Skiing meta-universe e-sports platform based on real physical mechanics feedback

Abstract

This invention relates to the fields of virtual reality, e-sports, and sports simulation technology, and particularly to a skiing metaverse e-sports platform based on real physical and mechanical feedback. The platform comprises: a motion recognition and capture system for collecting and processing images of the skier's human posture and depth information to obtain optimized three-dimensional joint point data; a sports biomechanics calculation system for solving joint angle data based on the optimized three-dimensional joint point data and constructing a multi-body dynamics model based on the joint angle data to simulate skiing trajectories; a virtual e-sports interaction system for constructing virtual scenes, physical interaction logic, and multi-dimensional interactive feedback based on simulated skiing trajectories; and a skiing metaverse ecosystem, serving as the application carrier for the aforementioned three systems and integrating skiing training, entertainment and social interaction, and e-sports competition. This solves the problems of high barriers to entry in traditional skiing, the lack of mechanical interaction analysis in existing simulation products, and the disconnect between the metaverse and e-sports scene experiences.

Description

Technical Field

[0001] This invention relates to the fields of virtual reality, e-sports and sports simulation technology, and in particular to a skiing metaverse e-sports platform based on real physical and mechanical feedback. Background Technology

[0002] Skiing and other winter sports have garnered widespread attention, with public enthusiasm for participation remaining high. However, traditional skiing presents significant barriers to entry: firstly, high-quality ski resorts are often located far from city centers, requiring considerable travel time, making frequent participation difficult for busy urban dwellers; secondly, the economic costs of skiing are high, including entrance fees, the purchase or rental of professional ski equipment and clothing, transportation, and accommodation, making frequent participation inaccessible to the average person; and thirdly, skiing carries inherent risks, with beginners prone to falls and injuries during high-speed skiing, deterring many potential enthusiasts. These factors prevent many skiing enthusiasts from engaging in frequent on-site training, creating an urgent market demand for efficient, safe, and economical ski simulation systems.

[0003] Current ski simulation products on the market have significant shortcomings: they are few in number and vary greatly in quality. Existing sports simulation games generally use keyboards and mice or gamepads as control tools, which severely lack realistic motion capture interaction mechanisms. Their movement logic differs greatly from that of real skiing, relying solely on simple parameter mapping to simulate skiing movements without incorporating professional sports biomechanics algorithms as support.

[0004] In the crucial aspect of motion simulation, existing products lack the conversion from key point coordinates to joint angles and also lack a motion biomechanical simulation process. This results in simulated motion trajectories that deviate significantly from real skiing patterns. Users cannot experience the same level of physical exertion as real skiing, nor can they become truly immersed in the experience, thus failing to meet users' core demand for a "realistic skiing" experience.

[0005] Existing biomechanical models, as well as ski simulators and e-sports models, all share a common and serious problem: a lack of mechanical feedback between human movement and the environment. In fact, the mechanical interaction between the environment and the human body is the most crucial innovation point in the field of ski simulation. Only by accurately capturing and simulating this mechanical interaction can ski simulation products truly reproduce the mechanical relationship between a skier's movements and trajectory, providing users with a realistic and immersive skiing experience. While motion capture technology is a key technology for solving many of the aforementioned problems and has broad application prospects in the fields of winter sports training and simulation games, a mature, biomechanical-based virtual reality e-sports solution for skiing has not yet been developed. This highlights the urgency and importance of making breakthroughs by focusing on the mechanical interaction between the environment and the human body. Summary of the Invention

[0006] This invention provides a skiing metaverse e-sports platform based on real physical mechanics feedback to solve problems such as the high barrier to entry of traditional skiing, the lack of mechanical interaction analysis in existing simulation products, and the disconnect between the metaverse and e-sports scene experience.

[0007] The first aspect of this invention provides a skiing metaverse e-sports platform based on real physical and mechanical feedback, comprising: The motion recognition and capture system is used to collect and process images of skiers' human postures and depth information to obtain optimized 3D joint data. A sports biomechanics calculation system is used to solve for joint angle data based on the optimized three-dimensional joint point data, and to construct a multibody dynamics model based on the joint angle data to simulate a skiing trajectory that conforms to the laws of real skiing mechanics. The sports biomechanics calculation system includes: The joint angle conversion module is used to convert the optimized three-dimensional joint point data into local coordinates to calculate the angles and angle change rates of each joint in the human body as the joint angle data. The sports biomechanics modeling module is used to construct a multibody dynamics model that includes the mass, moment of inertia, and joint constraints of each limb segment of the human body based on the optimized three-dimensional joint data. The motion trajectory solving module is used to import the joint angle data and the multibody dynamics model into a pre-built biomechanical simulation platform to calculate the skier's real-time motion trajectory, turning radius, rate of change of speed and attitude adjustment range in combination with the snow track terrain parameters, and to simulate the skiing trajectory based on the real-time motion trajectory, the turning radius, the rate of change of speed and the attitude adjustment range. The virtual e-sports interaction system is used to construct virtual scenes, physical interaction logic, and multi-dimensional interactive feedback based on the simulated skiing trajectory. The Skiing Metaverse Ecosystem serves as the application carrier for the motion recognition and capture system, the sports biomechanics computing system, and the virtual e-sports interaction system, and integrates skiing training, entertainment and social interaction, and e-sports competition.

