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《Journal of Data Acquisition and Processing》 2015-01
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Algorithm for Single Sample Face Recognition Based on Sample Augments and Double Subspace Decision Fusion

Yang Jun;Yuan Hongzhao;Liu Yanli;College of Computer Science,Sichuan Normal University;School of Computer Science,Anyang Normal University;College of Mathematics and Software Science,Sichuan Normal University;  
To apply supervised learning method in single face recognition problem,an improved algorithm based on sample augments by sliding window is proposed.The recognition time of the proposed algorithm is shorter than that of the original algorithm because of less feature dimension.Moreover,the mirror samples are generated to constitute auxiliary training set and two subspaces can be obtained by subspace learning.The recognition result is from the decision fusion of two subspaces and is robust to variation of the test samples.The experiment results on ORL face database and subset of Feret face database show that the proposed algorithm has higher recognition accuracy than other similar algorithms.
【Fund】: 国家自然科学基金(61373163)资助项目;; 国家科技支撑计划(2012BAH76F01)资助项目;; 四川省教育厅科研(11ZB069)资助项目;; 四川省可视化与虚拟现实重点实验室(PJ2012001)资助项目
【CateGory Index】: TP391.41
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