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In this paper, details are furnished with the method of sign language recognition based on hidden Markov model (HMM). It is aimed that the richer transitional topology of model would be better at accounting for motion variation modeling. In this paper, we describe a method of constructing various types of transitional topology of HMM by sharing common segments over the several sequences of sign. Thus...
Japan is one of the countries where a lot of earthquakes occur. Therefore it is very important to catch the portent of earthquakes. Anomalous environmental electromagnetic (EM) radiation waves have been reported as the portent of earthquakes. Therefore in order to detect the anomalous EM waves we propose a method for detecting anomalous EM waves based on its daily average using HMM. Experimental results...
In this paper, we propose separable lattice hidden Markov models, in which multiple hidden state sequences interact to model the observation on a lattice. The proposed model can be efficiently applied for modeling images, image sequences, 3-D object models and higher dimensional applications, due to the composite structure of Markov chains which reduces the complexity while retaining good properties...
In the present paper, the Monte Carlo EM (MCEM) algorithm with a Gibbs sampler is applied for estimating parameters of a trajectory HMM, which has been derived from an HMM by imposing explicit relationships between static and dynamic features. The trajectory HMM can alleviate two limitations of the HMM, which are i) constant statistics within a state, and ii) conditional independence of state output...
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