[0008] Optionally, the motion recognition and capture system includes: The depth acquisition module is used to acquire images of the skier's human posture and depth information; The joint point extraction module is used to extract the coordinates of 33 key points of the human body from the human posture image and the depth information, and generate three-dimensional joint point data based on the coordinates of the 33 key points of the human body. The data optimization module is used to perform calibration processing on the three-dimensional joint data using the Kalman filter algorithm to obtain the optimized three-dimensional joint data. The data transmission module is used to package the optimized three-dimensional joint data into a standardized data format and send it to the motion biomechanics calculation system through an end-to-end transmission protocol.

[0009] Optionally, the depth acquisition module is compatible with an optically marked motion capture module, which includes reflective markers, an infrared camera array, and a coordinate calculation submodule. The reflective markings are affixed to the skier's head, torso, hips, knees, ankles, and skis to form a human-ski linked marking system; The infrared camera array is set around the snowboard to capture the three-dimensional coordinates of reflective markers and generate the linkage posture data of the human body and the snowboard by combining the triangulation principle. The coordinate calculation submodule is used to calculate the linked posture data to obtain the skier's human posture image and depth information.

[0010] Optionally, the depth acquisition module is compatible with an optical label-free motion capture module, which includes an RGB-D camera group and a semantic segmentation submodule. The RGB-D camera group is deployed in front of, to the sides and behind the skier to form a 360° field of view without blind spots, so as to collect the linkage posture data of the human body and the snowboard. The semantic segmentation submodule uses a deep learning semantic segmentation algorithm to segment the snowboarder's body region and the snowboard equipment region in the linked posture data of the human body and the snowboard, so as to obtain the snowboarder's body posture image and depth information.

[0011] Optionally, the depth acquisition module is compatible with an inertial motion capture module, which includes an inertial measurement submodule and a data fusion submodule, wherein... The inertial measurement submodule uses a 9-axis IMU sensor, which is deployed on the skier's chest, waist, both thighs, both calves, and both ankles to collect acceleration, angular velocity, and magnetic field strength data. The data fusion submodule uses an extended Kalman filter algorithm to process the acceleration, angular velocity, and magnetic field strength data to calculate the skier's human posture image and depth information.

[0012] Optionally, the joint angle conversion module calculates key points of adjacent limb segments based on the principle of vector dot product and cross product to form the angles of each joint of the human body.

[0013] Optionally, the motion trajectory solving module is based on the Lagrange equation and constructs dynamic equations according to the biomechanical simulation platform and the snow track terrain parameters to solve the skier's real-time motion trajectory, turning radius, rate of change of speed, and attitude adjustment range.

[0014] Optionally, the virtual e-sports interaction system includes: The scene modeling module is used to construct the skeleton of the snow mountain track using terrain generation tools, and to create scene elements on the snow mountain track skeleton using 3D modeling tools to form a virtual snowfield scene. The physical interaction module is used to drive the virtual character to perform corresponding actions based on the virtual ski resort scene and the skiing trajectory, and to handle the force interaction between the virtual character and the ski slope terrain in order to conform to the physical laws of real skiing. The interactive feedback module is used to provide parameter setting options, background sound effects, operation feedback sound effects, and visual effects for the virtual ski resort scene. The game control module is used to provide game pause, rewind and fine-tuning of virtual character postures for the virtual snow field scene.

[0015] A second aspect of the present invention provides a metaverse system, comprising: a skiing metaverse e-sports platform based on real physical and mechanical feedback as described in the above embodiments, a carrier based on metaverse ecology, and a technical support module based on real physical and mechanical feedback.

[0016] Optionally, it also includes: In e-sports competition scenarios, it is used to support real-time online multiplayer battles, and through mechanical solution technology, it ensures that all users receive a unified standard of realistic physical feedback. Social entertainment scenarios are used to support users in creating virtual avatars, forming social groups, sharing ski tracks, communicating in real time via voice, and simultaneously sharing mechanical feedback data; Ski training scenarios are designed to provide skiers with professional movement guidance based on mechanical solution data.

[0017] The skiing metaverse e-sports platform based on real physical mechanics feedback proposed in this invention completes the conversion and simulation calculation of key point coordinates to joint angles through sports biomechanics algorithms. It breaks through the bottleneck of real physical world feedback simulation through mechanical solution technology, realizes high-precision mapping between real human movements and virtual skiing tracks, and provides an immersive, low-cost, and risk-free skiing simulation experience.

[0018] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0019] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 A block diagram illustrating a skiing metaverse e-sports platform based on real physical and mechanical feedback according to an embodiment of the present invention; Figure 2 This is an overall framework diagram of a skiing metaverse e-sports platform based on real physical and mechanical feedback, provided according to an embodiment of the present invention; Figure 3 This is an overall rendering of a virtual ski resort scene provided according to an embodiment of the present invention; Figure 4 This is a schematic diagram of a UI control interface provided according to an embodiment of the present invention.

[0020] Explanation of reference numerals in the attached figures: 10- A skiing metaverse e-sports platform based on real physical and mechanical feedback; 101- A motion recognition and capture system; 102- A sports biomechanical calculation system; 103- A virtual e-sports interaction system and a skiing metaverse ecosystem; 104. Detailed Implementation

[0021] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0022] The following description, with reference to the accompanying drawings, describes an embodiment of the skiing metaverse e-sports platform based on real physical and mechanical feedback.

[0023] Figure 1 This is a block diagram illustrating a skiing metaverse e-sports platform based on real physical and mechanical feedback, according to an embodiment of the present invention.

