Facial Expression Recognition Based on the Texture Features of Global Principal Component and Local Boundary

Abstract:

Facial expression recognition is a key ingredient to either emotion analysis or pattern recognition, which is also an important component in human-machine interaction. In facial expression analysis, one of the well-known methods to obtain the texture of expressions is local binary patterns (LBP) which compares pixels in local region and encodes the comparison result in forms of histogram. However, we argue that the textures of expressions are not accurate and still contain some irrelevant information, especially in the region between eyes and mouth. In this paper, we propose a compound method to recognize expressions by applying local binary patterns to global and local images processed by bidirectional principal component analysis (BDPCA) reconstruction and morphologic preprocess, respectively. It proves that our method can be applied for recognizing expressions by using texture features of global principal component and local boundary and achieves a considerable high accuracy.

• Periodical: Applied Mechanics and Materials (Volumes 548-549)
• Pages: 1110-1117
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.548-549.1110
• Online since: April 2014
• Authors: Wei Hao Zheng*, Wei Wang, Yi De Ma
• Keywords: BDPCA, Facial Expression Recognition, Global Principal Component, LBP, Local Boundary

References

[1] X. Feng, M. Pietikinen, and A. Hadid, in: Facial Expression Recognition Based on Local Binary Patterns, volume 17 of Pattern Recognition and Image Analysis, p.592–598 (2007).

DOI: 10.1134/s1054661807040190

[2] C. Shan, S. Gong, and P. W. McOwan, in: Facial Expression Recognition Based on Local Binary Patterns: A Comprehensive Study, volume 27 of Image and Vision Computing, no. 6, pp.803-816 (2009).

DOI: 10.1016/j.imavis.2008.08.005

[3] T. Jabeed, M. H. Kabir, and O. Chae, in: Robust Facial Expression Recognition Based on Local Directional Pattern, volume 32 of ETRI Journal, no. 5, p.784−794 (2010).

DOI: 10.4218/etrij.10.1510.0132

[4] M. A. Turk and A. P. Pentland, in: Face Recognition Using Eigenfaces, in Proc. Cvpr'91 IEEE Computer Society Conf . Digital Object Identifier, 1991, pp.586-591.

DOI: 10.1109/cvpr.1991.139758

[5] J. Yang, D. Zhang, A. F. Frangi, and J. Yang, in: Two-dimendional PCA: A New Approach to Appearance-based Face Representation and Recognition, volume 26 of IEEE Transactions on Pattern Analysis and Machine Intelligence, pp.131-137 (2004).

DOI: 10.1109/tpami.2004.1261097

[6] Y. Sun, S. Chen and B. Yin, in: Color Face Recognition Based on Quaternion Matrix Representation, volume 32 of Pattern Recognition Letters, pp.597-605 (2011).

DOI: 10.1016/j.patrec.2010.11.004

[7] T. Ojala, M. Pietikäinen, and T. Mäenpää, in: Multiresolution Gray-scale and Rotation Invariant Texture Classification with Local Binary Patterns, volume 24 of IEEE Transaction on Pattern Analysis and Machine Intelligence, no. 7, p.971−987 (2002).

DOI: 10.1109/tpami.2002.1017623

[8] F. Ahmed, E. Hossain, A.S.M. Hossain, and ASM. Shihavudd, in: Compound Local Binary Pattern (CLBP) for Facial Expression Recognition: the 12th IEEE International Symposium on Computational Intelligence and Informatics (2011), Budapest, Hungary.

DOI: 10.1109/cinti.2011.6108536

[9] M. Valstar, I. Patras, and M. Pantic, in: Facial Action Unit Detection Using Probabilistic Actively Learned Support Vector Machines on Tracked Facial Point Data, Computer Vision and Pattern Recognition. IEEE Computer Society Conference, p.76 (2005).

DOI: 10.1109/cvpr.2005.457

[10] R. C. Gonzalez, R. E. Woods and S. L. Eddins, in: Digital Image Processing Using MATLAB, TX: San Antonio, pp.277-289 (2004).

[11] J. Chen, Z. Zhao, H. Sun and G. Zhang, in: Facial Expression Recognition Based on PCA Reconstruction: the 5th International Conference on Computer Science & Education (2010), Hefei, China.

[12] T. Ojala, M. Pietikainen and D. Harw, in: A Comparative Study of Texture Measures with Classification Based on Featured Distributions, volume 29 of Pattern Recognition, no. 1, pp.51-59 (1996).

DOI: 10.1016/0031-3203(95)00067-4

[13] T. Ahonen, A. Hadid, and M. Pietikinen, in: Face Recognition with Local Binary Patterns: ECCV (2004), p.469–481.

[14] M. Lyons, J. Budynek, and S. Akamatsu, in: Automatic Classification of Single Facial Images, volume 21 of IEEE Transaction on Pattern Analysis and Machine Intelligence, no. 12, p.1357–1362 (1999).

DOI: 10.1109/34.817413

[15] Y. Luo, C. Wu, and Y. Zhang, in: Facial Expression Recognition Based on Fusion Feature of PCA and LBP with SVM, volume 124 of Optik-International Journal for Light and Electron Optics, pp.2767-2770 (2013).

DOI: 10.1016/j.ijleo.2012.08.040

[16] Z. Niu and X. Qiu, in: Facial Expression Recognition Based on Weighted Principal Component Analysis and Support Vector Machines: 3rd Int. Conf. Advanced Computer Theory and Engineering (2010), pp.174-178.

DOI: 10.1109/icacte.2010.5579670

[17] Y. Zhang and C. Liu, in: Face Recognition Based on Support Vector Machines and Nearest Neighbor Classifier, volume 14 of System Engineering and Electronics, pp.73-76 (2003).