计算机科学 ›› 2022, Vol. 49 ›› Issue (6A): 429-433.doi: 10.11896/jsjkx.210300169
黄璞, 沈阳阳, 杜旭然, 杨章静
HUANG Pu, SHEN Yang-yang, DU Xu-ran, YANG Zhang-jing
摘要： 针对协同表示分类器(CRC)及其相关算法在处理人脸识别问题时面临的特征表达能力不强、鉴别能力弱等问题,提出了局部约束特征线表示分类器(LCFLRC)用于人脸识别。LCFLRC首先将待识别图像表示成其在所有特征线上的投影的线性组合,并根据待识别图像与特征线的距离对其施加约束,然后采用拉格朗日乘子法求解基于L2范数的最优化问题,最后,根据待识别图像与其在每类特征线上的投影的重构残差大小判断待识别图像的类别。LCFLRC采用待识别图像在特征线上的投影来表示待识别图像,能够获取有限人脸图像样本中的更多变化,同时利用了待识别图像与特征线的距离信息,使得离待识别图像较近的特征线上的投影在表示待识别图像时重构系数较大,因此包含更多的判别信息。在CMU PIE,Extended Yale-B以及AR人脸库上的实验结果表明,相比其他分类算法,所提算法在图像光照、人脸表情、姿态等变化方面的识别率有显著提升。
中图分类号:
| [1] COVER T,HART P.Nearest neighbor pattern classification[J].IEEE Transactions on Information Theory,1967,13(1):21-27. [2] GONZALEZ R C,WOODS R E.Digital image processing [M].Hoboken:Addison Wesley,1997. [3] DUDA R O,HART P E,STORK D G.Pattern classification,2nd edition [M].Hoboken Wiley,2000. [4] LI S Z,LU J W.Face recognition using the nearest feature line method[J].IEEE Transactions on Neural Networks,1999,10(2):439-443. [5] WRIGHT J,YANG A Y,GANESH A,et al.Robust face recognition via sparse representation[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2008,31(2):210-227. [6] HANG L,YANG M,FENG X.Sparse representation or colla-borative representation:which helps face recognition[C]//Proceedings of IEEE Conference on Computer Vision.2011:471-487. [7] NASEEM I,TOGNERI R,BENNAMOUN M.Linear regres-sion for face recognition[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2010,32(11):2106-2112. [8] XU J,YANG J.Mean representation based classifier with its applications[J].Electronics Letters,2011,47(18):1024-1026. [9] HUANG P,QIAN C S,YANG G,et al.Local mean representation based classifier and its applications for data classification[J].International Journal of Machine Learning and Cybernetics,2018,9(8):969-978. [10] FENG Q,YUAN C,PAN J,et al.Superimposed Sparse Parameter Classifiers for Face Recognition[J].IEEE Transactions on Cybernetics,2017,47(2):378-390. [11] DONG X,ZHANG H,ZHU L,et al.Weighted locality collaborative representation based on sparse subspace[J].Journal of Visual Communication and Image Representation,2019,58:187-194. [12] GOU J,WANG L,HOU B,et al.Two-Phase Probabilistic Collaborative Representation-Based Classification[J].Expert Systems with Applications,2019,133:9-20. [13] GOU J,WANG L,YI Z,et al.Weighted discriminative collaborative competitive representation for robust image classification[J].Neural Networks,2020,125:104-120. [14] ZHENG C,WANG N.Collaborative representation with k-nearest classes for classification[J].Pattern Recognition Letters,2019,117:30-36. [15] WAQAS J,YI Z,ZHANG L.Collaborative neighbor representation based classification using l2-minimization approach[J].Pattern Recognition Letters,2013,34:201-208. [16] TURK M,PENTLAND A.Eigenfaces for recognition[J].Jou-rnal of Cognitive Neuroscience,1991,3(1):71-86. |