[0024] like Figure 1 As shown, the skiing metaverse e-sports platform 10 based on real physical and mechanical feedback includes: a motion recognition and capture system 101, a sports biomechanics calculation system 102, a virtual e-sports interaction system 103, and a skiing metaverse ecosystem 104.

[0025] The motion recognition and capture system 101 is used to acquire and process the skier's human posture images and depth information with high precision to obtain optimized three-dimensional joint point data. The sports biomechanics calculation system 102, as a core technology module, is used to solve for joint angle data based on the optimized three-dimensional joint point data, and to construct a multi-body dynamics model based on the joint angle data. Through mechanical solving, it achieves feedback simulation of the real physical world, thereby generating a ski trajectory that conforms to the laws of real skiing mechanics. The virtual e-sports interaction system 103 is used to construct virtual scenes, physical interactions, and interactive feedback based on the simulated ski trajectory driven by mechanical solving. The skiing metaverse ecosystem 104 serves as the core application carrier of the motion recognition and capture system 101, the sports biomechanics calculation system 102, and the virtual e-sports interaction system 103. It integrates multiple functions such as skiing training, entertainment and social interaction, and e-sports competition, prioritizing the deep integration of the metaverse scene and the e-sports experience, with real physical mechanics feedback as its core competitiveness. In this embodiment of the invention, the three components sequentially establish a data interaction link through network communication, forming a complete technical link of "motion acquisition - joint angle conversion - sports biomechanics simulation - virtual mapping".

[0026] In some embodiments, the motion recognition and capture system includes: The depth acquisition module is used to acquire high-precision images of skiers’ human posture and depth information, providing high-quality raw data for mechanical solutions. The joint point extraction module is used to extract the coordinates of 33 key points of the human body from human posture images and depth information, and generate three-dimensional joint point data based on the coordinates of the 33 key points of the human body to ensure that the key point data covers the core force-generating parts of skiing. The data optimization module is used to calibrate the 3D joint data using the Kalman filter algorithm to reduce data noise and latency, so as to obtain optimized 3D joint data and ensure the accuracy of mechanical solutions. The data transmission module is used to package the optimized 3D joint data into a standardized data format and send it to the motion biomechanics calculation system through an end-to-end transmission protocol to meet the real-time requirements of mechanical solution.

[0027] In actual implementation, such as Figure 2As shown, the depth acquisition module captures real-time images of the skier's human posture and depth information, providing basic data for joint point extraction. The joint point extraction module, based on a skeletal recognition framework, accurately extracts the coordinates of 33 key points from the acquired data, and generates 3D joint point data using depth back-projection technology, completely restoring the human skeletal distribution. The data optimization module uses a Kalman filter algorithm to reduce noise interference in the 3D joint point data through state estimation and error correction, calibrating the 3D joint point data to effectively reduce data jitter and transmission latency, ensuring the stability and coherence of the 3D skeletal posture, with transmission latency controlled within 50ms. The data transmission module packages the optimized 3D joint point data into JSON format and transmits it to the sports biomechanics computing system via TCP or WebSocket protocols, ensuring the reliability and real-time performance of data transmission.

[0028] Furthermore, the depth acquisition module in this embodiment of the invention is compatible with optical marked motion capture units, optical unmarked motion capture units, and inertial motion capture units to adapt to human posture acquisition in various scenarios and achieve three-dimensional data capture of core movements such as standing posture, turning, and carving during snowboarding.

[0029] Specifically, the depth acquisition module can be independently compatible with an optical marked motion capture module. The optical marked motion capture module includes reflective markers, an infrared camera array, and a coordinate calculation submodule. Reflective markers are affixed to the skier's head, torso, hips, knees, ankles, and skis to form a human-ski linkage marking system. This ensures that the collected data reflects the mechanical linkage between the human body and the equipment. It should be noted that there are no fewer than 18 reflective markers. An infrared camera array is set up around the snowboard, with no fewer than 4 cameras and a sampling frequency of no less than 60fps. This is to capture the three-dimensional coordinates of reflective markers and generate the linkage posture data of the human body and the snowboard by combining the triangulation principle, so as to provide accurate motion correlation data for mechanical solutions. The positioning accuracy of the marker coordinates is ≤1mm. The coordinate calculation submodule is used to calculate the linkage posture data to obtain the skier's human posture image and depth information, ensuring the accuracy of the basic data for mechanical solutions.

[0030] Furthermore, the depth acquisition module in this embodiment of the invention is independently compatible with the optical label-free motion capture unit. The optical label-free motion capture module includes an RGB-D camera group and a semantic segmentation submodule, wherein... The RGB-D camera group is deployed in front of, to the side and behind the skier to form a 360° field of view without blind spots, in order to collect the linkage posture data of the human body and the snowboard, with a sampling frequency of no less than 30fps. The semantic segmentation submodule utilizes deep learning semantic segmentation algorithms to accurately segment the snowboarder's body region and the snowboard equipment region in the linked posture data of the human body and the snowboard. This allows for precise separation of the core movement subject and equipment, eliminating background interference. It directly extracts the three-dimensional coordinates of 33 key points of the human body and snowboard edge feature points (no less than 4) from RGB images and depth data, generating non-contact posture-equipment linkage data, namely the snowboarder's human posture image and depth information, providing a clear data dimension for mechanical solutions.

