. The UK's Bristol company found that the intersection of virtual reality technology applications should focus on overall integrated technology, and they are leading in some areas of software and hardware. The UK's ARRL company's research experiments on remote presentation mainly include the UK's reconstruction of virtual reality technology. Their products also include architectural and scientific visualization computing. Other developed European countries such as the Netherlands, Germany, and Sweden have also actively carried out research and application of virtual reality technology. Sweden's DIVE distributed virtual interactive environment is a heterogeneous distributed system based on Unix, in which multiple processes on different nodes can work in the same world. The training and simulation system developed by the Physics and Electronics Laboratory (TNO-PEL) of the TNO Institute in The Hague, Netherlands, improves the existing simulation system by improving the human-computer interface so that users can fully intervene in the simulation environment. Germany has achieved unexpected results in the application of virtual reality technology in the UK

[11] . In terms of transforming traditional industries, virtual factories are used for three main purposes: first, product design to reduce costs and avoid the risks of developing new products; second, product demonstrations to attract customers and secure orders; and third, training to improve workers' operational skills before new production equipment is put into use. In 2016, Eurosport launched a new virtual reality (VR) app, Eurosport VR, providing sports fans with an opportunity to experience sporting events "personally."

[0008] Compared with some developed countries, my country's research on virtual reality (VR) technology still lags far behind. However, with the rapid development of computer graphics, computer systems engineering, and other technologies, VR technology has gained considerable attention and aroused interest and concern from all sectors of Chinese society, leading to research and application of VR and the establishment of virtual environments. Beijing University of Aeronautics and Astronautics (BUAA) was among the first universities in China to conduct VR research. After years of effort, it has achieved significant results in areas such as virtual environment database construction, human-computer immersive interaction, and simulation and reproduction of virtual object characteristics. Its self-designed and developed VR system for pilot training has also received widespread acclaim domestically. The successful clinical trial of Tianjin University's "Miaoshou" minimally invasive surgical robot broke the monopoly of the German da Vinci minimally invasive surgical robot, marking a significant milestone in the development of VR in my country.

[0009] In his article "Using Virtual Reality Information Technology to Improve the Quality of Football Training," Li Chen points out that with the rapid development of modern technology, virtual reality (VR) technology has shown strong growth momentum and has been widely applied in various fields such as entertainment, medicine, education, and architecture, bringing people entirely new experiences. In the field of football training, utilizing virtual reality information technology can simulate real-world scenarios for players, providing an immersive experience. Through data analysis and feedback, it can help players improve their techniques and tactics, thus enhancing the quality of football training. Applying virtual reality information technology to football training can not only improve training efficiency and players' technical skills but also help to tap into and stimulate players' potential, thereby promoting a comprehensive improvement in the quality and efficiency of football training. In practice, to promote the comprehensive application of virtual reality information technology in football training and further improve training quality, the following strategies can be used: first, using VR technology to acquire three-dimensional information about football training; second, using VR technology to build surreal virtual training scenarios; third, using VR technology to conduct virtual-real comparisons of football technical movements; and fourth, using VR technology to achieve remote interactive training for football.

[0010] In conclusion, virtual reality technology has flourished as an emerging technology and has been widely used in many fields such as education and healthcare. However, due to the special nature of sports, related applications have emerged later than in other industries, and research on it is not in-depth. This necessitates further exploration of the application of this technology in sports training. Summary of the Invention

[0011] To address the aforementioned issues, this invention proposes a football training method and system based on VR technology. This method solves the problems existing in the prior art by reviewing and summarizing research on the application of virtual reality technology in sports training, combining virtual reality technology with football training, and verifying the effectiveness of this auxiliary training method in football shooting training for university sports majors through applied practical research.

[0012] To achieve the above objectives, the present invention provides the following technical solution: a football training method based on VR technology, including a football training experimental framework design method based on VR technology, a human motion posture recognition method, a football motion trajectory analysis and simulation method, and a motion analysis and feedback method.

