GSoC Accelerometer-based Gestures Update 3

[Paul-Valentin Borza]

I've re-implemented hidden Markov Models. The evaluation algorithm
Viterbi that decodes the observation sequence works perfectly.
I've made a terrible mistake by using floats instead of doubles (I've
used doubles on Windows) and even with scaling, to prevent underflow,
underflow still happens.
Viterbi uses float representations and logarithms and doesn't need
scaling as underflow doesn't happen.
Underflow happens only at the training of the gestures and I'll have
to change the types to double.
I've tried a different approach when I created four models, than the
one I had on Windows, where each model used 27 states.
The Spoken Language Processing books says that it's a better to have
the number of states dependent of the model (on how compex the model
gets).
I've given some initial estimates to four models (left, right, forward
and up) and mapped these models to actions in Amarok (next, prev,
volumeUp and mute) with dcop.
For example, I've modeled right with 3 states (one state is the
initial state where you hold the Wii in your hand, the second is when
you make your push to your right and the final state is when you stop
moving your hand).

In currently working on gesture training to change the types to
double. Another thing I miss is Matlab (which I don't have on Ubuntu)
and can't seem to find it anywhere.
However, I've found Mathematica on Linux - I'm not familiar with
Mathematica, but this one seems to have a better syntax and it draws
antialiased plots (Matlab can't do antialias unfortunately).

Everything was checked in to SVN.

-- 
http://www.borza.ro