Animation motion capture device for virtual reality technology

Abstract

The invention discloses an animation motion capture device for a virtual reality technology, and particularly relates to the technical field of virtual reality, which comprises a data acquisition module for capturing and collecting user motion and environment information, and a data processing module for analyzing, converting and optimizing the acquired data. Through cooperative work of the data acquisition module, the data processing module, the rendering feedback module and the like, accurate capture and real-time feedback of user actions are achieved, it is ensured that physical attributes of a virtual environment and a real environment are highly consistent, the data acquisition module can obtain multi-dimensional information such as somatosensory, expressions and environments of a user at high precision, and the user experience is improved. And the data processing module accurately identifies and optimizes user actions through a deep learning algorithm and a skeleton mapping technology, and the rendering and feedback module generates vivid visual, tactile and sound effect feedback, so that high immersive experience is brought, and fluency and consistency of actions and feedback are guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of virtual reality technology, and in particular to an animation motion capture device used in virtual reality technology. Background Art

[0002] With the development of virtual reality (VR) technology, VR has been widely used in many fields such as games, film and television production, training simulation, etc., and users have higher and higher requirements for interactive experience in virtual environments. In order to enhance the user's immersion and interactive effect, accurately capturing the user's movements and converting them into the movements of virtual characters has become a key link in VR technology. Motion capture technology can greatly enhance the realism and immersion of the virtual environment by tracking the user's body movements in real time and converting these motion data into the movements of virtual characters. Traditional motion capture devices usually rely on external cameras, sensors or wearable devices to collect data, and then convert these data into the movements of virtual characters through complex algorithms. However, as users' requirements for motion capture accuracy, real-time performance and natural fluency continue to increase, existing motion capture technology still has certain limitations in these aspects.

[0003] In the prior art, the existing motion capture devices can realize the tracking of user movements and the synchronous display of virtual characters, but in practical applications, there are still some shortcomings. First, the existing technology has limited accuracy in capturing user movements, especially in capturing subtle movements and facial expressions. The performance is relatively rough and it is difficult to meet the application scenarios with high requirements for realism. Secondly, the processing speed of captured data is slow, and it is impossible to achieve real-time synchronization between virtual characters and user movements, resulting in delayed action feedback in the virtual environment, affecting the user's immersive experience. In addition, due to differences in user bone structure, the existing motion capture system is difficult to adaptively adjust the bone proportions and action performance of the virtual character when processing the actions of different users, resulting in the virtual character's actions being inconsistent with the user's actual actions, showing unnatural movements.

[0004] In addition, since extreme movements may exceed the range of motion of the virtual skeleton, existing technologies often cannot effectively handle these extreme movements, which may cause the skeleton of the virtual character to be distorted or abnormal, affecting the natural smoothness of the movement. At the same time, the existing motion capture system is relatively weak in optimizing multi-joint coherent movements, resulting in the virtual character's movements not being smooth enough when switching quickly or multi-joint coordinated movements, affecting the overall visual effect and user experience. Therefore, we provide an animation motion capture device for virtual reality technology. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings in the prior art and to propose an animation motion capture device for virtual reality technology.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] An animation motion capture device for virtual reality technology, comprising a data acquisition module for capturing and collecting user motion and environmental information, a data processing module for analyzing, converting and optimizing the collected data, a rendering and feedback module for converting the processed data into visual and tactile feedback, and a data storage and analysis module for storing, analyzing and optimizing data;

[0008] The data acquisition module includes a sensor management module for managing motion capture sensors, a biometric capture module for collecting user biometric information through body tracking, eye tracking and facial expression capture, an environmental data acquisition module for collecting spatial position and ambient lighting information to ensure that the physical properties of the virtual environment match the real one, a high-precision tracking module for capturing tiny movements using multi-point calibration and an accurate positioning system, and a dynamic data filtering module for real-time processing and filtering of the collected data to eliminate noise;

[0009] The data processing module includes an action recognition algorithm module based on deep learning that can convert complex action signals into system-recognizable behaviors, a data stream optimization module for compressing, denoising and completing the collected raw data, a bone mapping conversion module for mapping the user's actual actions to a virtual bone model, a physical attribute matching module for adjusting the character's physical feedback according to the user's posture and movement state, and a real-time data buffer module for setting up a buffer to handle delays and smoothly transition before data arrives for rendering.

