DocumentCode :
3249209
Title :
Real-time context-based gesture recognition using HMM and automaton
Author :
Iwai, Yoshio ; Shimizu, Hiroaki ; Yachida, And Masahiko
Author_Institution :
Dept. of Syst. & Human Sci., Osaka Univ., Japan
fYear :
1999
fDate :
1999
Firstpage :
127
Lastpage :
134
Abstract :
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
Keywords :
automata theory; gesture recognition; hidden Markov models; speech recognition; virtual reality; automaton; hidden Markov models; performance improvement; real-time context-based gesture recognition; speech recognition; virtual reality; Automata; Computational efficiency; Face recognition; Hidden Markov models; Humans; Image recognition; Karhunen-Loeve transforms; Magnetic sensors; Probability; Speech recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems, 1999. Proceedings. International Workshop on
Conference_Location :
Corfu
Print_ISBN :
0-7695-0378-0
Type :
conf
DOI :
10.1109/RATFG.1999.799235
Filename :
799235
Link To Document :
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