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增强LLE特征分类性能的人脸识别 被引量：3

Enhanced LLE Features Classification for Face Recognition
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摘要 为了增强局部线性嵌入(LLE)特征的可分类性,提出一种应用LMNN算法改善LLE特征分类性能的人脸识别方法.LMNN算法寻求一个线性变换,变换空间的欧氏距离等价于原始空间的马氏距离,马氏距离增强了LLE特征的kNN分类性能.在ORL数据库和扩展的YaleB数据库上进行实验,并与其他方法进行了比较.实验结果验证了该算法的有效性. A face recognition method is proposed using large margin nearest neighbor （LMNN） algorithm to improve locally linear embedding （LLE） features classification performance. LMNN is used to seek a linear transformation by which the Euclidean distance in the transformation space could equivalently be viewed as Mahalanobis distances in the original space. Hence, the kNN classification performance could be improved. Experiments on ORL database and extended YaleB database demonstrate the effectiveness of the proposed method.
作者 李建科 赵保军 张辉 焦继超
机构地区 河北经贸大学信息技术学院 北京理工大学雷达技术研究所 北京工业大学电子信息与控制工程学院
出处 《北京理工大学学报》 EI CAS CSCD 北大核心 2012年第6期621-624,649,共5页 Transactions of Beijing Institute of Technology
基金 国家"八六三"计划项目(2007AA1132) 河北省教育厅科研计划资助项目(20042013)
关键词 人脸识别 特征提取 分类 流形学习 距离学习 face recognitionl feature extraction classification manifold learning distancemetric learning
分类号 TN911.73 [电子电信—通信与信息系统]
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参考文献9

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同被引文献27

  • 1宋艳辉,王文永,程晓春.一个基于Viola-Jones框架的面部识别算法的改进[J].东北师大学报（自然科学版）,2005,37(3):24-27. 被引量：3
  • 2Gui J,Sun Z,Jia W,et al.Discriminant sparse neighborhood preserving embedding for face recognition[J].Pattern Recognition,2012,45(8):2884-2893.
  • 3Zhang T,Fang B,Yuan Y,et al.Multiscale facial structure representation for face recognition under varying illumination[J].Pattern Recognition,2009,42(2):251-258.
  • 4Li Y,Meng L,Feng J.Lighting coefficients transfer based face illumination normalization[M]//Pattern Recognition.Berlin Heidelberg:Springer,2012:268-275.
  • 5Zhao X,Zhang S.Facial expression recognition using local binary patterns and discriminant kernel locally linear embedding[J].EURASIP Journal on Advances in Signal Processing,2012,2012(1):1-9.
  • 6Tao D,Li X,Wu X,et al.Geometric mean for subspace selection[J].IEEE Trans on Pattern Anal.Mach.Intell,2011,31(2):260-274.
  • 7Yuan X,Hu B G.Robust feature extraction via information theoretic learning[C]//Proceedings of the 26th International Conference on Machine Learning.New York:ACM,2009:1193-1200.
  • 8Cai D,He X,Han J.Spectral regression for efficient regularized subspace learning[C]//Proceedings of the 11th International Conference on Computer Vision,2007:214-221.
  • 9Jing Xiaoyuan, Lan Chao, Zhang David, et al. Face feature extraction and recognition based on discriminant subclass-center manifold preserving projection [ J ]. Pattern Recognition Letters, 2012,33(6)..709-717.
  • 10Martinkauppi B, Hadid A, Pietiktiinen M. Color cue in facial image analysis[C]//Proceedings of Color Image Processing: Methods and Applications. Plataniots. New York: CRC Press, 2007:285-308.

引证文献3

北京理工大学学报
2012年 第6期

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