After dealing with it I have been able to obtain the weights. For obtaining the weights one has to obtain first the support vectors and then add them multiplied by the alpha values.
// get the svm weights by multiplying the support vectors by the alpha values
int numSupportVectors = SVM.get_support_vector_count();
const float *supportVector;
const CvSVMDecisionFunc *dec = SVM.decision_func;
svmWeights = (float *) calloc((numOfFeatures+1),sizeof(float));
for (int i = 0; i < numSupportVectors; ++i)
{
float alpha = *(dec[0].alpha + i);
supportVector = SVM.get_support_vector(i);
for(int j=0;j<numOfFeatures;j++)
*(svmWeights + j) += alpha * *(supportVector+j);
}
*(svmWeights + numOfFeatures) = - dec[0].rho; //Be careful with the sign of the bias!
The only trick here is that the instance variable float *decision_function
is protected on the opencv framework, so I had to change it in order to access it.
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