in emotion recognition from static images, we get the Gabor filters for each face part. the returning is matrices in terms of wavelengths and orientations.
How to construct the feature vector from these Gabor filters?
Yes the size of the vector will be too long (in one case I had a vector of 32 thousands of features from another descriptor), and then you use feature reduction, e.g. PCA, LDA, etc