[0013] Furthermore, the aforementioned VR-based football training method, specifically the VR-based football training experimental framework design method, is based on VR-based football training methods. By designing a reasonable training framework, VR technology is deeply integrated with daily football training, and key VR-based integration technologies are broken through within this framework. The specific steps include: S10: Select a suitable football field as the experimental field to carry out the experiment; S11: Training is conducted for different batches of students in two separate time periods, with identical training content and arrangements. S12: Each test will set up a control group and an experimental group. The control group will use traditional football training methods, while the experimental group will use virtual reality technology to assist in training. S13: Virtual Reality Material Recording. Pre-recorded videos are processed through digital image processing, Fourier transform, and Laplace transform to create materials that can be played in VR devices. In virtual space, the environment of the virtual football field is controlled by the controlled environment as the basis of computation, and this is used as the data source and reference for VR training. In a preferred embodiment, step S10 above involves conducting the experiment at the football field of Nanchang Applied Technology Normal University.

[0014] In another preferred embodiment, in step S11 above, the same coach is selected to teach the class members. This coach has rich experience in football training and needs to record the video footage required by the virtual reality technology equipment in advance and debug the equipment to ensure normal use during training.

[0015] In another preferred embodiment, the coach in step S11 above prepares a lesson plan based on the training outline as the main basis for teaching, highlighting the special characteristics of football training while taking into account the physical characteristics of university sports majors.

[0016] In another preferred embodiment, in step S11 above, the coach uses Coach's Eye software to assist in the analysis of athletes' sports data, behavior, and posture. In another preferred embodiment, in step S11 above, both the experimental group and the control group consist of students with no prior football experience. Before the experiment begins, the students undergo physical fitness tests. Students of similar age and physical fitness are selected as experimental subjects. The male-to-female ratio of the students should be adjusted appropriately to ensure a more even distribution.

[0017] In another preferred embodiment, in step S12 above, the experimental group members wear any one of the following: Pimax4K-VR glasses, Sony VRPS4 PSVR glasses, or Xiaomi VR glasses to complete the football training course.

[0018] Furthermore, in the aforementioned VR-based football training method, the human motion posture recognition method is a crucial source for VR virtual scene construction and updates, directly determining the user's real feeling and user experience during training. It is also an important condition for coaches to judge the trainees' training progress. Specific steps include: S20: Two optical systems (cameras) are used to capture the motion of the shot, recording the coordinates of the same marker point on their respective image planes. and ; S21: Using the known camera position and orientation, as well as the camera's intrinsic parameter matrix K, the two-dimensional coordinates captured by the camera are converted into three-dimensional coordinates using triangulation. The specific formula is as follows: ; ; in, and These are the projection matrices of the two cameras. R and t These are the camera's rotation matrix and translation vector, respectively. S22: Find the 3D point X by minimizing the reprojection error. The calculation expression is: ; S23: Set a 3D point on each limb of the human body, and obtain the shooting action based on the positional relationship of the 3D points on different parts of the body; S24: Analyze the motion angle during the shot and calculate the two vectors. a and b The angle between them is calculated using the following formula: , in, a This represents the position vector of a part of the body. b This represents the position vector of another part of the body. It is the magnitude of the vector, and the angle. It reflects the relative position between two joints or body segments; S25: Analyze the angle between the toe and knee during the shot, vector... a Representing the lower leg, from the ankle to the knee, vector b Representing the foot, from the toes to the ankle, by capturing these two vectors, the angle of the shot can be calculated using the formula in step S24 above; S26: Analyze velocity and acceleration. Velocity is the rate of change of position over time. If the discrete change of position over time is... Then speed The discrete differential formula is: , in, It is in time t The velocity vector, It is time t The position vector, At the position in the previous moment, It is a time interval; Acceleration is the rate of change of velocity over time. If the discrete change of velocity over time is... Then acceleration Discrete differential formula: , in, It is in time t acceleration vector, It is time t The velocity vector, The velocity vector at the previous moment, It refers to the time interval. By analyzing velocity, acceleration, and angle, the athlete's trajectory and posture can be described in detail and with precision.

