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| Extended Marginal Fisher Analysis Based on Difference Criterion |
| Jijian Liu, Heng Zheng, Shuchao Pang, Chaoxia Wu, Chengcheng Jia, Zhezhou Yu |
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Abstract The reasonable construction of neighbor graph plays an important
impact to improve the efficiency of face recognition in Marginal
Fisher Analysis (MFA) algorithm. In this paper, a new method of
constructing neighbor graph is proposed to improve the recognition
accuracy of MFA. Specifically, we try to map the raw data of the
training samples to a new feature space $\digamma$, then we select
the nearest neighbor points directly based on the new distances,
thereby constructing the graph. In addition, we also introduce a new
criterion function, which can overcome some shortcomings of MFA. The
contrastive experiments on several benchmark face databases show the
effectiveness of proposed method.
DOI: 10.12733/jics20101738
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