[0010] The present invention is further configured as follows: the rendering and feedback module includes a real-time rendering engine module for real-time rendering of the dynamic performance of the virtual character through GPU acceleration, a tactile feedback module for conveying physical feedback in the virtual world to the user using a tactile vest and a glove device, a sound effect feedback generation module for generating matching environmental sound effects for action events, an environmental interaction rendering module for adjusting the position, state and reaction of objects in the virtual space according to user actions, and a visual synchronization optimization module for eliminating dynamic blur and visual delay through multi-level rendering;

[0011] The data storage and analysis module includes an action recording and playback module for storing all user action data, a big data analysis module for mining user habits through machine learning based on user action data, an adaptive learning module for adaptively adjusting capture parameters and feedback strategies by continuously analyzing user habits, a cloud storage and backup module for backing up data in the cloud and supporting data synchronization of different devices, and a data privacy protection module for applying encryption technology to ensure the security of user personal data.

[0012] The present invention is further configured as follows: the skeleton mapping conversion module includes a motion capture point distribution determination module for determining whether the actual motion capture points of the user are evenly distributed on the joints and bones, a skeleton position re-screening module for cleaning and re-tableating punctuation data for unqualified skeleton points, a skeleton position accuracy determination module for determining the accuracy of the skeleton position through real-time monitoring and calibration algorithms, a skeleton position accuracy fine-tuning module for manually fine-tuning the skeleton point data with slightly deviated skeleton position accuracy, a joint angle dynamic adjustment module for real-time dynamic adjustment of the user's joint angle, a skeleton proportion adaptive adjustment module for adaptively adjusting the virtual skeleton model according to the user's skeleton proportion, a micro-motion compensation module for capturing the user's subtle movements when stationary or slightly moving, amplifying them and compensating them to the skeleton of the virtual character, a skeleton distortion protection module for preventing the skeleton of the virtual character from being distorted or deformed due to exceeding the normal range in extreme motion situations, a virtual-real time correction module for synchronizing the time node of the user's action with the action time of the virtual character, and a multi-branch skeleton smoothness optimization module for processing the motion smoothness problem in a complex multi-branch skeleton system to ensure smooth motion transmission between multiple joints and bones without motion stiffness or breakage.

[0013] The present invention is further configured as follows: the motion capture point distribution determination module first detects whether the distribution of the user's motion capture points on the joints and bones is uniform. If it is determined to be uneven, the bone position re-screening module will clean and re-screen these unqualified capture points; after completing the screening, the bone position re-screening module will pass the qualified data to the bone position accuracy determination module, which determines the accuracy of these capture points through real-time monitoring and calibration algorithms; when the bone position accuracy determination module finds that the accuracy of some capture points is slightly deviated, it will hand over these points to the bone position accuracy fine-tuning module for manual fine-tuning.

[0014] The present invention is further configured as follows: the bone position accuracy fine-tuning module fine-tunes the bone point data with a slight position deviation and transmits the fine-tuned data to the joint angle dynamic adjustment module, which dynamically adjusts the user's joint angle according to the adjusted bone position so that the joint angle of the virtual character is consistent with the user's actual action; the joint angle dynamic adjustment module ensures the consistency of the joint angle, and then the bone proportion adaptive adjustment module adaptively adjusts the bone model of the virtual character according to the user's bone proportion to match the user's body shape characteristics.

[0015] The present invention is further configured as follows: after the skeletal proportion adaptive adjustment module completes the adaptation of the skeletal proportion, the micro-motion compensation module starts to work to capture the user's subtle movements when still or slightly moving, and amplifies and processes these tiny movements and maps them to the virtual character; after the micro-motion compensation module maps the subtle movements to the virtual character, the skeletal distortion protection module is responsible for monitoring the skeletal state of the character to prevent the virtual character's bones from being twisted or deformed in extreme movement situations; the skeletal distortion protection module protects the skeletal structure of the virtual character, and the virtual-real time correction module accurately synchronizes the time nodes of the user's movements with the movement time of the virtual character on this basis; after the virtual-real time correction module synchronizes the user's movement time with the virtual character, the multi-branch skeletal smoothness optimization module further optimizes the movement smoothness in the multi-branch skeletal system to ensure that the movement is transmitted naturally and smoothly between different joints and bones.