[0019] Furthermore, the aforementioned VR-based football training method, wherein the football trajectory analysis and simulation method estimates the trajectory of the football in the virtual environment based on the recognized actions, constructs an accurate football trajectory curve and functional relationship, thereby promoting the realism of VR virtual scene construction and the accuracy and effectiveness of the football training process, specifically includes the following steps: S30: Get the position of the toes when kicking the ball. This includes obtaining information at the moment of action. t Capture the 3D coordinates of the toes ; S31: Calculate the speed and instantaneous acceleration of the football according to the calculation formula in step S26; S32: Calculate the angular velocity of the soccer ball at the instant it leaves the ground. The formula is: , in, It is the toes (and ankles) in time Rotation angle within; S33: Derive the initial conditions for the football (shoot or pass) under this action, including the following steps: S330: Estimates initial velocity by capturing the speed of the toe at the moment of shooting. ; S331: Calculate the angle by the relative angle between the toes and the ankle. ; S332: The initial position of the football at the moment of launch. ; S34: The direction of motion of the football is derived through kinematic analysis. The specific calculation formulas include: Horizontal movement: ; Vertical movement: ; S35: Analyze the influence of toe movement on the trajectory of the football. Toe movement affects the trajectory of the football by controlling its rotation and the applied force. Considering the initial velocity, angle, and toe force, the trajectory of the football obtained by the force applied by the toe can be described as follows: , Wherein, the initial rotation angle is The torque applied by the action is calculated using angular velocity. ; I It is the moment of inertia of the football. It is the rate of change of angular velocity; the force applied by the toes. F The final expressions for the initial velocity and direction that affect the toes are: ;in, m It's about the quality of the football. a It is acceleration; S36: Simulate the predicted football trajectory in the virtual segment; Furthermore, the aforementioned VR-based football training method, including its motion analysis and feedback methods, aims to assist designers and coaches in adjusting the VR-based football training method to achieve the best VR training results. Specific steps include: S40: Data collection, filming videos of professional football players kicking the ball in different situations, capturing kicking movements from multiple angles at different heights and with varying athletic abilities; S41: Use high-precision motion capture equipment to acquire the three-dimensional coordinate data of key points; S42: Mark key points. Using image processing technology, the key points of the human body are automatically identified and marked. S43: Extract posture features from the raw capture data, including joint angles, displacement, velocity and acceleration parameters; S44: Organize and classify the data according to different kicking actions, including passing and shooting actions, to create a structured standard library; S45: Convert each standard kicking posture into a feature vector and save it to the database; S46: Motion capture, using the same method to annotate the key points of an individual's kicking action and convert the individual's kicking action into a feature vector; S47: Use the KNN algorithm to determine the category of the individual's posture that is closest to the standard posture, and train an SVM classifier to determine whether the individual's posture is correct; S48: Calculate the Euclidean distance between the individual's posture feature vector and the feature vectors in the standard library, and generate a feedback report; S49: Posture deviation prompt. Based on the calculation results, it indicates the deviation between an individual's kicking action and the standard posture, including angle deviation and position deviation. S50: Improvement suggestions, providing specific improvement suggestions, including adjusting the lifting height and lifting angle.

[0020] In a preferred embodiment, the image processing technology described in step S42 above includes OpenPose or DeepLabCut technology, and the key points of the human body typically include the torso, lower legs, and feet.

