The temporal relationship between local spatio-temporal motion patterns is captured via a distribution-based Hidden Markov Model (HMM
) and the spatial relationship by a coupled HMM
The Hidden Markov Model (HMM
) is the most common and successful approach for isolated voice commands recognition today.
We applied Baum-Welch algorithm for the training of HMMs
for all classes.
The emission probability matrices for the first-order and second-order HMMs
are shown as follows:
Fridman demonstrated that visual behavior could be used to predict driving environment using HMM
from just 6 seconds with the 100-car naturalistic driving data .
These features are statistically modeled using the Bayesian network, CRFs, and HMMs
. Thirty cataract surgery videos are used for the testing purpose having 720 x 576 pixels.
As previously noted, of the two most popular families of stochastic taggers, HMMs
and MaxEnt, the former has a longer history in its application to natural language processing.
Offline recognition of unconstrained handwritten texts using hmms
and statistical language models.
The future is to learn the operator's motion patterns, derive hidden Markov models (HMMs
) from the patterns, and then use the HMMs
to estimate future operator positions .