[0016] The present invention is further configured as follows: the sensor management module is responsible for managing and calibrating the motion capture sensor to ensure that the sensor can accurately obtain the user's motion data and transmit these data to the biometric capture module to collect the user's biometric information through body tracking, eye tracking and facial expression capture; after the biometric capture module collects the user's biometric information, it is integrated with the spatial position and environmental information collected by the environmental data acquisition module to ensure that the physical properties in the virtual environment match the reality; the spatial and environmental information collected by the environmental data acquisition module is further transmitted to the high-precision tracking module to capture the user's tiny movements using multi-point calibration and precise positioning systems to improve the precision of motion capture; the fine motion data captured by the high-precision tracking module is then processed and filtered in real time by the dynamic data filtering module to eliminate noise and ensure that the system obtains high-quality input data.

[0017] The present invention is further configured as follows: the data processed by the dynamic data filtering module is sent to the action recognition algorithm module, which converts complex action signals into system-recognizable behaviors through a deep learning algorithm to form clear action features; the action recognition algorithm module transmits the identified action features to the data flow optimization module for compression, denoising and data completion; the data optimized by the data flow optimization module is input into the skeleton mapping conversion module to map the user's actual actions to the virtual skeleton model to achieve accurate action correspondence; after the skeleton mapping conversion module completes the skeleton mapping, the physical attribute matching module adjusts the character's physical feedback according to the user's posture and movement state to ensure that the character's movement performance conforms to the user's actual situation; the data adjusted by the physical attribute matching module enters the real-time data buffer module to set up a buffer to handle delays so that the data can transition smoothly before reaching rendering and reduce jitter.

[0018] The present invention is further configured as follows: the picture and action information generated by the real-time rendering engine module are transmitted to the tactile feedback module to convey the virtual physical feedback to the user through the tactile vest and glove equipment; the tactile signal and action information triggered by the tactile feedback module simultaneously enter the sound effect feedback generation module to generate environmental sound effects matching the action events; the sound effects and action data generated by the sound effect feedback generation module are transmitted to the environment interaction rendering module to adjust the position, state and reaction of the virtual object according to the user action; the final data output by the environment interaction rendering module enters the visual synchronization optimization module to eliminate dynamic blur and visual delay through multi-level rendering so that the picture is accurately synchronized with the actual action.

[0019] The present invention is further configured as follows: the recorded data of the action recording and playback module is transmitted to the big data analysis module to mine the user's behavioral habits through machine learning and optimize the personalized settings of the system; the information analyzed by the big data analysis module enters the adaptive learning module to adaptively adjust the capture parameters and feedback strategies by continuously learning the user's habits; the data optimized by the adaptive learning module is transmitted to the cloud storage and backup module for cloud backup of user data and synchronization between devices; the storage data of the cloud storage and backup module is encrypted and privacy protected by the data privacy protection module to ensure the security of the user's personal data during storage and transmission.

[0020] The beneficial effects of the present invention are:

[0021] 1. The present invention realizes accurate capture and real-time feedback of user actions through the collaborative work of modules such as data acquisition, data processing, rendering and feedback, ensuring that the physical properties of the virtual environment are highly consistent with those of the real environment. The data acquisition module can obtain multi-dimensional information such as the user's body sensation, expression, environment, etc. with high precision. The data processing module accurately identifies and optimizes user actions through deep learning algorithms and bone mapping technology. The rendering and feedback module generates realistic visual, tactile and sound feedback, bringing a highly immersive experience and ensuring the smoothness and consistency of actions and feedback.