[0021] On the other hand, a VR-based football training system is provided for application in any of the VR-based football training methods described above, wherein the VR-based football training system includes: VR Data Acquisition Subsystem: The VR data acquisition subsystem is located at the front end of the system and mainly consists of high-definition camera equipment. The high-definition camera equipment uses high-resolution cameras to record and capture the movement posture of football players and the trajectory of football movement for VR modeling. VR Data Processing Terminal: The VR data processing terminal is located on a high-performance computer device. With the help of video and image data processing software, it performs digital image processing, Fourier transform, and Laplace transform on the collected images and video data to create materials that can be played in VR devices. In the virtual space, it uses the controlled environment as the basis for calculation to control the environmental changes of the virtual football field in a realistic way, and uses this as the data source and reference for VR training. VR personal terminal devices: VR terminal devices include VR glasses, motion tracking systems, and interactive devices. VR glasses provide users with a virtual and perceptible football training scene. The motion tracking system captures the user's movements and position in the real world, including tracking the user's head, hand, and even whole-body movements, and feeding them back to the virtual world in real time. Interactive devices simulate real hand movements and tactile feedback, further enhancing the user's immersion in the virtual world.

[0022] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention provides a design method for a football training experiment framework based on VR technology, and presents a realistic and feasible method for constructing a football training experiment framework based on VR technology, which effectively promotes the application of VR technology in football training.

[0023] 2. This invention proposes a human motion posture recognition method, which accurately identifies and judges human motion posture by using a variety of intelligent computing algorithms and classification methods, effectively improving the accuracy and reliability of VR virtual modeling and simulation.

[0024] 3. This invention provides a method for analyzing and simulating the trajectory of a football, which can accurately track and simulate the trajectory of a football in the air, thereby improving the realism of VR modeling.

[0025] 4. This invention effectively promotes the improvement of VR-based football training methods through motion analysis and feedback, while providing effective guidance and suggestions for football trainers to judge the training status of athletes. Attached Figure Description

[0026] Figure 1 This is a flowchart of a football training method based on VR technology according to the present invention; Figure 2 This is a diagram of a football training structure based on VR technology according to the present invention; Detailed Implementation

[0027] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0028] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0029] In the description of this application, the term "for example" is used to mean "used as an example, illustration, or description." Any embodiment described as "for example" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use the invention. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that the invention can be made without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid obscuring the description of the invention with unnecessary detail. Therefore, the invention is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed in this application.

[0030] In this embodiment of the invention, a football training method based on VR technology is described in detail in the appendix. Figure 1It is applied to a football training system based on VR technology, including a design method for a football training experimental framework based on VR technology, a method for human motion posture recognition, a method for football trajectory analysis and simulation, and a method for motion analysis and feedback.

[0031] The VR-based football training experimental framework design method is based on VR technology. By designing a reasonable training framework, VR technology is deeply integrated with daily football training, and breakthroughs are made in the corresponding key VR-based integration technologies under this framework.

[0032] Human motion posture recognition is an important source of information for the construction and updating of VR virtual scenes. It directly determines the user's real feeling and user experience during training, and is also an important condition for coaches to judge the training progress of trainees.

[0033] The football trajectory analysis and simulation method estimates the trajectory of a football in a virtual environment based on the identified actions, and constructs accurate football trajectory curves and functional relationships to improve the realism of VR virtual scene construction and the accuracy and effectiveness of football training processes.

[0034] Motion analysis and feedback methods are designed to help designers and coaches adjust VR-based football training methods to achieve the best VR training results.

[0035] See attached document Figure 2 The present invention also provides a football training system based on VR technology, including a VR data acquisition subsystem, a VR data processing terminal, and a VR personal terminal device.

[0036] The VR data acquisition subsystem is located at the front end of the system and mainly consists of high-definition camera equipment. The high-definition camera equipment uses high-resolution cameras to record and capture the movement postures of football players and the trajectory of the football for VR modeling.

[0037] VR Data Processing Terminal: The VR data processing terminal is located on a high-performance computer device. It uses video and image data processing software to perform digital image processing, Fourier transform, and Laplace transform on the collected images and video data to create materials that can be played in VR devices. In the virtual space, the controlled environment is used as the basis for computation to control the environmental changes of the virtual football field, and this is used as the data source and reference for VR training.

