Facial expression recognition in JAFFE dataset based on Gaussian process classification

IEEE Transactions on Neural Networks

Volumn 21, Issue 10, 2010, Pages 1685-1690

  Cheng, Fei ^a   Yu, Jiangsheng ^b   Xiong, Huilin ^c  

^a BEIJING JIAOTONG UNIVERSITY   (China)

^b PEKING UNIVERSITY   (China)

^c SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

Classification; facial expression recognition; Gaussian process model; kernel method

Indexed keywords

BAYESIAN METHODS; CLASSIFICATION; CROSS VALIDATION; DATA SETS; EXPRESSOR; FACIAL EXPRESSION RECOGNITION; FACIAL EXPRESSIONS; GAUSSIAN PROCESS; GAUSSIAN PROCESS MODEL; GAUSSIAN PROCESSES; GP MODELS; KERNEL METHODS; LEAVE-ONE-OUT CROSS VALIDATIONS; NOVEL METHODS; RECOGNITION RATES; SMALL SAMPLES;

BAYESIAN NETWORKS; CLASSIFICATION (OF INFORMATION); CLASSIFIERS; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); GESTURE RECOGNITION;

FACE RECOGNITION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOMETRY; FEMALE; HUMAN; JAPAN; METHODOLOGY; NORMAL DISTRIBUTION; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIOMETRIC IDENTIFICATION; FEMALE; HUMANS; JAPAN; MODELS, STATISTICAL; NORMAL DISTRIBUTION; PATTERN RECOGNITION, AUTOMATED;

EID: 77957765197     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2010.2064176     Document Type: Article

References (32)

