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
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
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
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Hand gestures have been widely applied to interface as the way of interaction between human and computers. Since a human hand can express various shapes of gestures, previous models for recognizing them cannot distinguish them accurately since they use only single model for recognition. For efficient hand gesture recognition with its enhanced performance, we propose the fuzzy c-means clustering based mixture-of-experts (FME). The proposed method uses multiple local experts obtained via fuzzy c-means clustering and decisions from them are combined with the gating network. To evaluate the performance of the proposed method, we conduct experiments including comparisons with alternative models for hand gesture recognition. As the result of experiments, the proposed model shows improved gesture recognition performance, especially performance on similar hand gesture recognition.