[0038] VR personal terminal devices: VR terminal devices include VR glasses, motion tracking systems, and interactive devices. VR glasses provide users with a virtual and perceptible football training scene. The motion tracking system captures the user's movements and position in the real world, including tracking the user's head, hand, and even whole-body movements, and feeding them back to the virtual world in real time. Interactive devices simulate real hand movements and tactile feedback, further enhancing the user's immersion in the virtual world.

[0039] In a specific embodiment, football coaches and product designers determined a VR-based football training experimental framework using a VR-based football training experimental framework design method. The football field of Nanchang Applied Technology Normal University was selected as the experimental site. From 40 students interested in minoring in football, 30 were selected and divided into two groups for the experiment. One group served as the control group, receiving no additional intervention and undergoing training according to traditional football training methods. The other group served as the experimental group, training using VR technology, wearing one of the following: Pimax4k-VR glasses, Sony VR PS4 / PSVR glasses, or Xiaomi VR glasses. Both the experimental and control groups trained under the guidance of the same coach. The coach used Coach's Eye software in daily training to assist in analyzing athletes' sports data, behaviors, and postures. During product design and updates, product designers continuously collected various movement postures and actions of football players in daily training using human motion posture recognition methods, supported by an optical system. They then created 3D virtual models of the collected postures and actions to enhance the realism of the athletes' football training using VR technology. Product designers used football trajectory analysis and simulation methods to analyze, mathematically model, and simulate the trajectory of a football on the field, enhancing the realism and reliability of the VR-based football training system. Coaches, through the design of motion analysis and feedback methods, can promptly assess and correct the training performance of football players, improving training efficiency.

[0040] Example 1

[0041] In one embodiment, the football coach and VR product designer selected the football field of Nanchang Applied Technology Normal University as the experimental site for the product and training methods. Thirty students were randomly selected from the 2021 cohort of physical education majors at Nanchang Applied Technology Normal University who intended to minor in football. They were divided into two groups: one group served as the control group, receiving training according to standard football training methods; the other group served as the experimental group, receiving VR training using one of the following: Pimax4K-VR glasses, Sony VR PS4 / PSVR glasses, or Xiaomi VR glasses. Before selection, the registered students underwent tests on reaction time, movement speed, and explosive power. Both groups received football training under the guidance of the same coach. The coach possessed extensive football training experience and needed to pre-record the video footage required for the virtual reality equipment, and debug the equipment to ensure proper use during training. During video recording, the product designer also needed to process the pre-recorded video using digital image processing, Fourier transform, and Laplace transform to create material playable on the VR device. In the virtual space, the environmental changes of the virtual football field were controlled using a real-world approach, based on a controlled environment, and this served as the data source and reference for VR training. Each group receives 4 hours of basketball and soccer training per week, totaling 32 hours per group. Training includes soccer kicking technique practice, shooting from fixed positions, crossing from corners, and passing drills with predetermined landing points; and specific physical fitness exercises such as shuttle runs, finger push-ups, lower limb weight training, high knees, and sprints. After a period of soccer training, coaches use Coach's Eye software to analyze athletes' sports data, behaviors, and postures. Post-training tests are conducted, including physical fitness and fixed-point shooting assessments. Trainees' scores are recorded, compiled, and analyzed using SPSS 20.0 and Excel to obtain the results.

