A face recognition algorithm based on collaborative representation |
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Authors: | Zhengming Li Tong Zhan Binglei Xie Jian Cao Jianxiong Zhang |
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Institution: | 1. Guangdong Industry Training Center, Guangdong Polytechnic Normal University, Guangzhou, China;2. Bio-Computing Research Center, Harbin Institute of Technology, Shenzhen Graduate School, Shenzhen, China;3. Shenzhen Key Laboratory of Urban Planning and Decision-Making Simulation, Shenzhen, China |
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Abstract: | In this paper, we propose a face recognition algorithm by incorporating a neighbor matrix into the objective function of sparse coding. We first calculate the neighbor matrix between the test sample and each training sample by using the revised reconstruction error of each class. Specifically, the revised reconstruction error (RRE) of each class is the division of the l2-norm of reconstruction error to the l2-norm of reconstruction coefficients, which can be used to increase the discrimination information for classification. Then we use the neighbor matrix and all the training samples to linearly represent the test sample. Thus, our algorithm can preserve locality and similarity information of sparse coding. The experimental results show that our algorithm achieves better performance than four previous algorithms on three face databases. |
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Keywords: | Face recognition Sparse coding Neighbor matrix Collaborative representation |
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