PCA-based dictionary building for accurate facial expression recognition via sparse representation
We propose a new dictionary building algorithm based on Principal Component Analysis. The new DB algorithm is used for facial expression recognition. The PCA-based dictionary is less dependent to identity and more reliable. The state-of-the-art sparse solvers including BP, MP and SL0 are compared. The generalization power of the proposed algorithm across datasets is studied.
dictionary building facial expression recognition sparse representation principal component analysis generalization power basic emotions dictionary learning difference image