[0042] Example 2

[0043] In one embodiment, the product designer uses a human motion posture recognition method to construct and update a VR virtual scene. First, two optical systems (cameras) are used to capture the shooting action, recording the coordinates of the same marker point on their respective image planes. and Then, using the known camera position and orientation, as well as the camera's intrinsic parameter matrix K, triangulation is used to convert the two-dimensional coordinates captured by the camera into three-dimensional coordinates, based on the formula: ; ; in, and These are the projection matrices of the two cameras. R and t These are the camera's rotation matrix and translation vector, respectively; then, the reprojection calculation formula is minimized. Find the 3D point X; then analyze the motion angle during the shot and calculate the two vectors. a and b The angle between them is calculated using the following formula: , in, a This represents the position vector of a part of the body. b This represents the position vector of another part of the body. It is the magnitude of the vector, and the angle. It reflects the relative position between two joints or body segments; Subsequently, the angle between the toe and knee during the shot was analyzed, and the vector was... a Representing the lower leg, from the ankle to the knee, vector b Representing the foot, from the toes to the ankle, by capturing these two vectors, the angle of the shot can be calculated using the formula in step S24 above; Furthermore, analyzing velocity and acceleration, velocity is the rate of change of position over time. If the discrete change of position over time is... Then speed The discrete differential formula is: , in, It is in time t The velocity vector, It is time t The position vector, At the position in the previous moment, It is a time interval; Finally, analyzing the acceleration data, acceleration is the rate of change of velocity over time. If the discrete change of velocity over time is... Then acceleration Discrete differential formula: , in, It is in time t acceleration vector, It is time t The velocity vector, The velocity vector at the previous moment, It refers to the time interval. By analyzing velocity, acceleration, and angle, the athlete's trajectory and posture can be described in detail and with precision.

[0044] Example 3

[0045] In one embodiment, product designers use football trajectory analysis and simulation methods to estimate the trajectory of a football in a virtual environment based on identified actions, constructing accurate football trajectory curves and functional relationships to enhance the realism of VR virtual scene construction and the accuracy and effectiveness of football training processes. Specific steps include: First, determine the position of your toes when kicking the ball. This includes obtaining information at the moment of action. t Capture the 3D coordinates of the toes Calculate the velocity and instantaneous acceleration of the football using the formula; calculate the angular velocity of the football at the instant it leaves the ground using the following formula: , in, It is the toes (and ankles) in time Rotation angle within; Then, the initial conditions for the football (shoot or pass) are derived under this action, and the specific steps include: The initial velocity is estimated by capturing the speed of the toe at the moment of shooting. The angle is calculated by examining the relative angle between the toes and the ankle. The initial position of the football at the moment of launch. The direction of motion of the football is derived through kinematic analysis, and the specific calculation formulas include: Horizontal movement: , Vertical movement: ; Next, we analyze the influence of toe movement on the trajectory of the football. Toe movement affects the trajectory of the football by controlling its rotation and the applied force. Taking into account the initial velocity, angle, and toe force, the trajectory of the football obtained by the force applied by the toe can be described as follows: , Wherein, the initial rotation angle is The torque applied by the action is calculated using angular velocity. ; I It is the moment of inertia of the football. It is the rate of change of angular velocity; the force applied by the toes. F The final expressions for the initial velocity and direction that affect the toes are: ;in, m It's about the quality of the football. a It's acceleration; the simulation is performed in a virtual segment based on the predicted soccer ball trajectory. Example 4 In one embodiment, product designers and coaches adjust VR-based football training methods using motion analysis and feedback techniques to achieve optimal VR training results. Specific steps include: Data collection involves filming videos of professional soccer players kicking the ball in different situations, capturing kicking movements from multiple angles at different heights and with varying athletic abilities; using high-precision motion capture equipment to obtain 3D coordinate data of key points; and labeling key points using image processing technologies, including OpenPose or DeepLabCut, to automatically identify and label key points of the human body, including the torso, lower legs, and feet. Extract posture features: Extract posture features from the raw captured data, including joint angles, displacement, velocity, and acceleration parameters; organize and classify: Classify the data according to different kicking actions, including passing and shooting actions, to create a structured standard library; convert each standard kicking posture into a feature vector and save it to the database; motion capture: Use the same method to annotate the key points of individual kicking actions and convert individual kicking actions into feature vectors; The KNN algorithm is used to determine the individual's posture and the closest standard posture category, and an SVM classifier is trained to determine whether the individual's posture is correct. The Euclidean distance between the individual's posture feature vector and the feature vectors in the standard library is calculated, and a feedback report is generated. Posture deviation prompts are provided, pointing out the deviations between the individual's kicking action and the standard posture based on the calculation results, including angle deviation and position deviation. Improvement suggestions are provided, including adjusting the kicking height and kicking angle.