| [1] | 黄璞, 杜旭然, 沈阳阳, 杨章静. 基于局部正则二次线性重构表示的人脸识别 Face Recognition Based on Locality Regularized Double Linear Reconstruction Representation 计算机科学, 2022, 49(6A): 407-411. https://doi.org/10.11896/jsjkx.210700018 |
| [2] | 程祥鸣, 邓春华. 基于无标签知识蒸馏的人脸识别模型的压缩算法 Compression Algorithm of Face Recognition Model Based on Unlabeled Knowledge Distillation 计算机科学, 2022, 49(6): 245-253. https://doi.org/10.11896/jsjkx.210400023 |
| [3] | 魏勤, 李瑛娇, 娄平, 严俊伟, 胡辑伟. 基于边云协同的人脸识别方法研究 Face Recognition Method Based on Edge-Cloud Collaboration 计算机科学, 2022, 49(5): 71-77. https://doi.org/10.11896/jsjkx.210300222 |
| [4] | 何嘉玉, 黄宏博, 张红艳, 孙牧野, 刘亚辉, 周哲海. 基于深度学习的单幅图像三维人脸重建研究综述 Review of 3D Face Reconstruction Based on Single Image 计算机科学, 2022, 49(2): 40-50. https://doi.org/10.11896/jsjkx.210500215 |
| [5] | 陈长伟, 周晓峰. 快速局部协同表示分类器及其在人脸识别中的应用 Fast Local Collaborative Representation Based Classifier and Its Applications in Face Recognition 计算机科学, 2021, 48(9): 208-215. https://doi.org/10.11896/jsjkx.200800155 |
| [6] | 温荷, 罗频捷. 基于改进脉冲耦合神经网络的动态人脸识别 Dynamic Face Recognition Based on Improved Pulse Coupled Neural Network 计算机科学, 2021, 48(6A): 85-88. https://doi.org/10.11896/jsjkx.200600172 |
| [7] | 白子轶, 毛懿荣, 王瑞平. 视频人脸识别进展综述 Survey on Video-based Face Recognition 计算机科学, 2021, 48(3): 50-59. https://doi.org/10.11896/jsjkx.210100210 |
| [8] | 陆要要, 袁家斌, 何珊, 王天星. 基于超分辨率重建的低质量视频人脸识别方法 Low-quality Video Face Recognition Method Based on Super-resolution Reconstruction 计算机科学, 2021, 48(11A): 295-302. https://doi.org/10.11896/jsjkx.201200159 |
| [9] | 杨章静, 王文博, 黄璞, 张凡龙, 王昕. 基于局部加权表示的线性回归分类器及人脸识别 Local Weighted Representation Based Linear Regression Classifier and Face Recognition 计算机科学, 2021, 48(11A): 351-359. https://doi.org/10.11896/jsjkx.210100173 |
| [10] | 栾晓, 李晓双. 基于多特征融合的人脸活体检测算法 Face Anti-spoofing Algorithm Based on Multi-feature Fusion 计算机科学, 2021, 48(11A): 409-415. https://doi.org/10.11896/jsjkx.210100181 |
| [11] | 王慧, 乐孜纯, 龚轩, 武玉坤, 左浩. 基于特征分类的链路预测方法综述 Review of Link Prediction Methods Based on Feature Classification 计算机科学, 2020, 47(8): 302-312. https://doi.org/10.11896/jsjkx.190700136 |
| [12] | 吴庆洪, 高晓东. 稀疏表示和支持向量机相融合的非理想环境人脸识别 Face Recognition in Non-ideal Environment Based on Sparse Representation and Support Vector Machine 计算机科学, 2020, 47(6): 121-125. https://doi.org/10.11896/jsjkx.190500058 |
| [13] | 李新豆,高陈强,周风顺,韩慧,汤林. 基于图像扩散速度模型和纹理信息的人脸活体检测 Face Liveness Detection Based on Image Diffusion Speed Model and Texture Information 计算机科学, 2020, 47(2): 112-117. https://doi.org/10.11896/jsjkx.181202339 |
| [14] | 金堃, 陈少昌. 步态识别现状与发展 Status and Development of Gait Recognition 计算机科学, 2019, 46(6A): 30-34. |
| [15] | 陈晋音, 王桢, 陈劲聿, 陈治清, 郑海斌. 基于深度学习的智能教学系统的设计与研究 Design and Research on Intelligent Teaching System Based on Deep Learning 计算机科学, 2019, 46(6A): 550-554. |
|
||