[0022] 2. The present invention further improves the capture accuracy and detail expression through the bone mapping conversion module. It can not only determine and adjust the distribution and position accuracy of the capture points, but also adaptively adjust the user's bone proportions to ensure that the virtual character's movements are consistent with the user's real movements. Through micro-motion compensation and distortion protection functions, the module can amplify subtle movements and prevent virtual bone abnormalities caused by extreme movements, thereby enhancing the naturalness of the virtual character. The virtual-real time correction and multi-branch bone smoothness optimization module ensures the continuity of multi-joint movements, making the virtual character's movements more realistic and smooth. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a schematic diagram of the system modules in the present invention.

[0024] Figure 2 It is a partial system diagram of the skeleton mapping conversion module in the present invention. DETAILED DESCRIPTION

[0025] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0026] Example 1

[0027] like Figure 1 As shown, an animation motion capture device for virtual reality technology includes a data acquisition module for capturing and collecting user motion and environmental information, a data processing module for analyzing, converting and optimizing the collected data, a rendering and feedback module for converting the processed data into visual and tactile feedback, and a data storage and analysis module for storing, analyzing and optimizing data;

[0028] The data acquisition module includes a sensor management module for managing motion capture sensors, a biometric capture module for collecting user biometric information through body tracking, eye tracking and facial expression capture, an environmental data acquisition module for collecting spatial position and ambient lighting information to ensure that the physical properties of the virtual environment match the real one, a high-precision tracking module for capturing tiny movements using multi-point calibration and an accurate positioning system, and a dynamic data filtering module for real-time processing and filtering of the collected data to eliminate noise;

[0029] The data processing module includes an action recognition algorithm module for converting complex action signals into system-recognizable behaviors based on a deep learning action recognition algorithm, a data stream optimization module for compressing, denoising and completing the collected raw data, a bone mapping conversion module for mapping the user's actual actions to a virtual bone model, a physical attribute matching module for adjusting the character's physical feedback according to the user's posture and motion state, and a real-time data buffer module for setting up a buffer to handle delays and smoothly transition before data arrives for rendering;

[0030] The rendering and feedback module includes a real-time rendering engine module for real-time rendering of the dynamic performance of the virtual character through GPU acceleration, a tactile feedback module for conveying physical feedback in the virtual world to the user using a tactile vest and glove equipment, a sound effect feedback generation module for generating matching environmental sound effects for action events, an environmental interaction rendering module for adjusting the position, state and reaction of objects in the virtual space according to user actions, and a visual synchronization optimization module for eliminating dynamic blur and visual delay through multi-level rendering;

[0031] The data storage and analysis module includes an action recording and playback module for storing all action data of the user, a big data analysis module for mining user habits through machine learning based on user action data, an adaptive learning module for adaptively adjusting capture parameters and feedback strategies by continuously analyzing user habits, a cloud storage and backup module for backing up data in the cloud and supporting data synchronization of different devices, and a data privacy protection module for applying encryption technology to ensure the security of user personal data;

[0032] The sensor management module is responsible for managing and calibrating the motion capture sensor to ensure that the sensor can accurately obtain the user's motion data and pass this data to the biometric capture module to collect the user's biometric information through body tracking, eye tracking and facial expression capture; after collecting the user's biometric information, the biometric capture module integrates it with the spatial position and environmental information collected by the environmental data acquisition module to ensure that the physical properties in the virtual environment match the reality; the spatial and environmental information collected by the environmental data acquisition module is further passed to the high-precision tracking module to capture the user's tiny movements using multi-point calibration and precise positioning systems to improve the precision of motion capture; the fine motion data captured by the high-precision tracking module is then processed and filtered in real time by the dynamic data filtering module to eliminate noise and ensure that the system obtains high-quality input data;

[0033] The data processed by the dynamic data filtering module is sent to the action recognition algorithm module, which converts complex action signals into system-recognizable behaviors through a deep learning algorithm to form clear action features; the action recognition algorithm module passes the recognized action features to the data flow optimization module for compression, denoising and data completion; the data optimized by the data flow optimization module is input to the skeleton mapping conversion module to map the user's actual actions to the virtual skeleton model to achieve accurate action correspondence; after the skeleton mapping conversion module completes the skeleton mapping, the physical attribute matching module adjusts the character's physical feedback according to the user's posture and movement state to ensure that the character's movement performance conforms to the user's actual situation; the data adjusted by the physical attribute matching module enters the real-time data buffer module to set up a buffer to handle delays so that the data can transition smoothly before reaching the rendering to reduce jitter;

