/**
* Performs hmm train for all training data set.<br>
* First quantizes the feature vector against codebook, and then train baum-welch
*
* @return
*/
public boolean trainHMM() {
boolean operationSuccess = false;
codebook = new Codebook();
database.setMode(DBMode.TRAINDATA);
Model[][] regModels = database.readAllDataofCurrentMode();
String[] gestName = database.getRegisteredModelNames();
int quantizedSeq[][];
HiddenMarkov mkv = new HiddenMarkov(NUM_STATES, NUM_SYMBOLS);
// for each gesture
for (int i = 0; i < regModels.length; i++) {
operationSuccess = false;
// for each train sample of current gesture
quantizedSeq = new int[regModels[i].length][];
for (int j = 0; j < regModels[i].length; j++) {
GestureFeature[] gf = getFeature((RawFeature) regModels[i][j]);
Points[] pts = getPointsFromFeatureVector(gf);
quantizedSeq[j] = codebook.quantize(pts);
}
mkv.setTrainSeq(quantizedSeq);
mkv.train();
mkv.save(gestName[i]);
operationSuccess = true;
}
return operationSuccess;
}
public String[] readTrainData1D() {
database.setMode(DBMode.TRAINDATA);
return (database.getRegisteredModelNames());
}
public String[] readRegGestureModels() {
database.setMode(DBMode.HMM_MODEL);
return (database.getRegisteredModelNames());
}
