Efficiency Improvement in Recognition of Human Facial Expression

Authors(1) :-Uttam L. Patel

Face recognition has been very important issue in computer vision and pattern recognition over the last several decades. One difficulty in face recognition is how to handle the variations in the expression, pose and illumination when only a limited number of training samples are available. Here we used two databases, one is an Indian database which is not a standard database and second one is a JAFFE (Japanese Female Facial Expression). When we implemented facial expression recognition system using Indian database then we got accuracy of the algorithm is 68%. Then we implemented same system with JAFFE database then we got accuracy of the algorithm is about 70-71% which gives quite poor Efficiency of the system. Then we implemented facial expression recognition system with Gabor filter and principal component analysis. Here Gabor filter we have selected because of its good feature extraction property. Then the output of the Gabor filter we have used as an input for the PCA. Principal Component Analysis has a good feature of dimension reduction so we choose it for that purpose. In this system we used JAFFE database for training and testing purpose and we got good results. We got efficiency of the system is about 76-77% which higher than the previous system.

Authors and Affiliations

Uttam L. Patel
Department of Computer Science, C. U. Shah Science College, Ashram Road, Ahmedabad, Gujarat, India

Human Facial Expression, JAFFE, fingerprint, face recognition, DNA, iris recognition, ICA, Principal Component Analysis, Linear Discriminant Analysis, PCA

  1. G. Donato, M.S. Bartlett, J.C. Hager, P. Ekman, T.J. Sejnowski, "Classifying Facial Actions", IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 21, No. 10, pp. 974-989, 1999
  2. Mehrabian.A, 1968. "Communication without Words", Psychology Today, Vo1.2, No.4, pp 53-56.
  3. M. Pantic, L.J.M. Rothkrantz, "Automatic Analysis of Facial Expressions: the State of the Art", IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 22, No.12, pp. 1424-1445, 2000
  4. B. Fasel, J. Luettin, "Automatic facial expression analysis: a survey", Pattern Recognition, Vol. 36, 2003, pp.259-275
  5. M. Pantic, J. M. Rothkrantz, "Automatic Analysis of Facial Expressions: The State of the Art", IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 22, 2000, pp.1424-1444.
  6. Essa, A. P. Pentland, "Coding, Analysis, Interpretation, and Recognition of Facial Expressions", IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 19, 1997, pp.757-763
  7. Jonathon Shlens." A Tutorial on Principal Component Analysis", Center for Neural Science, New York University, April 2009.
  8. G. R. S. Murthy, R.S.Jadon, "Effectiveness of Eigen spaces for Facial Expressions Recognition " International Journal of Computer Theory and Engineering, Vol. 1, No. 5, December, 2009,1793-8201
  9. B. Fasel, Juergen Luettin, Automatic facial expression analysis: a survey, Pattern Recognition, vol. 36, no. 1, pp. 259-275, January 2003
  10. Seyed Mehdi Lajevardi, Margaret Lech, "Averaged Gabor Filter Features for Facial Expression Recognition," Digital Image Computing: Techniques and Applications, pp. 71-76, 2008
  11. Bartlett, M.S.; Littlewort, G.; Frank, M.; Lainscsek, C.; Fasel, I.; Movellan, J., "Recognizing facial expression: machine learning and application to spontaneous behavior," Computer Vision and Pattern Recognition, 2005. IEEE Computer Society Conference on , vol.2, no., pp. 568-573 June 2005
  12. Daugman, J.G., "Two-dimensional spectral analysis of cortical receptive field profiles", Vision Res., vol 20 (10), pp. 847–56
  13. Lyons, M. Akamatsu, S. Kamachi, M. Gyoba, J. "Coding facial expressions with Gabor wavelets", Proceedings of the 3rd IEEE Int. Conf. on AFGR, Nara, Japan, pp 200-205, 1998.
  14. Zhang, Z., Lyons, M., Schuster, M., Akamatsu, S., 1998. "Comparison between geometry-based and Gabor wavelets-based facial expression recognition using multi-layer perceptron." Proceedings of the Third IEEE International Conference on Automatic Face and Gesture Recognition., 1998
  15. T. ACHARYA, A. K. RAY, "Image Processing – Principles and Applications", Wiley InterScience, 2005.

Publication Details

Published in : Volume 3 | Issue 5 | July-August 2017
Date of Publication : 2017-07-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 668-678
Manuscript Number : IJSRSET151124
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Uttam L. Patel, " Efficiency Improvement in Recognition of Human Facial Expression, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 3, Issue 5, pp.668-678, July-August-2017.
Journal URL : http://ijsrset.com/IJSRSET151124

Follow Us

Contact Us