HMMs are often used for gesture recognition because of the robustness. However, the computational cost and accuracy of recognition are important for real applications such as gesture recognition, speech recognition or virtual reality. In this paper, we propose methods for performance improvement of gesture recognition using HMMs. For the computational cost, we use KL transform to compress the input information and propose a recursive calculation method for the HMMs' probabilities. For the accuracy of recognition, we use an automaton layered up on HMMs to deal with context information of gestures. We also show experimental results to make the efficiency of our methods clear.
Real-time context-based gesture recognition using HMM and automaton
1999-01-01
967356 byte
Conference paper
Electronic Resource
English
3-D Real-Time Gesture Recognition Using Proximity Spaces
British Library Conference Proceedings | 1996
|3-D real-time gesture recognition using proximity spaces
IEEE | 1996
|Real-time gesture recognition system and application
British Library Online Contents | 2002
|