Title :
Partly-hidden Markov model and its application to gesture recognition
Author :
Kobayashi, Tetsunori ; Haruyama, Satoshi
Author_Institution :
Dept. of Electr. Eng., Waseda Univ., Tokyo, Japan
Abstract :
A new pattern matching method, the partly-hidden Markov model, is proposed for gesture recognition. The hidden Markov model, which is widely used for the time series pattern recognition, can deal with only piecewise stationary stochastic process. We solved this problem by introducing the modified second order Markov model, in which the first state is hidden and the second one is observable. As shown by the results of 6 sign-language recognition test, the error rate was improved by 73% compared with normal HMM
Keywords :
feature extraction; hidden Markov models; image recognition; motion estimation; pattern matching; time series; HMM; error rate; gesture recognition; hidden Markov model; modified second order Markov model; partly hidden Markov model; pattern matching method; piecewise stationary stochastic process; sign-language recognition test; time series pattern recognition; Error analysis; Hidden Markov models; Image processing; Image recognition; Pattern matching; Pattern recognition; Read only memory; Speech recognition; Stochastic processes; Testing;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on
Conference_Location :
Munich
Print_ISBN :
0-8186-7919-0
DOI :
10.1109/ICASSP.1997.595443
