多稀疏表示分类器决策融合的人脸识别

唐彪; 金炜; 符冉迪; 龚飞

doi:10.11959/j.issn.1000-0801.2018010

您当前的位置：

首页 >

文章列表页 >

多稀疏表示分类器决策融合的人脸识别

研究与开发 | 更新时间：2024-06-05

- 多稀疏表示分类器决策融合的人脸识别
- Face recognition using decision fusion of multiple sparse representation-based classifiers
- 电信科学 2018年34卷第4期页码：31-40
- 作者机构：
- 作者简介：
  
  [ "唐彪（1994-），男，宁波大学信息科学与工程学院硕士生，主要研究方向为模式识别、压缩感知和图像处理。" ]
  [ "金炜（1969-），男，博士，宁波大学信息科学与工程学院副教授、硕士生导师，主要研究方向为压缩感知、模式识别和数字图像处理等。" ]
  [ "符冉迪（1971-），男，宁波大学信息科学与工程学院副教授、硕士生导师，主要研究方向为压缩感知、数字图像处理等。" ]
  [ "龚飞（1989-），男，宁波大学信息科学与工程学院硕士生，主要研究方向为机器学习、压缩感知和图像处理。" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(61471212);浙江省自然科学基金资助项目;The Natural Science Foundation of Zhejiang Province of China(LY16F010001);宁波市自然科学基金资助项目;The Natural Science Foundation of Ningbo of China(2016A610091);宁波市自然科学基金资助项目;The Natural Science Foundation of Ningbo of China(2017A610297)
- DOI：10.11959/j.issn.1000-0801.2018010
  中图分类号： TP391.4
- 网络出版日期：2018-04，
  
  纸质出版日期：2018-04-20
- 稿件说明：
移动端阅览
唐彪, 金炜, 符冉迪, 等. 多稀疏表示分类器决策融合的人脸识别[J]. 电信科学, 2018,34(4):31-40.

Biao TANG, Wei JIN, Randi FU, et al. Face recognition using decision fusion of multiple sparse representation-based classifiers[J]. Telecommunications science, 2018, 34(4): 31-40.
唐彪, 金炜, 符冉迪, 等. 多稀疏表示分类器决策融合的人脸识别[J]. 电信科学, 2018,34(4):31-40. DOI： 10.11959/j.issn.1000-0801.2018010.

Biao TANG, Wei JIN, Randi FU, et al. Face recognition using decision fusion of multiple sparse representation-based classifiers[J]. Telecommunications science, 2018, 34(4): 31-40. DOI： 10.11959/j.issn.1000-0801.2018010.

摘要

针对目前人脸识别仍然存在顽健性较差的问题，提出一种多稀疏表示分类器决策融合（FR-MSRC）的人脸识别方法。首先提取3组特征，并训练3个稀疏表示子分类器，然后引入决策融合的思想，根据每个子分类器的分类性能，通过迭代运算过程自适应确定各子分类器的融合权值，最后利用融合权值对多个子分类器的输出结果进行决策，实现不同复杂因素干扰下的人脸识别，分别在Yale B、JAFFE和AR人脸库中进行光照、表情、遮挡以及多类型因素混合干扰实验。实验结果表明，本文提出的方法在复杂的环境中仍保持较高的识别率，顽健性更佳。

Abstract

A new approach to face recognition combining decision fusion and multiple sparse representation-based classifiers was proposed to improve the robustness of the traditional methods.Different types of facial features were extracted

followed by training multiple sparse representation sub-classifiers

and then decision fusion was used to obtain the recognition result of the system.The significant advantage of the proposed scheme lines in that the final recognition results were not driven by averaging outputs of multiple sub-classifiers

but driven by combining multiple outputs via weighted fusion method.In particular

the fusion weights were adaptively determined by an iterative pro-cedure according to the different classification performance of each sub-classifier.Extensive experiments on Yale B

JAFFE and AR face databases demonstrate that the proposed approach is much more effective than state-of-the-art methods in dealing with lighting changes

expression changes and face occlusion and multi factor mixed interference.

关键词

Keywords

references

邹国锋 , 傅桂霞 , 李海涛 , 等 . 多姿态人脸识别综述 [J ] . 模式识别与人工智能 , 2015 , 28 ( 7 ): 613 - 625 .

ZOU G F , FU G X , LI H T , et al . A survey of multi-pose face recognition [J ] . Pattern Recognition and Artificial Intelligence , 2015 , 28 ( 7 ): 613 - 625 .

李娜 , 张晓宁 , 朱芳娥 . 视觉传感网络中身份特征自适应识别算法改进 [J ] . 电信科学 , 2016 , 32 ( 6 ): 110 - 115 .

