// ----------------------------------------------------------------------------------------------------------
// Feature Mean subtraction and Cov reduction for a segment and cluster (segment is considerred to be the minimum time unit to perform this).
void computeZeroOne(const DoubleVector &featureMean,const DoubleVector &featureStd,FeatureServer & fs,unsigned long begin, unsigned long length,Config &config) {
unsigned long vectsize=fs.getVectSize(); // Get the vect size (number of coeff)
Feature f;
fs.seekFeature(begin);
for (unsigned long idxFrame=0;idxFrame<length;idxFrame++){ // for all the features of the segment
fs.readFeature(f,0);
// Get the feature;
for (unsigned int i = 0; i < vectsize; i++) { // For each coeff
f[i]=(f[i]-featureMean[i])/featureStd[i]; // Apply the 0 mean 1 cov normalisation
}
fs.writeFeature(f);
}
}
// ----------------------------------------------------------------------------------------------------------
// Feature Warping giving a source(tab of histo, one by coeff) and a target distribution
// for a segment and cluster (segment is the minimum time unit to perform this)
void computeWarp(Histo *histoT,Histo &destH,FeatureServer & fs,unsigned long begin, unsigned long length,Config &config) {
unsigned long vectsize=fs.getVectSize(); // Get the vect size (number of coeff)
Feature f;
fs.seekFeature(begin);
for (unsigned long idxFrame=0;idxFrame<length;idxFrame++){ // for all the features of the segment
fs.readFeature(f,0);
// Get the feature;
for (unsigned int i = 0; i < vectsize; i++){ // For each coeff
f[i]=warping(f[i],histoT[i],destH); // Apply the warping function
}
fs.writeFeature(f);
}
}