2D Principal Component Analysis for Face and Facial-Expression Recognition

Computing in Science and Engineering

Volumn 13, Issue 3, 2011, Pages 9-13

  Oliveira, Luiz S ^a   Koerich, Alessandro L ^a   Mansano, Marcelo ^a   Britto, Alceu S ^b  

^a FEDERAL UNIVERSITY OF PARANÁ   (Brazil)

^b PONTIFICAL CATHOLIC UNIVERSITY OF PARANÁ   (Brazil)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85008561842     PISSN: 15219615     EISSN: None     Source Type: Journal    
DOI: 10.1109/MCSE.2010.149     Document Type: Article

References (11)

1. W. Zhao et al., “Face Recognition: A Literature Survey,” ACM Computing Surveys, vol. 35, no. 4, 2003, pp. 399–458.
2. M. Turk and A. Pentland, “Eigenfaces for Recognition,” J. Cognitive Neuroscience, vol. 3, no. 1, 1991, pp. 71–86.
3. J. Yang et al., “Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 26, no. 1, 2004, pp. 131–137.
4. 2PCA: 2-Directional 2-Dimensional PCA for Efficient Face Representation and Recognition,” NeuroComputing, vol. 69, nos. 1–2, 2005, pp. 224–231.
5. A.S. Britto, Jr., L.S. Oliveira, and A.L. Koerich, “Face Recognition Using Selected 2DPCA Coefficients,” Proc. 17th Int'l Conf. Systems, Signals and Image Processing, Editora da Universidade Federal Fluminense, 2010, pp. 490–493; www.ic.uff.br/iwssip2010/Proceedings/nav/papers/paper_162.pdf.
6. M. Kudo and J. Sklansky, “Comparison of Algorithms that Select Features for Pattern Classifiers,” Pattern Recognition, vol. 33, no. 1, 2000, pp. 25–41.
7. L.S. Oliveira et al., “A Methodology for Feature Selection Using Multi-Objective Genetic Algorithms for Handwritten Digit String Recognition,” Int'l J. Pattern Recognition and Artificial Intelligence, vol. 17, no. 6, 2003, pp. 903–930.
8. P. Viola and M. Jones, “Robust Real-Time Face Detection,” Int'l J. Computer Vision, vol. 57, no. 2, 2004, pp. 137–154.
9. S. Bashyal and G.K. Venayagamoorthy, “Recognition of Facial Expressions Using Gabor Wavelets and Learning Vector Quantization,” Eng. Applications of Artificial Intelligence, vol. 28, no. 7, 2008, pp. 1056–1064.
10. A. Koutlas and D.I. Fotiadis, “An Automatic Region-Based Methodology for Facial Expression Recognition,” Proc. IEEE Int'l Conf. Systems, Man and Cybernetics, IEEE Press, 2008, pp. 662–666.
11. C. Shan, S. Gong, and P.W. McOwan, “Facial Expression Recognition Based on Local Binary Patterns: A Comprehensive Study,” Image and Vision Computing, vol. 27, no. 6, 2009, pp. 803–816.