[0034] The picture and action information generated by the real-time rendering engine module are transmitted to the tactile feedback module to convey the virtual physical feedback to the user through the tactile vest and glove equipment; the tactile signal and action information triggered by the tactile feedback module simultaneously enter the sound effect feedback generation module to generate environmental sound effects that match the action events; the sound effects and action data generated by the sound effect feedback generation module are transmitted to the environment interaction rendering module to adjust the position, state and reaction of the virtual object according to the user action; the final data output by the environment interaction rendering module enters the visual synchronization optimization module to eliminate dynamic blur and visual delay through multi-level rendering to make the picture and the actual action accurately synchronized;

[0035] The recorded data of the action recording and playback module is transmitted to the big data analysis module to mine the user's behavioral habits through machine learning and optimize the personalized settings of the system; the information analyzed by the big data analysis module enters the adaptive learning module to adaptively adjust the capture parameters and feedback strategies by continuously learning the user's habits; the data optimized by the adaptive learning module is transmitted to the cloud storage and backup module for cloud backup of user data and synchronization between devices; the storage data of the cloud storage and backup module is encrypted and privacy protected by the data privacy protection module to ensure the security of the user's personal data during storage and transmission.

[0036] In the above embodiments, the data acquisition module collects the user's body sensation, biometrics and environmental information through sub-modules such as sensor management and high-precision tracking to ensure high data quality. The data processing module uses motion recognition algorithms to convert motion signals into system behaviors, optimizes and maps them to virtual skeleton models, and ensures accurate restoration of user movements. The rendering and feedback module generates visual and tactile feedback through a real-time rendering engine and tactile feedback devices, allowing users to obtain a synchronized and realistic immersive experience. The data storage and analysis module records, analyzes and stores user data in the cloud, continuously optimizes the system's personalized settings in combination with its own adaptive learning module, and ensures information security through data privacy protection.

[0037] Example 2

[0038] like Figure 1-2 As shown, an animation motion capture device for virtual reality technology, the skeleton mapping conversion module includes a motion capture point distribution determination module for determining whether the actual motion capture points of the user are evenly distributed on the joints and bones, a skeleton position re-screening module for cleaning and re-tableating punctuation data for unqualified skeleton points, a skeleton position accuracy determination module for determining the accuracy of the skeleton position through real-time monitoring and calibration algorithms, a skeleton position accuracy fine-tuning module for manually fine-tuning the skeleton point data with slightly deviated skeleton position accuracy, a joint angle dynamic adjustment module for real-time dynamic adjustment of the user's joint angle, a skeleton proportion adaptive adjustment module for adaptively adjusting the virtual skeleton model according to the user's skeleton proportion, a micro-motion compensation module for capturing the user's subtle movements when stationary or slightly moving, amplifying them and compensating them to the skeleton of the virtual character, a skeleton distortion protection module for preventing the skeleton of the virtual character from being distorted or deformed due to exceeding the normal range in extreme motion situations, a virtual-real time correction module for synchronizing the time node of the user's action with the action time of the virtual character, and a multi-branch skeleton smoothness optimization module for processing the motion smoothness problem in a complex multi-branch skeleton system to ensure smooth motion transmission between multiple joints and bones without motion stiffness or fracture;

[0039] The motion capture point distribution determination module first detects whether the distribution of the user's motion capture points on the joints and bones is uniform. If it is determined to be uneven, the bone position re-screening module will clean and re-screen these unqualified capture points; after the bone position re-screening module completes the screening, it will pass the qualified data to the bone position accuracy determination module, which determines the accuracy of these capture points through real-time monitoring and calibration algorithms; when the bone position accuracy determination module finds that the accuracy of some capture points is slightly deviated, it will hand these points over to the bone position accuracy fine-tuning module for manual fine-tuning;

[0040] The bone position precision fine-tuning module fine-tunes the bone point data with a slight position deviation and then transmits the fine-tuned data to the joint angle dynamic adjustment module, which dynamically adjusts the user's joint angle according to the adjusted bone position so that the joint angle of the virtual character is consistent with the user's actual action; the joint angle dynamic adjustment module ensures the consistency of the joint angle, and then the bone proportion adaptive adjustment module adaptively adjusts the bone model of the virtual character according to the user's bone proportion to match the user's body shape characteristics;