[0031] Furthermore, the depth acquisition module in this embodiment of the invention is independently compatible with the inertial motion capture module. The inertial motion capture module includes an inertial measurement submodule and a data fusion submodule, wherein... The inertial measurement module uses 9-axis IMU sensors, deployed on the skier's chest, waist, both thighs, both calves, and both ankles. Each IMU sensor has a sampling frequency of no less than 60Hz, synchronously collecting acceleration, angular velocity, and magnetic field strength data to directly obtain raw data on the mechanical characteristics during motion. The data fusion submodule uses the extended Kalman filter algorithm to fuse data from multiple IMU sensors and calculate the joint angles of the human body and the spatial posture of the skis, namely the human posture image and depth information of the skier, providing highly reliable kinematic fundamental data for mechanical solutions, with a posture calculation error ≤0.5°; The wireless transmission submodule can transmit data via Bluetooth 5.0 or WiFi 6 protocols with a transmission latency of ≤30ms, and can connect with the data optimization module to complete data calibration and integration.

[0032] Furthermore, in this embodiment of the invention, the depth acquisition module can support the individual or mixed activation of three modes: optical marked motion capture module, optical unmarked motion capture module, and inertial motion capture module. When the mixed mode is activated, the attitude data acquired by the three modes is complementaryly corrected through a data fusion algorithm to eliminate blind zone errors of a single motion capture mode (such as optical motion capture occlusion area and inertial motion capture cumulative error), thereby further improving the acquisition accuracy and stability of human posture and snowboard motion state.

[0033] In some embodiments, the sports biomechanics computing system includes: The joint angle conversion module is used to convert the optimized 3D joint point data into local coordinates to calculate the angles and angle change rates of each joint in the human body as joint angle data. The sports biomechanics modeling module is used to construct a multibody dynamics model containing the mass, moment of inertia and joint constraints of each limb segment of the human body based on the optimized 3D joint data, providing a basic framework for mechanical solutions. The motion trajectory solving module is used to import joint angle data and multibody dynamics models into a pre-built biomechanical simulation platform. Based on the core logic of mechanical solving, it calculates the skier's real-time motion trajectory, turning radius, rate of change of speed, and attitude adjustment range by combining snow track terrain parameters. It also accurately simulates the skiing trajectory based on the real-time motion trajectory, turning radius, rate of change of speed, and attitude adjustment range, which all reflect the mechanical feedback characteristics of the real physical world.

[0034] In some embodiments, the joint angle conversion module calculates key points of adjacent limb segments based on the principle of vector dot product and cross product to form the angles of each joint in the human body, providing core joint mechanical parameters for mechanical solutions.

[0035] In some embodiments, the motion trajectory solution module is based on the Lagrange equation, constructs dynamic equations according to the biomechanical simulation platform and snow track terrain parameters, and precisely solves the skier's real-time motion trajectory, turning radius, rate of change of speed and attitude adjustment range through the core logic of mechanical solution, ensuring that all parameters reflect the mechanical feedback law of the real physical world.

[0036] In actual implementation, such as Figure 2 As shown, the joint angle conversion module uses the midpoint of the line connecting the two feet as the origin, converting the coordinates of 33 three-dimensional joint points into local coordinates. Based on the principles of vector dot product and cross product, it calculates the relative angles and rate of change of each joint. Specifically, the calculation method is as follows: Let the coordinates of the key points of two adjacent limb segments be... , , Construct vectors with vector Through formula Calculate joint angles It covers the hip, knee, and ankle joints of the lower limbs, the spinal joints of the trunk, and the shoulder, elbow, and wrist joints of the upper limbs, providing core input data for sports biomechanics simulation.

[0037] Furthermore, in the sports biomechanics modeling module, a multibody dynamics model is constructed based on the principles of sports biomechanics, including the mass, moment of inertia, and joint constraints of each limb segment. The limb segment mass and moment of inertia are set based on human anatomical data, with the lower limbs accounting for a higher proportion of mass than the upper limbs. The thigh segment accounts for 10-15% of the total body mass, the lower leg segment for 6-10%, and the trunk segment for 40-50%. The joint constraint model sets the range of motion for the lower limb joints (hip flexion 0-120°, extension 0-30°, knee flexion 0-150°, ankle dorsiflexion 0-20°, plantar flexion 0-50°), with lower limb joint constraints having a higher priority than upper limb constraints. This accurately simulates the limb linkage mechanism and mechanical transmission path in real skiing, closely matching the force exertion characteristics of the human body during skiing.

[0038] The motion trajectory solving module imports joint angle data and multibody dynamics models into the biomechanical simulation platform, and combines them with snow track terrain parameters (slope, curvature, friction coefficient, etc.) to construct dynamic equations based on the Lagrange equations (expression: ,in, Lagrange ( , As kinetic energy, (potential energy) For generalized coordinates (joint angles). This refers to the generalized velocity (joint angular velocity). (For generalized forces), the system calculates the skier's real-time trajectory, turning radius, rate of change of speed, and attitude adjustment range to achieve a realistic simulation of the skiing trajectory. When the joint range of motion exceeds the preset range, a fall detection is triggered and a respawn mechanism is activated.

[0039] In some embodiments, the virtual esports interaction system includes: The scene modeling module is used to construct the skeleton of the snow mountain track using terrain generation tools, and to create scene elements on the snow mountain track skeleton using 3D modeling tools to form a highly immersive virtual snow field scene. The scene design prioritizes meeting the visual needs of metaverse social interaction and e-sports competition. The physics interaction module is used to drive the corresponding actions of the virtual character based on the ski trajectory driven by mechanics solution in the virtual ski resort scene, and to handle the force interaction between the virtual character and the ski terrain, so as to conform to the real skiing physics and enhance the real physical feedback experience. The interactive feedback module provides parameter setting options, background sound effects, operation feedback sound effects, and visual effects for the virtual ski resort scene. The feedback effect is linked with the mechanical solution results in real time, allowing users to intuitively perceive real physical feedback. The game control module provides game pause, rewind and fine-tuning functions for the virtual snow field scene. The function design prioritizes adapting to the operation requirements of e-sports and the interaction logic of the metaverse scene.

