Lua—an extensible extension language
Software—Practice & Experience
Cyber Composer: Hand Gesture-Driven Intelligent Music Composition and Generation
MMM '05 Proceedings of the 11th International Multimedia Modelling Conference
Intelligent Interactive Entertainment Grand Challenges
IEEE Intelligent Systems
Robotics and Autonomous Systems
Wavelet/mixture of experts network structure for EEG signals classification
Expert Systems with Applications: An International Journal
Glove-Based Approach to Online Signature Verification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hand gesture recognition and tracking based on distributed locally linear embedding
Image and Vision Computing
Taiwan sign language (TSL) recognition based on 3D data and neural networks
Expert Systems with Applications: An International Journal
WAVE: Sound and music in an immersive environment
Computers and Graphics
User-adaptive hand gesture recognition system with interactive training
Image and Vision Computing
ConaMSN: A context-aware messenger using dynamic Bayesian networks with wearable sensors
Expert Systems with Applications: An International Journal
Adaptive motion-based gesture recognition interface for mobile phones
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
A person independent system for recognition of hand postures used in sign language
Pattern Recognition Letters
A Survey of Glove-Based Systems and Their Applications
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
IEEE Transactions on Neural Networks
Investigation of mixture of experts applied to residential premises valuation
ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems - Volume Part II
Hi-index | 12.05 |
Hand gestures have great potential to act as a computer interface in the entertainment environment. However, there are two major problems when implementing the hand gesture-based interface for multiple users, the complexity problem and the personalization problem. In order to solve these problems and implement multi-user data glove interface successfully, we propose an adaptive mixture-of-experts model for data-glove based hand gesture recognition models which can solve both the problems. The proposed model consists of the mixture-of-experts used to recognize the gestures of an individual user, and a teacher network trained with the gesture data from multiple users. The mixture-of-experts model is trained with an expectation-maximization (EM) algorithm and an on-line learning rule. The model parameters are adjusted based on the feedback received from the real-time recognition of the teacher network. The model is applied to a musical performance game with the data glove (5DT Inc.) as a practical example. Comparison experiments using several representative classifiers showed both outstanding performance and adaptability of the proposed method. Usability assessment completed by the users while playing the musical performance game revealed the usefulness of the data glove interface system with the proposed method.