[0041] After the skeleton proportion adaptive adjustment module completes the adaptation of skeleton proportions, the micro-motion compensation module starts to work to capture the user's subtle movements when still or slightly moving, and amplifies these tiny movements and maps them to the virtual character; after the micro-motion compensation module maps the subtle movements to the virtual character, the skeleton distortion protection module is responsible for monitoring the skeleton state of the character to prevent the skeleton of the virtual character from being twisted or deformed in extreme movement conditions; the skeleton distortion protection module protects the skeleton structure of the virtual character, and the virtual-real time correction module accurately synchronizes the time nodes of the user's movements with the movement time of the virtual character on this basis; after the virtual-real time correction module synchronizes the user's movement time with the virtual character, the multi-branch skeleton smoothness optimization module further optimizes the movement smoothness in the multi-branch skeleton system to ensure the natural and smooth transmission of movements between different joints and bones.

[0042] In the above embodiment, the motion capture point distribution determination module checks the uniformity of the capture points on the joints and bones, and unqualified data is cleaned and screened by the bone position re-screening module. Then, the bone position accuracy determination module ensures the accuracy of the capture points, and if there is a deviation, the bone position accuracy fine-tuning module performs fine-tuning. Next, the joint angle dynamic adjustment module adjusts the virtual character joint angles, and the bone proportion adaptive adjustment module adaptively adjusts the bone structure of the virtual character according to the user's bone proportion. The system also captures subtle movements through the micro-motion compensation module, and the bone distortion protection module prevents bone distortion caused by extreme movements. Finally, the virtual-real time correction module synchronizes the user and virtual character action time, and the multi-branch bone smoothness optimization module ensures that the movements between multiple joints are natural and smooth.

[0043] Working principle: When the present invention is in use, the data acquisition module collects the user's movements and environmental information in real time through sub-modules such as sensor management and biometric capture. The environmental data acquisition module records the spatial position and lighting information to ensure that the virtual environment is consistent with the real environment; the high-precision tracking module uses the positioning system to capture the user's tiny movements; the dynamic data filtering module filters the collected data in real time to eliminate noise and ensure the clarity and accuracy of the data.

[0044] Next, the data processing module converts complex motion signals into system-recognizable behaviors through deep learning motion recognition algorithms, optimizes and compresses data streams, and maps the user's actual movements to the virtual skeleton model. The skeleton mapping conversion module first determines whether the distribution of capture points is uniform, then cleans and screens unqualified points, and then adjusts the bone position and joint angle through the accuracy judgment and fine-tuning module. The bone proportion adaptive adjustment module adjusts the bone structure of the virtual character according to the user's body shape. The micro-motion compensation module amplifies and compensates for the user's subtle movements, and the bone distortion protection module prevents abnormal distortion of the virtual skeleton caused by extreme movements, ensuring that the time nodes of the user's movements are synchronized with the virtual character. At the same time, the multi-branch bone smoothness optimization module ensures the natural smoothness of multi-joint movements.

[0045] Finally, the rendering and feedback module converts the processed data into visual and tactile feedback. The real-time rendering engine module uses GPU acceleration to dynamically render the virtual character, and the tactile feedback module provides tactile feedback through vests and gloves. The sound feedback generation module generates environmental sound effects based on action events, and the environmental interaction rendering module adjusts the state of virtual objects based on user actions. The visual synchronization optimization module eliminates blur and delay through multi-level rendering, ensuring that the visual effects are synchronized with user actions and enhancing the immersive experience.

