Facial expression recognition based on Local Binary Pattern features and Support Vector Machine

International Journal of Pattern Recognition and Artificial Intelligence

Volumn 28, Issue 6, 2014, Pages

  Cao, Nhan Thi ^a   Ton That, An Hoa ^a   Choi, Hyung Il ^a  

^a Soongsil University   (South Korea)

Author keywords

Computer vision; Facial expression recognition; Local Binary Pattern; Support Vector Machine

Indexed keywords

COMPUTER VISION; GESTURE RECOGNITION; SUPPORT VECTOR MACHINES;

FACE IMAGES; FACIAL EXPRESSION RECOGNITION; FACIAL EXPRESSIONS; INTELLIGENT COMMUNICATION; LBP FEATURES; LOCAL BINARY PATTERNS; NON-OVERLAP; PRE-PROCESSING STEP;

FACE RECOGNITION;

EID: 84929285055     PISSN: 02180014     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0218001414560126     Document Type: Article

References (72)

1. T. Ahonen, A. Hadid and M. Pietikainen, Face recognition with local binary patterns, European Conf. Computer Vision, eds. T. Pajdla and J. Matas (Springer-Verlag Berlin Heidelberg, 2004), pp. 469-481.
2. T. Ahsan, T. Jabid and U.-P. Chong, Facial expression recognition using local transitional pattern on Gabor filtered facial images, IETE Tech. Rev. 30 (1) (2013) 47-52.
3. N. Aifanti, C. Papachristou and A. Delopoulos, The MUG facial expression database, in Proc. 11th Int. Workshop on Image Analysis for Multimedia Interactive Services, Desenzano, Italy (2010), pp. 1-4.
4. M. S. Bartlett, G. Littlewort, I. Fasel and J. R. Movellan, Real time face detection and facial expression recognition: Development and application to human-computer interaction, in Proc. IEEE Conf. Computer Vision and Pattern Recognition (2003), pp. 53-58.
5. M. S. Bartlett, G. Littlewort, M. Frank, C. Lainscsek, I. Fasel and J. Movellan, Recognizing facial expression: Machine learning and application to spontaneous behavior, in Proc. IEEE Conf. Computer Vision and Pattern Recognition, Vol. 2(2005), pp. 568-573.
6. M. S. Bartlett, G. Littlewort, C. Lainscsek, I. Fasel and J. Movellan, Machine learning methods for fully automatic recognition of facial expressions and facial actions, in Proc. IEEE Int. Conf. Systems, Man and Cybernetics, Vol. 1(2004), pp. 592-597.
7. M. S. Bartlett, J. R. Movellan and T. J. Sejnowski, Face recognition by independent component analysis, IEEE Trans. Neural Netw. 13 (6) (2002) 1450-1464.
8. P. N. Belhumeur, J. P. Hespanha and D. J. Kriegman, Eigenfaces vs. fisherfaces: Recognition using class specific linear projection, IEEE Trans. Pattern Anal. Mach. Intell. 19 (9) (1997) 711-720.
9. I. Buciu and I. Pitas, Application of non-negative and local non negative matrix factorization to facial expression recognition, in Proc. 17th Int. Conf. Pattern Recognition, Cambridge, UK, Vol. 1, August 2004, pp. 288-291.
10. C.-C. Chang and C.-J. Lin, LIBSVM: A library for support vector machines, ACM Trans. Intell. Syst. Technol. 2 (3) (2011) 27:1-27:27.
11. C.-C. Chang and C.-J. Lin, LIBSVM: A library for support vector machines, ACM Trans. Intell. Syst. Technol. 2 (3) (2011), Updated version, Available at http://www.csie.ntu.edu.tw/~cjlin/papers/libsvm.pdf (accessed on march 2013).
12. T.-H. Chueh, T.-B. Chen, H. H.-S. Lu, S.-S. Ju, T.-H. Tao and J.-H. Shaw, Statistical prediction of emotional states by physiological signals with manova and machine learning, Int. J. Patt. Recogn. Artif. Intell. 26 (4) (2012) 1250008-1-1250008-18.
13. I. Cohen, N. Sebe, F. G. Cozman, M. C. Cirelo and T. S. Huang, Learning Bayesian network classifiers for facial expression recognition using both labeled and unlabeled data, in Proc. IEEE Conf. Computer Vision and Pattern Recognition, Vol. 1(2003), pp. 595-601.