[0046] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0047] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A football training method based on VR technology, comprising a VR-based football training experimental framework design method, a human motion posture recognition method, a football trajectory analysis and simulation method, and a motion analysis and feedback method, characterized in that, The design method for the VR-based football training experimental framework includes the following specific steps: S10: Select a suitable football field as the experimental field to carry out the experiment; S11: Training is conducted for different batches of students in two separate time periods, with identical training content and arrangements. S12: Each test will set up a control group and an experimental group. The control group will use traditional football training methods, while the experimental group will use virtual reality technology to assist in training. S13: Virtual Reality Material Recording. Pre-recorded videos are processed through digital image processing, Fourier transform, and Laplace transform to create materials that can be played in VR devices. In virtual space, the environment of the virtual football field is controlled by the controlled environment as the basis of computation, and this is used as a data source and reference for VR training.

2. The football training method based on VR technology according to claim 1, characterized in that, The specific steps of the human motion posture recognition method include: S20: Two optical systems (cameras) are used to capture the motion of the shot, recording the coordinates of the same marker point on their respective image planes. and ; S21: Using the known camera position and orientation, as well as the camera's intrinsic parameter matrix K, the two-dimensional coordinates captured by the camera are converted into three-dimensional coordinates using triangulation. The specific formula is as follows: ； ； in, and These are the projection matrices of the two cameras. R and t These are the camera's rotation matrix and translation vector, respectively. S22: Find the 3D point X by minimizing the reprojection error. The calculation expression is: ； S23: Set a 3D point on each limb of the human body, and obtain the shooting action based on the positional relationship of the 3D points on different parts of the body; S24: Analyze the motion angle during the shot and calculate the two vectors. a and b The angle between them is calculated using the following formula: ， in, a This represents the position vector of a part of the body. b This represents the position vector of another part of the body. It is the magnitude of the vector, and the angle. It reflects the relative position between two joints or body segments; S25: Analyze the angle between the toe and knee during the shot, vector... a Representing the lower leg, from the ankle to the knee, vector b Representing the foot, from the toes to the ankle, by capturing these two vectors, the angle of the shot can be calculated using the formula in step S24 above; S26: Analyze velocity and acceleration. Velocity is the rate of change of position over time. If the discrete change of position over time is... Then speed The discrete differential formula is: ， in, It is in time t The velocity vector, It is time t The position vector, At the position in the previous moment, It is a time interval; Acceleration is the rate of change of velocity over time. If the discrete change of velocity over time is... Then acceleration Discrete differential formula: ， in, It is in time t acceleration vector, It is time t The velocity vector, The velocity vector at the previous moment, It refers to the time interval. By analyzing velocity, acceleration, and angle, the athlete's trajectory and posture can be described in detail and with precision.

3. The football training method based on VR technology according to claim 1, characterized in that, The football trajectory analysis and simulation method estimates the trajectory of the football in the virtual environment based on the identified actions, and constructs accurate football trajectory curves and functional relationships to promote the realism of VR virtual scene construction and the accuracy and effectiveness of football training process.