LI N , ZHANG X N , ZHU F E . Improvement of identity adaptive recognition algorithm in visual sensor network [J ] . Telecommunications Science , 2016 , 32 ( 6 ): 110 - 115 .

赵鑫 , 汪维家 , 曾雅云 , 等 . 改进的模块 PCA 人脸识别新算法 [J ] . 计算机工程与应用 , 2015 ( 2 ): 161 - 164 .

ZHAO X , WANG W J , ZENG Y Y , et al . Improved modular PCA face recognition algorithm [J ] . Computer Engineering and Applications , 2015 ( 2 ): 161 - 164 .

张健 , 肖迪 . 基于多尺度自适应 LDA 的人脸识别方法 [J ] . 计算机工程与设计 , 2012 , 33 ( 1 ): 332 - 335 .

ZHANG J , XIAO D . Face recognition method based on multi-scale adaptive LDA [J ] . Computer Engineering and Design , 2012 , 33 ( 1 ): 332 - 335 .

WRIGHT J , YANG A Y , GANESH A , et al . Robust face recognition via sparse representation [J ] . IEEE Transactions on Pattern Analysis and Machine Intelligence , 2009 , 31 ( 2 ): 210 - 227 .

张勇 , 党兰学 . 线性判别分析特征提取稀疏表示人脸识别方法 [J ] . 郑州大学学报(工学版) , 2015 , 36 ( 2 ): 94 - 98 .

ZHANG Y , DANG L X . Sparse representation-based face recognition method by LDA feature extraction [J ] . Journal of Zhengzhou University (Engineering Science) , 2015 , 36 ( 2 ): 94 - 98 .

YANG M , ZHANG L . Gabor feature based sparse representation for face recognition with gabor occlusion dictionary [J ] . Computer Vision-ECCV , 2010 : 448 - 461 .

龚飞 , 金炜 , 朱珂晴 , 等 . 采用双字典协作稀疏表示的光照及表情顽健人脸识别 [J ] . 电信科学 , 2017 , 33 ( 3 ): 52 - 58 .

GONG F , JIN W , ZHU K Q , et al . Illumination and expression robust face recognition using collaboration of double dictionary’s sparse representation-based classification [J ] . Telecommunications Science , 2017 , 33 ( 3 ): 52 - 58 .

LIU Z , PU J , XU M , et al . Face recognition via weighted two phase test sample sparse representation [J ] . Neural Processing Letters , 2015 , 41 ( 1 ): 43 - 53 .

LI J , SANG N , GAO C . Log-Gabor weber descriptor for face recognition [J ] . Journal of Electronic Imaging , 2015 , 24 ( 5 ):053014.

SURULIANDI A , MEENA K , ROSE R R . Local binary pattern and its derivatives for face recognition [J ] . IET Computer Vision , 2012 , 6 ( 5 ): 480 - 488 .

DALAL N , TRIGGS B . Histograms of oriented gradients for human detection [C ] // IEEE Computer Society Conference on Computer Vision and Pattern Recognition,June 20-25,2005,San Diego,USA . Piscataway:IEEE Press , 2005 : 886 - 893 .

颜文 , 金炜 , 符冉迪 . 结合 VLAD 特征和稀疏表示的图像检索 [J ] . 电信科学 , 2016 , 32 ( 12 ): 80 - 85 .

YAN W , JIN W , FU R D . Image retrieval based on the feature of VLAD and sparse representation [J ] . Telecommunications Science , 2016 , 32 ( 12 ): 80 - 85 .

RAHMAN A F R , FAIRHURST M C . Multiple classifier decision combination strategies for character recognition:a review [J ] . International Journal on Document Analysis and Recognition , 2003 , 5 ( 4 ): 166 - 194 .

张文博 , 姬红兵 , 王磊 . 一种自适应权值的多特征融合分类方法 [J ] . 系统工程与电子技术 , 2013 , 35 ( 6 ): 1133 - 1137 .

ZHANG W B , JI H B , WANG L . Adaptive weighted feature fusion classification method [J ] . Systems Engineering and Electronics , 2013 , 35 ( 6 ): 1133 - 1137 .

张冬慧 , 孙波 , 王鹏 , 等 . 权值自适应调整的多分类器融合算法 [J ] . 计算机工程 , 2008 ( 10 ): 28 - 29 ,32.

ZHANG D H , SUN B , WANG P , et al . Multi-classifiers fusion algorithm of adaptive weight adjustment [J ] . Computer Engineering , 2008 ( 10 ): 28 - 29 ,32.

浏览量

860

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

基于吸引模式的局部二阶梯度轮廓人脸识别算法

人机交互安全攻防综述

采用双字典协作稀疏表示的光照及表情顽健人脸识别