[0046] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An animation motion capture device for virtual reality technology, characterized in that: It includes a data acquisition module for capturing and collecting user actions and environmental information, a data processing module for analyzing, converting and optimizing the collected data, a rendering and feedback module for converting the processed data into visual and tactile feedback, and a data storage and analysis module for storing, analyzing and optimizing data; The data acquisition module includes a sensor management module for managing motion capture sensors, a biometric capture module for collecting user biometric information through body tracking, eye tracking and facial expression capture, an environmental data acquisition module for collecting spatial position and ambient lighting information to ensure that the physical properties of the virtual environment match the real one, a high-precision tracking module for capturing tiny movements using multi-point calibration and an accurate positioning system, and a dynamic data filtering module for real-time processing and filtering of the collected data to eliminate noise; The data processing module includes an action recognition algorithm module based on deep learning that can convert complex action signals into system-recognizable behaviors, a data stream optimization module for compressing, denoising and completing the collected raw data, a bone mapping conversion module for mapping the user's actual actions to a virtual bone model, a physical attribute matching module for adjusting the character's physical feedback according to the user's posture and movement state, and a real-time data buffer module for setting up a buffer to handle delays and smoothly transition before data arrives for rendering.

2. The animation motion capture device for virtual reality technology according to claim 1, characterized in that: The rendering and feedback module includes a real-time rendering engine module for real-time rendering of the dynamic performance of the virtual character through GPU acceleration, a tactile feedback module for conveying physical feedback in the virtual world to the user using a tactile vest and glove equipment, a sound effect feedback generation module for generating matching environmental sound effects for action events, an environmental interaction rendering module for adjusting the position, state and reaction of objects in the virtual space according to user actions, and a visual synchronization optimization module for eliminating dynamic blur and visual delay through multi-level rendering; The data storage and analysis module includes an action recording and playback module for storing all user action data, a big data analysis module for mining user habits through machine learning based on user action data, an adaptive learning module for adaptively adjusting capture parameters and feedback strategies by continuously analyzing user habits, a cloud storage and backup module for backing up data in the cloud and supporting data synchronization of different devices, and a data privacy protection module for applying encryption technology to ensure the security of user personal data.

3. The animation motion capture device for virtual reality technology according to claim 1, characterized in that: The skeleton mapping conversion module includes a motion capture point distribution determination module for determining whether the actual motion capture points of the user are evenly distributed on the joints and bones, a skeleton position re-screening module for cleaning and re-tableating punctuation data for unqualified skeleton points, a skeleton position accuracy determination module for determining the accuracy of skeleton positions through real-time monitoring and calibration algorithms, a skeleton position accuracy fine-tuning module for manually fine-tuning skeleton point data with slightly deviated skeleton position accuracy, a joint angle dynamic adjustment module for real-time dynamic adjustment of the user's joint angles, a skeleton proportion adaptive adjustment module for adaptively adjusting the virtual skeleton model according to the user's skeleton proportions, a micro-motion compensation module for capturing the user's subtle movements when stationary or slightly moving, amplifying them and compensating them to the skeleton of the virtual character, a skeleton distortion protection module for preventing the skeleton of the virtual character from being distorted or deformed due to exceeding the normal range in extreme motion situations, a virtual-real time correction module for synchronizing the time nodes of the user's movements with the action time of the virtual character, and a multi-branch skeleton smoothness optimization module for handling the problem of motion smoothness in a complex multi-branch skeleton system to ensure smooth motion transmission between multiple joints and bones without motion stiffness or breakage.

4. The animation motion capture device for virtual reality technology according to claim 3, characterized in that: The motion capture point distribution determination module first detects whether the distribution of the user's motion capture points on the joints and bones is uniform. If it is determined to be uneven, the bone position re-screening module will clean and re-screen these unqualified capture points; after completing the screening, the bone position re-screening module will pass the qualified data to the bone position accuracy determination module, which determines the accuracy of these capture points through real-time monitoring and calibration algorithms; when the bone position accuracy determination module finds that the accuracy of some capture points is slightly deviated, it will hand these points over to the bone position accuracy fine-tuning module for manual fine-tuning.

5. The animation motion capture device for virtual reality technology according to claim 4, characterized in that: The bone position accuracy fine-tuning module fine-tunes the bone point data with slight position deviations and then passes the fine-tuned data to the joint angle dynamic adjustment module, which dynamically adjusts the user's joint angle according to the adjusted bone position to make the joint angle of the virtual character consistent with the user's actual movements; the joint angle dynamic adjustment module ensures the consistency of the joint angles, and then the bone proportion adaptive adjustment module adaptively adjusts the bone model of the virtual character according to the user's bone proportions to match the user's body shape characteristics.

