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基于Fisher块对角LNMF的彩色人脸识别
引用本文:王成章,白晓明. 基于Fisher块对角LNMF的彩色人脸识别[J]. 计算机工程, 2010, 36(16): 24-26
作者姓名:王成章  白晓明
作者单位:1. 中央财经大学应用数学学院,北京,100081
2. 首都经济贸易大学信息学院,北京,100070
基金项目:国家自然科学基金青年科学基金资助项目,中央财经大学学科建设基金,首都经济贸易大学校级基金资助重点项目 
摘    要:为提高对彩色人脸的识别率,提出一种基于Fisher块对角局部非负矩阵分解(LNMF)的识别算法。采用块对角矩阵编码彩色图像不同通道的颜色信息,在LNMF算法中增加块对角约束和Fisher判别约束,对不同通道的颜色信息同时进行计算并融入人脸的类别信息,用于提取人脸特征。在CVL和PIE彩色人脸数据库上的实验结果验证了该识别算法的有效性。

关 键 词:人脸识别  非负矩阵分解  Fisher判别

Color Face Recognition Based on Fisher Block Diagonal LNMF
WANG Cheng-zhang,BAI Xiao-ming. Color Face Recognition Based on Fisher Block Diagonal LNMF[J]. Computer Engineering, 2010, 36(16): 24-26
Authors:WANG Cheng-zhang  BAI Xiao-ming
Affiliation:(1. College of Applied Mathematics, Central University of Finance and Economics, Beijing 100081;2. College of Information, Capital University of Economics and Business, Beijing 100070)
Abstract:To improve the recognition rate of color face, this paper proposes a recognition algorithm based on Fisher block diagonal Local Non-negative Matrix Factorization(LNMF). The algorithm employs block diagonal matrix to encode color information of different channels for color images. Block diagonal constraint and Fisher discrimination constraint are imposed on LNMF algorithm to compute color information of different channels simultaneously for face feature extraction. Experimental results on CVL and PIE color face databases verify the effectiveness of the recognition algorithm.
Keywords:face recognition  Non-negative Matrix Factorization(NMF)  Fisher discrimination
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