Title: Face recognition of large scale via sparse representation under frequency domain
Abstract: The recognition rate of face recognition is influenced by many factors,in which there are lots of effective algorithms,however,with the increase of face in the database,and the recognition rate will be decreased rapidly. In this situation,the sparse representation classification under the frequency domain can solve the above problems effectively. Firstly,the face image will be transformed from time domain to frequency domain using FFT algorithm,and then sparse representation about the test sample will be obtained by l1 norm optimization approach,in which all the training samples as the base vectors,in addition using the nearest neighbor subspace classification. Finally the experimental results show that the algorithm is effective in the extensional Yale B face database.
Publication Year: 2015
Publication Date: 2015-01-01
Language: en
Type: article
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