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- 저자 : ( Qiaolin Ye ) (검색결과 1 건)
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A Novel Multiple Kernel Sparse Representation based Classification for Face Recognition
( Hao Zheng ),( Qiaolin Ye ),( Zhong Jin ) 한국인터넷정보학회 2014 KSII Transactions on Internet and Information Syst Vol.8 No.4
It is well known that sparse code is effective for feature extraction of face recognition, especially sparse mode can be learned in the kernel space, and obtain better performance. Some recent algorithms made use of single kernel in the sparse mode, but this didn`t make full use of the kernel information. The key issue is how to select the suitable kernel weights, and combine the selected kernels. In this paper, we propose a novel multiple kernel sparse representation based classification for face recognition (MKSRC), which performs sparse code and dictionary learning in the multiple kernel space. Initially, several possible kernels are combined and the sparse coefficient is computed, then the kernel weights can be obtained by the sparse coefficient. Finally convergence makes the kernel weights optimal. The experiments results show that our algorithm outperforms other state-of-the-art algorithms and demonstrate the promising performance of the proposed algorithms.
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