[0040] In some embodiments, the terrain generation tool is a GPU-accelerated real-time 3D terrain generation software, and the 3D modeling tool is an open-source 3D modeling software.

[0041] In actual implementation, such as Figure 2As shown, the virtual e-sports interactive system includes a scene modeling module, a physical interaction module, an interaction feedback module, and a game control module. The scene modeling module uses a GPU-accelerated terrain generation tool to construct the skeleton of the snow mountain track. It uses open-source 3D modeling tools to create terrain details, vegetation, protective facilities, and other scene elements, integrating snow environment resources to form a virtual snowfield scene of at least 3000m × 3000m. The snow track width is set to 8-12m. Simultaneously, the terrain is optimized to eliminate path breaks and surface defects, and the slope distribution and geometric smoothness of the snow track are adjusted to ensure compatibility with the calculated motion trajectory results.

[0042] The physics interaction module receives the motion trajectory and mechanical parameters output by the sports biomechanics calculation system, and drives the virtual character to complete actions such as turning, accelerating, and decelerating. It uses a combination of ray detection and collision detection to process the interaction between the virtual character and the snow terrain in real time. The detection frequency is consistent with the motion data acquisition frequency to ensure real-time interaction and that the character's movement conforms to the physical laws of real skiing.

[0043] The interactive feedback module includes a UI display unit, a sound effects unit, and a visual effects unit. The UI control unit provides parameter settings such as resolution, image quality, and anti-aliasing, and displays information such as skiing duration, instantaneous speed, and trajectory deviation in real time. The sound effects unit has built-in background sound effects and operation feedback sound effects. The visual effects unit includes visual presentation functions such as dynamic blur, snow mark generation, and particle effects to achieve multi-sensory immersion.

[0044] The game control module includes a pause unit, a checkpoint unit, and a character adjustment unit. The pause unit allows users to trigger a pause operation; the checkpoint unit triggers a rollback function when the virtual character goes out of the ski slope range, returning the character to the previous checkpoint; and the character adjustment unit dynamically fine-tunes the virtual character's posture based on the deviation of the movement trajectory to ensure the continuity of movement.

[0045] The following detailed description of the skiing metaverse e-sports platform based on real physical and mechanical feedback proposed in this invention will be provided through a specific embodiment.

[0046] Activate the depth acquisition module and install it at the preset height and angle to ensure complete capture of the human body's full posture. Set the sampling frequency to 30fps or higher and enable the image and depth information acquisition function to capture real-time images of the user's skiing posture and depth data.

[0047] The acquired images and depth information are transmitted in real time to the joint point extraction module. Based on the skeleton recognition framework, this module preprocesses the input data (including image noise reduction, grayscale correction, and depth calibration) and extracts the two-dimensional coordinates of 33 key points of the human body. Then, combined with depth back projection technology, the two-dimensional coordinates are converted into three-dimensional joint point data to form a complete three-dimensional dataset of human skeleton key points.

[0048] The 3D joint data is transmitted to the data optimization module, the Kalman filter algorithm is started, and the filtering parameters (including process noise covariance, observation noise covariance, and initial state covariance) are set to calibrate the 3D joint data, remove abnormal data points, reduce data jitter, compensate for transmission delay, and reconstruct complete and coherent 3D skeleton posture data, ensuring that the data transmission delay is controlled within 50ms.

[0049] The optimized 3D skeletal posture data is packaged in a standardized JSON format using a data transmission module. TCP or WebSocket protocols are selected as the end-to-end transmission protocols to establish a stable data connection with the sports biomechanics computing system, and the packaged data is transmitted to the sports biomechanics computing system in real time.

[0050] After the joint angle conversion module receives the 3D joint point data, it establishes a local coordinate system with the midpoint of the line connecting the two feet as the origin, and converts the coordinates of the 33 3D joint points into coordinate values ​​in this local coordinate system. Based on the principles of vector dot product and cross product, it calculates the coordinates of key points of adjacent limb segments, constructs the vector relationship between adjacent limb segments, and uses formulas to... Calculate the relative angles and rate of change of angles of each joint (hip, knee, ankle, spine, shoulder, elbow, wrist, etc.) to form a joint angle dataset.

[0051] In the sports biomechanics modeling module, based on the principles of sports biomechanics and combined with human anatomical data, the mass parameters (thigh segment mass percentage 10-15%, lower leg segment 6-10%, trunk segment 40-50%, upper limbs and other parts 25-44%) and rotational inertia parameters of each limb segment are set. Joint constraints are set, defining the range of motion angles of the lower limb joints (hip flexion 0-120°, extension 0-30°, knee flexion 0-150°, ankle dorsiflexion 0-20°, plantar flexion 0-50°), and setting the lower limb joint constraints to have a higher priority than the upper limb joints, thus constructing a complete multibody dynamics model. The limb segment mass and rotational inertia are set based on human anatomical data, and the joint constraints set the range and priority of the lower limb joint motion angles. This model is then imported into the biomechanical simulation platform to complete the model initialization configuration. The multibody dynamics model is trained and optimized using more than 20 sets of human anatomical data and mechanical feature samples of different skiing movements.