4. The football training method based on VR technology according to claim 3, characterized in that, The specific steps of the football trajectory analysis and simulation method include: S30: Get the position of the toes when kicking the ball. This includes obtaining information at the moment of action. t Capture the 3D coordinates of the toes ; S31: Calculate the speed and instantaneous acceleration of the football according to the calculation formula in step S26; S32: Calculate the angular velocity of the soccer ball at the instant it leaves the ground. The formula is: ， in, It is the toes (and ankles) in time Rotation angle within; S33: Derive the initial conditions for the football (shoot or pass) under this action, including the following steps: S330: Estimates initial velocity by capturing the speed of the toe at the moment of shooting. ; S331: Calculate the angle by the relative angle between the toes and the ankle. ; S332: The initial position of the football at the moment of launch. ; S34: The direction of motion of the football is derived through kinematic analysis. The specific calculation formulas include: Horizontal movement: ; Vertical movement: ; S35: Analyze the influence of toe movement on the trajectory of the football. Toe movement affects the trajectory of the football by controlling its rotation and the force applied. Considering the initial velocity, angle, and toe force, the trajectory of the football obtained by the force applied by the toe can be described as follows: ， Wherein, the initial rotation angle is The torque applied by the action is calculated using angular velocity. ; I It is the moment of inertia of the football. It is the rate of change of angular velocity; the force applied by the toes. F The final expressions for the initial velocity and direction that affect the toes are: ;in, m It's about the quality of the football. a It is acceleration; S36: Simulate the predicted soccer ball trajectory in a virtual segment.

5. A football training method based on VR technology according to claim 1, characterized in that, The motion analysis and feedback method aims to assist designers and coaches in adjusting VR-based football training methods to achieve optimal VR training results. Specific steps include: S40: Data collection, filming videos of professional football players kicking the ball in different situations, capturing kicking movements from multiple angles at different heights and with varying athletic abilities; S41: Use high-precision motion capture equipment to acquire the three-dimensional coordinate data of key points; S42: Mark key points. Using image processing technology, the key points of the human body are automatically identified and marked. S43: Extract posture features from the raw capture data, including joint angles, displacement, velocity and acceleration parameters; S44: Organize and classify the data according to different kicking actions, including passing and shooting actions, to create a structured standard library; S45: Convert each standard kicking posture into a feature vector and save it to the database; S46: Motion capture, using the same method to annotate the key points of an individual's kicking action and convert the individual's kicking action into a feature vector; S47: Use the KNN algorithm to determine the category of the individual's posture that is closest to the standard posture, and train an SVM classifier to determine whether the individual's posture is correct; S48: Calculate the Euclidean distance between the individual's posture feature vector and the feature vectors in the standard library, and generate a feedback report; S49: Posture deviation prompt. Based on the calculation results, it indicates the deviation between an individual's kicking action and the standard posture, including angle deviation and position deviation. S50: Improvement suggestions, providing specific improvement suggestions, including adjusting the lifting height and lifting angle.

6. A football training system based on VR technology, characterized in that, A football training system based on VR technology is implemented using any one of claims 1-5, wherein the football training system based on VR technology comprises: The VR data acquisition subsystem, located at the front end of the system, mainly consists of high-definition camera equipment. The high-definition camera equipment uses a high-resolution camera to record and capture the movement posture of football players and the trajectory of the football for VR modeling.

7. The football training system based on VR technology according to claim 6 further includes a VR data processing terminal, characterized in that, The VR data processing terminal is located on a high-performance computer device. It uses video and image data processing software to perform noise reduction, enhancement, editing, and frame splitting operations on the acquired images and video data, making it convenient for coaches and VR designers to analyze and improve the data frame by frame.

8. The football training system based on VR technology according to claim 7 further includes a VR personal terminal device, characterized in that, The VR personal terminal device includes VR glasses, a motion tracking system, and an interactive device. The VR glasses provide users with a virtual and perceptible football training scene. The motion tracking system captures the user's movements and position in the real world, including tracking the user's head, hand, and even whole-body movements, and feeding them back to the virtual world in real time. The interactive device simulates real hand movements and tactile feedback, further enhancing the user's immersion in the virtual world.

Images