1. P. Ekman and W. Friesen, Unmasking the Face. Englewood Cliffs, NJ: Prentice-Hall, 1975.
2. C. F. Shan, S. G. Gong, and P. W. McOwan, "Facial expression recognition based on local binary patterns: A comprehensive study", Image Vis. Comput., vol. 27, no. 6, pp. 803-816, May 2009.
3. A. K. Jain, P. W. Duin, and J. Mao, "Statistical pattern recognition: A review", IEEE Trans. Pattern Anal. Mach. Intell., vol. 22, no. 1, pp. 4-37, Jan. 2000.
4. M. J. Lyons, J. Budynek, and S. Akamatsu, "Automatic classification of single facial images", IEEE Trans. Pattern Anal. Mach. Intell., vol. 21, no. 12, pp. 1357-1362, Dec. 1999.
5. A. J. Calder, A. M. Burton, and P. Miller, "A principals component analysis of facial expressions", Vis. Res., vol. 41, no. 9, pp. 1179-1208, Apr. 2001.
6. I. Buciu, C. Kotropoulos, and I. Pitas, "ICA and gabor representation for facial expression recognition", IEEE ICIP, vol. 2, nos. 14-17, pp. 855-858, Sep. 2003.
7. W. M. Zheng, X. Y. Zhou, C. R. Zou, and L. Zhao, "Facial expression recognition using kernel canonical correlation analysis (KCCA)", IEEE Trans. Neural Netw., vol. 17, no. 1, pp. 233-238, Jan. 2006.
8. B. Fasel and J. Luettin, "Automatic facial expression analysis: A survey", Pattern Recogni., vol. 36, no. 1, pp. 259-275, Jan. 2003.
9. Y. Tian, T. Kanade, and J. F. Cohn, "Recognizing action units for facial expression analysis", IEEE Trans. Pattern Anal. Mach. Intell., vol. 23, no. 2, pp. 97-115, Feb. 2001.
10. C. F. Chuang and F. Y. Shih, "Recognizing facial action units using independent component analysis and support vector machine", Pattern Recognit., vol. 39, no. 9, pp. 1795-1798, 2006.
11. F. Y. Shih, C. F. Chuang, and P. S. P. Wang, "Performance comparisons of facial expression recognition in JAFFE database", Int. J. Pattern Recognit. Artificial Intell., vol. 22, no. 3, pp. 445-459, 2008.
12. T. Zhao, Z. Z. Liang, D. Zhang, and Q. Zou, "Interest filter vs. interest operator: Face recognition using fisher linear discriminant based on interest filter representation", Pattern Recognit. Lett., vol. 29, no. 13, pp. 1849-1857, Oct. 2008.
13. D. Liang, J. Yang, Z. L. Zheng, and Y. C. Chang, "A facial expression recognition system based on supervised locally linear embedding", Pattern Recognit. Lett., vol. 26, no. 15, pp. 2374-2389, Nov. 2005.
14. B. D. Ripley, Pattern Recognition and Neural Networks. Cambridge, U. K.: Cambridge Univ. Press, 1996.
15. C. M. Bishop, Neural Networks for Pattern Recognition. London, U. K.: Oxford Univ. Press, 1995.
16. R. M. Neal, "Bayesian learning for neural networks", in Lecture Notes in Statistics, vol. 118. New York: Springer-Verlag, 1996, p. 204.
17. T. Hofmann, B. Schölkoft, and A. J. Smola, "Kernel methods in machine learning", Ann. Statist., vol. 36, no. 3, pp. 1171-1220, 2008.
18. A. J. Smola and B. Schölkopf, "Bayesian kernel methods", in Advanced Lectures on Machine Learning: Machine Learning Summer School, S. Mendelson and A. J. Smola, Eds. New York: Spring-Verlag, 2002, pp. 65-117.
19. J. Lampinen and A. Vehtari, "Bayesian approach for neural networksreview and case studies", Neural Netw., vol. 14, no. 3, pp. 257-274, Apr. 2001.
20. C. E. Rasmussen and C. K. I. Williams, Gaussian Processes for Machine Learning. Cambridge, MA: MIT Press, 2006.
21. H. Nickisch and C. E. Rasmussen, "Approximations for binary Gaussian process classification", J. Mach. Learn. Res., vol. 9, pp. 2035-2078, Oct. 2008.
22. C. K. I. Williams and D. Barber, "Bayesian classification with Gaussian processes", IEEE Trans. Pattern Anal. Mach. Intell., vol. 20, no. 12, pp. 1342-1351, Dec. 1998.
23. B. Schölkoft and A. J. Smola, Learning with Kernels. Cambridge, MA: MIT Press, 2002.
24. W. Liu, J. C. Principe, and S. Haykin, Kernel Adaptive Filtering: A Comprehensive Introduction. New York: Wiley, 2010.
25. A. Gelman, J. B. Carlin, H. S. Stern, and D. B. Rubin, Bayesian Data Analysis, 2nd ed. Boston, MA: Chapman & Hall, 2004.
26. C. P. Robert and G. Casella, Monte Carlo Statistical Methods, 2nd ed. New York: Springer-Verlag, 2004.
27. R. M. Neal, "Monte Carlo implementation of Gaussian process models for Bayesian regression and classification", Dept. Comput. Sci., Univ. Toronto, ON, Canada, Tech. Rep. CRG-TR-97-2, 1997.
28. T. Jaakkola and M. I. Jordan, "Bayesian parameter estimation via variational methods", Statist. Comput., vol. 10, no. 1, pp. 25-37, Jan. 2000.
29. L. Tierney and J. Kadane, "Accurate approximations for posterior moments and marginal densities", J. Amer. Statist. Assoc., vol. 81, no. 393, pp. 82-86, Mar. 1986.
30. M. A. Tanner, Tools for Statistical Inference-Methods for the Exploration of Posterior Distributions and Likelihood Functions, 3rd ed. New York: Springer-Verlag, 1996.
31. C. R. Rao, Linear Statistical Inference and its Applications. New York: Wiley, 1973.
32. C. M. Bishop, Pattern Recognition and Machine Learning. New York: Springer-Verlag, 2006.