[0052] In the motion trajectory solution module, the initialized multibody dynamics model is retrieved from the biomechanical simulation platform, the joint angle dataset is imported, and preset snow track terrain parameters (slope 5-35 degrees, friction coefficient 0.08-0.15, curvature set according to snow track design parameters) are input; the dynamic equations are constructed based on the Lagrange equations. ,in, ( As kinetic energy, (potential energy) For joint angle, The joint angular velocity, The force is a generalized force (including gravity, support force, friction, and air resistance). The dynamic equations are solved by numerical calculation methods to obtain the skier's real-time trajectory, turning radius, rate of change of speed, and attitude adjustment range, among other core motion parameters.

[0053] Using terrain generation tools and GPU acceleration, the skeleton of the snow mountain track was constructed. 3D modeling tools were used to create terrain details, vegetation, safety features, and other scene elements. Snowfield environment resources were integrated, and the virtual snowfield scene was at least 3000m × 3000m in size, with a ski slope width of 8-12m. A preliminary snow mountain terrain model was generated according to the preset ski slope direction, gradient changes, and curvature distribution. Figure 3 As shown.

[0054] Using 3D modeling tools, terrain detail elements (such as rocks, depressions, and protrusions), vegetation models (such as trees and grass), and protective facility models (such as protective nets and fences) are created. Texture mapping and lighting rendering are applied to each model to enhance its realism. The completed models are then imported into terrain generation tools and integrated with the preliminary snow mountain terrain model to form a complete initial draft of the virtual snowfield scene.

[0055] The initial draft of the virtual ski resort scene is optimized by: eliminating height differences and breaks in the ski slope path using terrain editing functions, adjusting the slope distribution and geometric smoothness (i.e., surface geometry) of the ski slope to ensure a smooth ski slope that matches the motion trajectory calculation results; rationally arranging the elements in the ski resort scene to avoid overlapping or uneven distribution of scene elements; and exporting the optimized virtual ski resort scene to a format supported by the 3D engine.

[0056] Configure the ski resort terrain parameter adjustment function, establish the association between parameters such as slope and friction coefficient and the UI control unit, and set the parameter adjustment range (slope 5-35 degrees, friction coefficient 0.08-0.15) to ensure that users can customize and adjust the terrain parameters through the UI interface.

[0057] In the physical interaction module of the virtual e-sports interactive system, data communication is established with the sports biomechanics calculation system to receive motion trajectory and mechanical parameter data in real time and parse motion commands (turning, acceleration, deceleration, etc.) in the data.

[0058] Based on the parsed motion commands, the virtual character model is driven to perform corresponding actions, ensuring that the virtual character's posture, trajectory, and motion parameter data remain consistent. Simultaneously, collision detection is activated, employing a combination of raycasting and collider detection to process the interaction forces between the virtual character and the snow track terrain in real time. The detection frequency is set to match the motion data acquisition frequency (no less than 30fps). Collision detection determines the approximate contact area between the virtual character and the snow track terrain, while raycasting precisely locates the mechanical feedback parameters at the contact point. Specifically, the combination of raycasting and collider detection works as follows: collider detection determines the approximate contact area between the virtual character and the snow track terrain, while raycasting precisely locates the mechanical feedback parameters at the contact point.

[0059] Based on the slope and curvature of the ski slope, the mechanical feedback parameters (such as the magnitude of friction and the direction of support force) between the virtual character and the ski slope are dynamically adjusted to ensure that the movement of the virtual character conforms to the physical laws of real skiing and to avoid unexpected shaking, airborne or other abnormal phenomena.

[0060] The UI control unit loads the parameter setting interface and data display interface. The parameter setting interface provides options such as resolution (e.g., 640×480 and above), image quality (low, medium, high), and anti-aliasing (on / off). The data display interface refreshes in real time and displays information such as skiing duration, instantaneous speed, and trajectory deviation, ensuring that the information display delay does not exceed 100ms.

[0061] Start the sound effects unit to load background sound effect files, set the sound effect playback mode to automatically loop after the game starts; configure operation feedback sound effects (such as sound effects corresponding to actions like turning, accelerating, and collisions), set sound effect trigger conditions, and ensure that the corresponding feedback sound effects are played in real time when the action occurs.

[0062] Enable the visual effects unit, activate the dynamic blur effect (dynamically adjust the blur intensity according to the speed of the virtual character), start the snow trail generation function (generate snow trails in real time during the virtual character's gliding process, and the snow trail retention time is configurable), and load particle effects (such as falling snowflakes, snow splashing during gliding, etc.) to enhance the visual immersion.

[0063] like Figure 4As shown, the pause function of the game control module is activated, and the pause trigger method is set (such as a specific keyboard key or UI interface button). After pausing, the game screen, sound effects, and character movement are frozen, and the state before pausing is restored. A checkpoint unit is configured, and checkpoints are evenly set according to the length of the ski slope. When the virtual character runs out of the ski slope range, the backtracking function is triggered, which teleports the virtual character to the nearest checkpoint and resumes movement. The character adjustment unit is activated to monitor the deviation between the virtual character's movement trajectory and the ideal trajectory in real time. When the deviation exceeds a preset threshold, the posture parameters of the virtual character are dynamically fine-tuned to ensure the continuity and smoothness of the movement.

