A Kernel Two-Phase Test Sample Sparse Representation for Face Recognition

作者：Liu, Zhonghua^*; Pu, Jiexin; Qiu, Yong; Zhang, Moli; Zhang, Xiaoli; Huang, Guangjun

来源：International Journal of Pattern Recognition and Artificial Intelligence, 2016, 30(1): 1656001.

DOI：10.1142/S0218001416560012

• Face recognition
• sparse representation
• kernel two-phase test sample sparse representation method
• kernel trick

Sparse representation is a new hot technique in recent years. The two-phase test sample sparse representation method (TPTSSR) achieved an excellent performance in face recognition. In this paper, a kernel two-phase test sample sparse representation method (KTPTSSR) is proposed. Firstly, the input data are mapped into an implicit high-dimensional feature space by a non-linear mapping function. Secondly, the data are analyzed by means of the TPTSSR method in the feature space. If an appropriate kernel function and the corresponding kernel parameter are selected, a test sample can be accurately represented as the linear combination of the training data with the same label information of the test sample. Therefore, the proposed method could have better recognition performance than TPTSSR. Experiments on the face databases demonstrate the effectiveness of our methods.

• 出版日期2016-1
• 单位中国人民解放军信息工程大学; 西华大学; 河南大学