Symmetry based two-dimensional principal component analysis for face recognition

被引：0
|
作者：
Ding, Mingyong [1 ]
Lu, Congde [2 ]
Lin, Yunsong [2 ]
Tong, Ling [2 ]
机构：
[1] Chongqing Technol & Business Univ, Sch Comp Sci & Informat Engn, Chongqing 400067, Peoples R China
[2] Univ Elect Sci & Technol China, Sch Automat Engn, Chengdu 610054, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2007, PT 2, PROCEEDINGS | 2007年 / 4492卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Two-dimensional principal component analysis (2DPCA) proposed recently overcome a limitation of principal component analysis (PCA) which is expensive computational cost. Symmetrical principal component analysis (SPCA) is also a better feature extraction technique because it utilizes effectively the symmetrical property of human face. This paper presents a symmetry based two-dimensional principal component analysis (S2DPCA), which combines the advantages of 2DPCA and of the SPCA. The experimental results show that S2DPCA is competitive with or superior to 2DPCA and SPCA.
引用
收藏
页码：1048 / +
页数：3
相关论文
共 50 条
  • [21] An Incremental Two-Dimensional Principal Component Analysis for Object Recognition
    Ge, Weimin
    Sun, Mingyue
    Wang, Xiaofeng
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2018, 2018
  • [22] Structural two-dimensional principal component analysis for image recognition
    Wang, Haixian
    MACHINE VISION AND APPLICATIONS, 2011, 22 (02) : 433 - 438
  • [23] Two-Dimensional Sparse Principal Component Analysis for Palmprint Recognition
    Xiao, Cuntao
    ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS, 2010, 6215 : 611 - 618
  • [24] Face Recognition via Multi linear Principal Component Analysis and Two-Dimensional Extreme Learning Machine
    Zhang, Fan
    Qi, Lin
    Chen, Enqing
    JOURNAL OF COMPUTATIONAL AND THEORETICAL NANOSCIENCE, 2015, 12 (07) : 1138 - 1143
  • [25] Recognition of Wafer Defect Based on Two-Dimensional Principal Component Analysis Based Convolutional Autoencoder
    Liu, Jiatong
    Yu, Jianbo
    Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics, 2020, 32 (03): : 425 - 436
  • [26] EXPLOITING SYMMETRY IN TWO-DIMENSIONAL CLUSTERING-BASED DISCRIMINANT ANALYSIS FOR FACE RECOGNITION
    Papachristou, Konstantinos
    Tefas, Anastasios
    Pitas, Ioannis
    2015 23RD EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), 2015, : 155 - 159
  • [27] Two-dimensional matrix principal component analysis useful for character recognition
    Manjunath, Aradhya V. N.
    Hemantha, Kumar G.
    Noushath, S.
    2006 INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION, 2007, : 390 - 393
  • [28] An Incremental Two-dimensional Principal Component Analysis for Image Compression and Recognition
    Nakouri, Haifa
    Limam, Mohamed
    2016 12TH INTERNATIONAL CONFERENCE ON SIGNAL-IMAGE TECHNOLOGY & INTERNET-BASED SYSTEMS (SITIS), 2016, : 725 - 731
  • [29] Face Hallucination Using Bilateral-Projection-Based Two-Dimensional Principal Component Analysis
    Sanguansat, Parinya
    ICCEE 2008: PROCEEDINGS OF THE 2008 INTERNATIONAL CONFERENCE ON COMPUTER AND ELECTRICAL ENGINEERING, 2008, : 876 - 880
  • [30] FACE RECOGNITION USING CURVELET-BASED TWO-DIMENSIONAL PRINCIPLE COMPONENT ANALYSIS
    Zhang, Yan
    Yu, Bin
    Gu, Hai-Ming
    INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2012, 26 (03)
12345