[0064] The skiing metaverse e-sports platform based on real physical and mechanical feedback proposed in the embodiments of the present invention has the following beneficial effects: (1) Based on the complete technical link of sports biomechanics, the key point coordinates are converted into joint angles through the joint angle conversion module. The motion trajectory is solved by combining the multibody dynamics model and the biomechanical simulation platform. This breaks through the technical limitations of existing skiing simulation products that only use simple parameter mapping. It accurately restores the mechanical characteristics of limb linkage in skiing, so that the virtual skiing trajectory fully conforms to the mechanical laws of real skiing and significantly enhances the sense of immersion. (2) The three-dimensional joint data is optimized by Kalman filtering algorithm, the transmission delay is controlled within 50ms, and the joint angle is accurately calculated by vector operation, providing high-quality data support for sports biomechanical simulation and ensuring the synchronization of motion capture and trajectory simulation. (3) The multibody dynamics model sets the mass and moment of inertia of limb segments based on human anatomical data, and reasonably sets the range and priority of joint constraints to fit the limb force and movement characteristics of real skiing, making the simulation effect more convincing. (4) The virtual ski resort scene has been optimized in multiple rounds. The terrain parameters (slope, friction coefficient, etc.) can be customized and adjusted to meet the needs of users with different skiing levels. It also supports convenient functions such as checkpoint retracing and pausing to improve the user experience. (5) It can provide ordinary users with a low-cost, risk-free immersive skiing experience, helping to popularize ice and snow sports; it can also serve as a virtual training auxiliary platform for professional skiers, providing scientific training guidance through motion trajectory analysis and feedback; and it can also be expanded into a multiplayer online e-sports platform, with broad market application prospects.

[0065] Secondly, this invention also proposes a skiing metaverse e-sports system.

[0066] The skiing metaverse e-sports system includes: a skiing metaverse e-sports platform based on real physical and mechanical feedback according to the above embodiments, a carrier based on the metaverse ecosystem, a technical support module based on real physical and mechanical feedback, e-sports competition scenarios, social entertainment scenarios, and skiing training scenarios.

[0067] The e-sports arena supports real-time multiplayer battles, using mechanics-based problem-solving techniques to ensure all users receive consistent and realistic physical feedback. The social entertainment arena allows users to create virtual avatars, form social groups, share ski tracks, and communicate via real-time voice, while simultaneously sharing mechanics feedback data. The ski training arena provides professional movement guidance to skiers based on mechanics-based problem-solving data.

[0068] Specifically, the system uses the metaverse ecosystem as its core carrier, e-sports as its core application scenario, and realistic physical and mechanical feedback as its core technological support, constructing a three-in-one architecture of "metaverse + e-sports + realistic physical and mechanical feedback." Furthermore, the system focuses on three core scenarios: ski training, social interaction, and e-sports competition. It prioritizes achieving real-time multiplayer e-sports battles, consistent and synchronized mechanical feedback, and the construction of social relationship chains within the metaverse scenario. Through mechanical solution technology, it ensures that different users receive a unified standard of realistic physical feedback experience in the metaverse space, creating a metaverse e-sports ecosystem with strong immersion and competitive fairness.

[0069] It should be noted that the foregoing explanation of the embodiment of the skiing metaverse e-sports platform based on real physical and mechanical feedback also applies to the skiing metaverse e-sports system of this embodiment, and will not be repeated here.

[0070] The skiing metaverse e-sports system proposed in the embodiments of the present invention has the following beneficial effects: (1) Based on the complete technical link of sports biomechanics, the key point coordinates are converted into joint angles through the joint angle conversion module. The motion trajectory is solved by combining the multibody dynamics model and the biomechanical simulation platform. This breaks through the technical limitations of existing skiing simulation products that only use simple parameter mapping. It accurately restores the mechanical characteristics of limb linkage in skiing, so that the virtual skiing trajectory fully conforms to the mechanical laws of real skiing and significantly enhances the sense of immersion. (2) The three-dimensional joint data is optimized by Kalman filtering algorithm, the transmission delay is controlled within 50ms, and the joint angle is accurately calculated by vector operation, providing high-quality data support for sports biomechanical simulation and ensuring the synchronization of motion capture and trajectory simulation. (3) The multibody dynamics model sets the mass and moment of inertia of limb segments based on human anatomical data, and reasonably sets the range and priority of joint constraints to fit the limb force and movement characteristics of real skiing, making the simulation effect more convincing. (4) The virtual ski resort scene has been optimized in multiple rounds. The terrain parameters (slope, friction coefficient, etc.) can be customized and adjusted to meet the needs of users with different skiing levels. It also supports convenient functions such as checkpoint retracing and pausing to improve the user experience. (5) It can provide ordinary users with a low-cost, risk-free immersive skiing experience, helping to popularize ice and snow sports; it can also serve as a virtual training auxiliary platform for professional skiers, providing scientific training guidance through motion trajectory analysis and feedback; and it can also be expanded into a multiplayer online e-sports platform, with broad market application prospects.

