关键词: 稀疏表示, 字典学习, 人脸识别, LC-KSVD算法

Abstract: To improve the face recognition rate, speed and robustness, this paper proposes a face recognition algorithm based on extended sparse representation model and LC-KSVD（Label Consist K-SVD）. For solving the problem that dictionary learning only contains representation ability but no class information, the algorithm adds residual vector as coefficient amending vector into original sparse representation model, making the extended model have stronger robustness. The algorithm also adds sparse coding and classifier parameter constraints into the process of dictionary learning and updates sparse coding and classifier parameters in the process, making the dictionary possess good representation and discrimination ability. The experimental results show that the algorithm has high recognition rate, low recognition speed and good robustness.

Key words: sparse representation, dictionary learning, face representation, LC-KSVD（Label Consist K-SVD）