14. I. Cohen, N. Sebe, A. Garg, L. Chen and T. S. Huang, Facial expression recognition from video sequences: Temporal and static modeling, Comput. Vis. Image Understand. 91 (1-2) (2003) 160-187.
15. C. Cortes and V. Vapnik, Support-vector networks, Machine Learn. 20 (3) (1995) 273-297.
16. G. Donato, M. S. Bartlett, J. C. Hager, P. Ekman and T. J. Sejnowski, Classifying facial actions, IEEE Trans. Pattern Anal. Mach. Intell. 21 (10) (1999) 974-989.
17. I. Essa and A. Pentland, Coding, analysis, interpretation, and recognition of facial expressions, IEEE Trans. Pattern Anal. Mach. Intell. 19 (7) (1997) 757-763.
18. M. R. Everingham and A. Zisserman, Regression and classification approaches to eye localization in face images, IEEE Int. Conf. Automatic Face and Gesture Recognition (2006), pp. 441-446.
19. B. Fasel and J. Luettin, Automatic facial expression analysis: A survey, Pattern Recogn. 36 (2003) 259-275.
20. X. Feng, A. Hadid and M. Pietikainen, A coarse-to-fine classification scheme for facial expression recognition, Int. Conf. Image Analysis and Recognition, eds. A. Campilho and M. Kamel (Springer-Verlag, Berlin Heidelberg, 2004), pp. 668-675.
21. X. Feng, M. Pietikäinen and A. Hadid, Facial expression recognition based on local binary patterns, Pattern Recogn. Image Anal. 17 (4) (2007) 592-598.
22. A. Hadid, M. Pietikainen and T. Ahonen, A discriminative feature space for detecting and recognizing faces, in Proc. IEEE Conf. Computer Vision and Pattern Recognition, Vol. 2(2004), pp. 797-804.
23. L. He, X. Wang, C. Yu and K. Wu, Facial expression recognition using embedded hidden Markov model, IEEE Int. Conf. Systems, Man and Cybernetics, October 2009, pp. 1568-1572.
24. J. Hoey and J. J. Little, Value directed learning of gestures and facial displays, in Proc. IEEE Conf. Computer Vision and Pattern Recognition, Vol. 2(2004), pp. 1026-1033.
25. C.-C. Hsieh and M.-K. Jiang, A facial expression classification system based on active shape model and support vector machine, IEEE Int. Symp. Computer Science and Society (2011), pp. 311-314.
26. C.-W. Hsu, C.-C. Chang and C.-J. Lin, A practical guide to support vector classification, Tech. Rep., Department of Computer Science, National Taiwan University, Taipei (2010).
27. Y. Ji and K. Idrissi, Automatic facial expression recognition based on spatiotemporal descriptors, Pattern Recogn. Lett. 33 (10) (2012) 1373-1380.
28. R. E. Kaliouby and P. Robinson, Real-time inference of complex mental states from facial expressions and head gestures, in Proc. IEEE Conf. Computer Vision and Pattern Recognition (2004), pp. 154-159.
29. T. Kanade, J. F. Cohn and Y. Tian, Comprehensive database for facial expression analysis, in Proc. 4th IEEE Int. Conf. Automatic Face and Gesture Recognition, France (2000), pp. 46-53.
30. R. A. Khan, A. Meyer, H. Konik and S. Bouakaz, Framework for reliable, real-time facial expression recognition for low resolution images, Pattern Recogn. Lett. 34 (10) (2013) 1159-1168.
31. H. Kobayashi and F. Hara, Recognition of six basic facial expression and their strength by neural network, in Proc. IEEE Int. Workshop on Robot and Human Communication (1992), pp. 381-386.
32. I. Kotsia and I. Pitas, Facial expression recognition in image sequences using geometric deformation features and support vector machines, IEEE Trans. Image Process. 16 (1) (2007) 172-187.
33. X. Li and Q. Ji, Active affective state detection and user assistance with dynamic Bayesian networks, IEEE Trans. Syst., Man, Cybern. A, Syst. Hum. 35 (1) (2005) 93-105.
34. S. Liao, W. Fan, A. C. S. Chung and D. Y. Yeung, Facial expression recognition using advanced local binary patterns, tsallis entropies and global appearance features, IEEE Int. Conf. Image Processing (2006), pp. 665-668.