[0071] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

Claims

1. A skiing metaverse e-sports platform based on real physical mechanics feedback, characterized in that, include: The motion recognition and capture system is used to collect and process images of skiers' human postures and depth information to obtain optimized 3D joint data. A sports biomechanics calculation system is used to solve for joint angle data based on the optimized three-dimensional joint point data, and to construct a multibody dynamics model based on the joint angle data to simulate a skiing trajectory that conforms to the laws of real skiing mechanics. The sports biomechanics calculation system includes: The joint angle conversion module is used to convert the optimized three-dimensional joint point data into local coordinates to calculate the angles and angle change rates of each joint in the human body as the joint angle data. The sports biomechanics modeling module is used to construct a multibody dynamics model that includes the mass, moment of inertia, and joint constraints of each limb segment of the human body based on the optimized three-dimensional joint data. The motion trajectory solving module is used to import the joint angle data and the multibody dynamics model into a pre-built biomechanical simulation platform to calculate the skier's real-time motion trajectory, turning radius, rate of change of speed and attitude adjustment range in combination with the snow track terrain parameters, and to simulate the skiing trajectory based on the real-time motion trajectory, the turning radius, the rate of change of speed and the attitude adjustment range. The virtual e-sports interaction system is used to construct virtual scenes, physical interaction logic, and multi-dimensional interactive feedback based on the simulated skiing trajectory. The Skiing Metaverse Ecosystem serves as the application carrier for the motion recognition and capture system, the sports biomechanics computing system, and the virtual e-sports interaction system, and integrates skiing training, entertainment and social interaction, and e-sports competition.

2. The skiing metaverse e-sports platform based on real physical mechanics feedback according to claim 1, characterized in that, The motion recognition and capture system includes: The depth acquisition module is used to acquire images of the skier's human posture and depth information; The joint point extraction module is used to extract the coordinates of 33 key points of the human body from the human posture image and the depth information, and generate three-dimensional joint point data based on the coordinates of the 33 key points of the human body. The data optimization module is used to perform calibration processing on the three-dimensional joint data using the Kalman filter algorithm to obtain the optimized three-dimensional joint data. The data transmission module is used to package the optimized three-dimensional joint data into a standardized data format and send it to the motion biomechanics calculation system through an end-to-end transmission protocol.

3. The skiing metaverse e-sports platform based on real physical mechanics feedback according to claim 2, characterized in that, The depth acquisition module is compatible with an optically marked motion capture module, which includes reflective markers, an infrared camera array, and a coordinate calculation submodule. The reflective markings are affixed to the skier's head, torso, hips, knees, ankles, and skis to form a human-ski linked marking system; The infrared camera array is set around the snowboard to capture the three-dimensional coordinates of reflective markers and generate the linkage posture data of the human body and the snowboard by combining the triangulation principle. The coordinate calculation submodule is used to calculate the linked posture data to obtain the skier's human posture image and depth information.

4. The skiing metaverse e-sports platform based on real physical mechanics feedback according to claim 2, characterized in that, The depth acquisition module is compatible with an optical label-free motion capture module, which includes an RGB-D camera group and a semantic segmentation submodule. The RGB-D camera group is deployed in front of, to the sides and behind the skier to form a 360° field of view without blind spots, so as to collect the linkage posture data of the human body and the snowboard. The semantic segmentation submodule uses a deep learning semantic segmentation algorithm to segment the snowboarder's body region and the snowboard equipment region in the linked posture data of the human body and the snowboard, so as to obtain the snowboarder's body posture image and depth information.

5. The skiing metaverse e-sports platform based on real physical mechanics feedback according to claim 2, characterized in that, The depth acquisition module is compatible with an inertial motion capture module, which includes an inertial measurement submodule and a data fusion submodule. The inertial measurement submodule uses a 9-axis IMU sensor, which is deployed on the skier's chest, waist, both thighs, both calves, and both ankles to collect acceleration, angular velocity, and magnetic field strength data. The data fusion submodule uses an extended Kalman filter algorithm to process the acceleration, angular velocity, and magnetic field strength data to calculate the skier's human posture image and depth information.

6. The skiing metaverse e-sports platform based on real physical mechanics feedback according to claim 1, characterized in that, The joint angle conversion module calculates key points of adjacent limb segments based on the principles of vector dot product and cross product to form the angles of each joint of the human body.

7. The skiing metaverse e-sports platform based on real physical mechanics feedback according to claim 1, characterized in that, The motion trajectory solving module is based on the Lagrange equation and constructs dynamic equations according to the biomechanical simulation platform and the snow track terrain parameters to solve the skier's real-time motion trajectory, turning radius, rate of change of speed, and attitude adjustment range.

8. The skiing metaverse e-sports platform based on real physical mechanics feedback according to claim 1, characterized in that, The virtual e-sports interaction system includes: The scene modeling module is used to construct the skeleton of the snow mountain track using terrain generation tools, and to create scene elements on the snow mountain track skeleton using 3D modeling tools to form a virtual snowfield scene. The physical interaction module is used to drive the virtual character to perform corresponding actions based on the virtual ski resort scene and the skiing trajectory, and to handle the force interaction between the virtual character and the ski slope terrain in order to conform to the physical laws of real skiing. The interactive feedback module is used to provide parameter setting options, background sound effects, operation feedback sound effects, and visual effects for the virtual ski resort scene. The game control module is used to provide game pause, rewind and fine-tuning of virtual character postures for the virtual snow field scene.

9. A skiing metaverse e-sports system, characterized in that, include: The skiing metaverse e-sports platform based on real physical and mechanical feedback, the carrier based on metaverse ecology, and the technical support module based on real physical and mechanical feedback as described in any one of claims 1-8.

10. The skiing metaverse e-sports system according to claim 9, characterized in that, Also includes: In e-sports competition scenarios, it is used to support real-time online multiplayer battles, and through mechanical solution technology, it ensures that all users receive a unified standard of realistic physical feedback. Social entertainment scenarios are used to support users in creating virtual avatars, forming social groups, sharing ski tracks, communicating in real time via voice, and simultaneously sharing mechanical feedback data; Ski training scenarios are designed to provide skiers with professional movement guidance based on mechanical solution data.

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