[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Chen, 2024 - Google Patents

3D Convolutional Neural Networks based Movement Evaluation System for Gymnasts in Computer Vision Applications

Chen, 2024

Document ID
9282384493079621644
Author
Chen Y
Publication year
Publication venue
Journal of Electrical Systems

External Links

Snippet

This study introduces an innovative Movement Evaluation System, which utilizes state of art 3D CNNs in grassland of computer vision. This system presents a significant advancement in analyzing and assessing complex gymnastic movements, providing a comprehensive …
Continue reading at search.proquest.com (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
    • G06K9/00268—Feature extraction; Face representation
    • G06K9/00281—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B24/00—Electric or electronic controls for exercising apparatus of preceding groups; Controlling or monitoring of exercises, sportive games, training or athletic performances
    • A63B24/0003—Analysing the course of a movement or motion sequences during an exercise or trainings sequence, e.g. swing for golf or tennis
    • A63B24/0006—Computerised comparison for qualitative assessment of motion sequences or the course of a movement
    • A63B2024/0012—Comparing movements or motion sequences with a registered reference
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00335—Recognising movements or behaviour, e.g. recognition of gestures, dynamic facial expressions; Lip-reading
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34—Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/011—Arrangements for interaction with the human body, e.g. for user immersion in virtual reality

Similar Documents

Publication Publication Date Title
Garg et al. Yoga pose classification: a CNN and MediaPipe inspired deep learning approach for real-world application
Yadav et al. Real-time Yoga recognition using deep learning
Avola et al. An interactive and low-cost full body rehabilitation framework based on 3D immersive serious games
Brooks et al. Quantifying upper‐arm rehabilitation metrics for children through interaction with a humanoid robot
CN110490109A (en) A kind of online human body recovery action identification method based on monocular vision
CN115311737A (en) Method for recognizing hand motion of non-aware stroke patient based on deep learning
Cui et al. Deep learning based advanced spatio-temporal extraction model in medical sports rehabilitation for motion analysis and data processing
Mohammed et al. Recognition of yoga asana from real-time videos using blaze-pose
Zhen et al. Hybrid Deep‐Learning Framework Based on Gaussian Fusion of Multiple Spatiotemporal Networks for Walking Gait Phase Recognition
US20240070854A1 (en) Tracking, analysing and assessment of huamn body movements using a subject-specific digital twin model of the human body
Molavian et al. Artificial intelligence approach in biomechanics of gait and sport: a systematic literature review
Shah et al. An efficient and lightweight multiperson activity recognition framework for robot-assisted healthcare applications
Jadhav et al. Aasna: Kinematic Yoga Posture Detection And Correction System Using CNN
Portaz et al. Exploring raw data transformations on inertial sensor data to model user expertise when learning psychomotor skills
Chen 3D Convolutional Neural Networks based Movement Evaluation System for Gymnasts in Computer Vision Applications
Acı et al. Accuracy Detection in Some Sports Training Using Computer Vision and Deep Learning Techniques
Bhambure et al. YOG-assist
Zielinski Live Perception and Real Time Motion Prediction with Deep Neural Networks and Machine Learning
Hoang et al. Poses classification in a Taekwondo lesson using skeleton data extracted from videos with shallow and deep learning architectures
Vyas Pose estimation and action recognition in sports and fitness
Chen An interpretable composite CNN and GRU for fine-grained martial arts motion modeling using big data analytics and machine learning
Luo et al. Basketball Free Throw Posture Analysis and Hit Probability Prediction System Based on Deep Learning.
Saurav et al. Exploration of deep learning architectures for real-time yoga pose recognition
Kumar et al. Yoga Asanas Pose Detection using Feature Level Fusion with Deep Learning-Based Model
Torres et al. Detection of proper form on upper limb strength training using extremely randomized trees for joint positions