Application of Dictionary Learning Based on DDR in Face Recognition with Illustration Variation
Liya Wang · Science Technology and Engineering · 2014
Most existing face recognition algorithms can not use discriminative information of samples due to they only carry out dimensionality reduction or dictionary learning,for which dictionary learning algorithm based on discriminative dimensionality reduction is proposed. Firstly,typical feature extraction algorithm PCA is used to initialize dimensionality reduction projection matrix. Then,dictionary and coefficient is computed and the dictionary can match with each other by jointing dimension reduction and dictionary learning. Finally,dictionary and projection matrix is outputted by using iterative algorithm,and classifier regularized by l2-norm is used to finish face recognition. The effectiveness and reliability of proposed algorithm has been verified by experiments on PIE and extended YaleB face databases. Experimental results show that proposed algorithm has higher recognition accuracy than several other advanced linear represent algorithms in dealing with face recognition with illustration variation.