6. The animation motion capture device for virtual reality technology according to claim 5, characterized in that: After the skeleton proportion adaptive adjustment module completes the adaptation of skeleton proportions, the micro-motion compensation module starts to work to capture the user's subtle movements when still or slightly moving, and amplifies these tiny movements and maps them to the virtual character; after the micro-motion compensation module maps the subtle movements to the virtual character, the skeleton distortion protection module is responsible for monitoring the skeleton state of the character to prevent the skeleton of the virtual character from being twisted or deformed in extreme movement conditions; the skeleton distortion protection module protects the skeleton joints of the virtual character, and the virtual-real time correction module accurately synchronizes the time nodes of the user's movements with the movement time of the virtual character on this basis; after the virtual-real time correction module synchronizes the user's movement time with the virtual character, the multi-branch skeleton smoothness optimization module further optimizes the movement smoothness in the multi-branch skeleton system to ensure the natural and smooth transmission of movements between different joints and bones.

7. The animation motion capture device for virtual reality technology according to claim 1, characterized in that: The sensor management module is responsible for managing and calibrating the motion capture sensors to ensure that the sensors can accurately obtain the user's motion data and pass these data to the biometric capture module to collect the user's biometric information through body tracking, eye tracking and facial expression capture; after collecting the user's biometric information, the biometric capture module integrates it with the spatial position and environmental information collected by the environmental data acquisition module to ensure that the physical properties in the virtual environment match the reality; the spatial and environmental information collected by the environmental data acquisition module is further passed to the high-precision tracking module to capture the user's tiny movements using multi-point calibration and precise positioning systems to improve the precision of motion capture; the fine motion data captured by the high-precision tracking module is then processed and filtered in real time by the dynamic data filtering module to eliminate noise and ensure that the system obtains high-quality input data.

8. The animation motion capture device for virtual reality technology according to claim 1, characterized in that: The data processed by the dynamic data filtering module is sent to the action recognition algorithm module, which converts complex action signals into system-recognizable behaviors through a deep learning algorithm to form clear action features; the action recognition algorithm module passes the recognized action features to the data flow optimization module for compression, denoising and data completion; the data optimized by the data flow optimization module is input into the skeleton mapping conversion module to map the user's actual actions to the virtual skeleton model to achieve accurate action correspondence; after the skeleton mapping conversion module completes the skeleton mapping, the physical property matching module adjusts the character's physical feedback according to the user's posture and movement state to ensure that the character's movement performance conforms to the user's actual situation; the data adjusted by the physical property matching module enters the real-time data buffer module to set up a buffer to handle delays so that the data can transition smoothly before reaching rendering and reduce jitter.

9. The animation motion capture device for virtual reality technology according to claim 2, characterized in that: The picture and action information generated by the real-time rendering engine module are transmitted to the tactile feedback module to convey the virtual physical feedback to the user through the tactile vest and glove devices; the tactile signal and action information triggered by the tactile feedback module simultaneously enter the sound effect feedback generation module to generate environmental sound effects that match the action events; the sound effects and action data generated by the sound effect feedback generation module are transmitted to the environment interaction rendering module to adjust the position, state and reaction of the virtual object according to the user's action; the final data output by the environment interaction rendering module enters the visual synchronization optimization module to eliminate dynamic blur and visual delay through multi-level rendering to ensure accurate synchronization of the picture with the actual action.

10. The animation motion capture device for virtual reality technology according to claim 2, characterized in that: The recorded data of the action recording and playback module is transmitted to the big data analysis module to mine the user's behavioral habits through machine learning and optimize the personalized settings of the system; the information analyzed by the big data analysis module enters the adaptive learning module to adaptively adjust the capture parameters and feedback strategies by continuously learning the user's habits; the data optimized by the adaptive learning module is transmitted to the cloud storage and backup module for cloud backup of user data and synchronization between devices; the storage data of the cloud storage and backup module is encrypted and privacy protected by the data privacy protection module to ensure the security of the user's personal data during storage and transmission.

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