Nothing Special   »   [go: up one dir, main page]

Chambers et al., 2002 - Google Patents

Hierarchical recognition of intentional human gestures for sports video annotation

Chambers et al., 2002

View PDF
Document ID
16640517743591702960
Author
Chambers G
Venkatesh S
West G
Bui H
Publication year
Publication venue
2002 International Conference on Pattern Recognition

External Links

Snippet

We present a novel technique for the recognition of complex human gestures for video annotation using accelerometers and the hidden Markov model. Our extension to the standard hidden Markov model allows us to consider gestures at different levels of …
Continue reading at dro.deakin.edu.au (PDF) (other versions)

Classifications

    • 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
    • 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
    • G06F3/03—Arrangements for converting the position or the displacement of a member into a coded form
    • G06F3/033—Pointing devices displaced or positioned by the user, e.g. mice, trackballs, pens or joysticks; Accessories therefor
    • 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
    • G06F3/017—Gesture based interaction, e.g. based on a set of recognized hand gestures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50—Computer-aided design
    • G06F17/5009—Computer-aided design using simulation
    • 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
    • G06K9/62—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
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F2203/00—Indexing scheme relating to G06F3/00 - G06F3/048
    • 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

Similar Documents

Publication Publication Date Title
Chambers et al. Hierarchical recognition of intentional human gestures for sports video annotation
Tu et al. Joint-bone fusion graph convolutional network for semi-supervised skeleton action recognition
Watson A survey of gesture recognition techniques
Oz et al. American sign language word recognition with a sensory glove using artificial neural networks
Alrubayi et al. A pattern recognition model for static gestures in malaysian sign language based on machine learning techniques
Areeb et al. Helping hearing-impaired in emergency situations: A deep learning-based approach
Wu et al. A Visual-Based Gesture Prediction Framework Applied in Social Robots.
dos Santos Anjo et al. A real-time system to recognize static gestures of Brazilian sign language (libras) alphabet using Kinect.
Adhikari et al. A Novel Machine Learning-Based Hand Gesture Recognition Using HCI on IoT Assisted Cloud Platform.
Xu et al. A long term memory recognition framework on multi-complexity motion gestures
Loeding et al. Progress in automated computer recognition of sign language
Prikhodko et al. Sign language recognition based on notations and neural networks
Swee et al. Malay sign language gesture recognition system
CN113743247A (en) Gesture recognition method based on Reders model
Gavrilescu Recognizing human gestures in videos by modeling the mutual context of body position and hands movement
Chambers et al. Hierarchical recognition of intentional human gestures for sports video
Moustafa et al. Arabic Sign Language Recognition Systems: A Systematic Review
Gibet et al. Corpus of 3D natural movements and sign language primitives of movement
CN113807280A (en) Kinect-based virtual ship cabin system and method
Dawod Hand Gesture Recognition Based Sign Language Interpretation in Real-Time
Watson A survey of gesture recognition techniques technical report tcd-cs-93-11
Tolba et al. Arabic glove-talk (AGT): A communication aid for vocally impaired
Giao et al. Hidden Markov Model for recognition of skeletal databased hand movement gestures
Sriharsha et al. An Adaptive Learning Method for Sign Language Detection
Hyder et al. An adavanced Gesture Recognition Using Machine Learning