35. D.-T. Lina and D.-C. Pan, Integrating a mixed-feature model and multiclass support vector machine for facial expression recognition, Integr. Comput.-Aided Eng. 16 (1) (2009) 61-74.
36. C. L. Lisetti and D. E. Rumelhart, Facial expression recognition using a neural network, in Proc. 11th Int. Florida Artificial Intelligence Research Society Conf., Florida (1998), pp. 328-332.
37. G. Littlewort, M. Bartlett, I. Fasel, J. Susskind and J. Movellan, Dynamics of facial expression extracted automatically from video, Image Vis. Comput. 24 (6) (2006) 615-625.
38. P. Lucey, J. F. Cohn, T. Kanade, J. Saragih and Z. Ambadar, The extended Cohn-Kanade dataset (CK+): A complete dataset for action unit and emotion-specified expression, IEEE Conf. Computer Vision and Pattern Recognition Workshops (2010), pp. 94-101.
39. M. J. Lyons, J. Budynek and S. Akamatsu, Automatic classification of single facial images, IEEE Trans. Pattern Anal. Mach. Intell. 21 (12) (1999) 1357-1362.
40. A. Majumder, L. Behera and V. K. Subramanian, Emotion recognition from geometric facial features using self-organizing map, Pattern Recogn. 47 (3) (2014) 1282-1293.
41. B. W. Miners and O. A. Basir, Dynamic facial expression recognition using fuzzy hidden Markov models, in Proc. IEEE Int. Conf. Systems, Man and Cybernetics (2005), pp. 1417-1422.
42. T. Ojala, M. Pietikainen and D. Harwood, A comparative study of texture measures with classification based on featured distribution, Pattern Recogn. 29 (1) (1996) 51-59.
43. T. Ojala, M. Pietikainen and T. Maenpaa, Multiresolution gray-scale and rotation invariant texture classification with local binary patterns, IEEE Trans. Pattern Anal. Mach. Intell. 24 (7) (2002) 971-987.
44. C. Padgett and G. Cottrell, Representing face images for emotion classification, in Proc. Advanced in Neural Information Processing Systems 9(1996), pp. 894-900.
45. M. Pantic and I. Patras, Dynamics of facial expression: Recognition of facial actions and their temporal segments from face profile image sequences, IEEE Trans. Syst., Man, Cybern. 36 (2) (2006) 433-449.
46. M. Pantic and L. J. M. Rothkrantz, Automatic analysis of facial expressions: The state of art, IEEE Trans. Pattern Anal. Mach. Intell. 22 (12) (2000) 1424-1445.
47. M. Pantic and L. J. M. Rothkrantz, Expert system for automatic analysis of facial expression, Image Vis. Comput. 18 (11) (2000) 881-905.
48. M. Pantic and L. J. M. Rothkrantz, Facial action recognition for facial expression analysis from static face images, IEEE Trans. Syst., Man, Cybern. 34 (3) (2004) 1449-1461.
49. O. Rudovic, M. Pantic and I. Patras, Coupled Gaussian processes for pose-invariant facial expression recognition, IEEE Trans. Pattern Anal. Mach. Intell. 35 (6) (2013) 1357-1369.
50. M. Schmidt, M. Schels and F. Schwenker, A hidden Markov model based approach for facial expression recognition in image sequences, in Proc. 4th IAPR TC3 Conf. Artificial Neural Networks in Pattern Recognition (ANNPR 2010), eds. F. Schwenker and N. El Gayar (Springer-Verlag Berlin Heidelberg, 2010), pp. 149-160.
51. N. Sebe, M. S. Lew, Y. Sun, I. Cohen, T. Gevers and T. S. Huang, Authentic facial expression analysis, Image Vis. Comput. 25 (2007) 1856-1863.
52. C. Shan and T. Gritti, Learning discriminative LBP-histogram bins for facial expression recognition, in Proc. British Machine Vision Conf. (2008), pp. 27.1-27.10.
53. C. Shan, S. Gong and P. W. McOwan, Appearance manifold of facial expression, ICCV Workshop on Human-Computer Interaction, eds. N. Sebe, M. S. Lew, T. S. Huang (Springer-Verlag Berlin Heidelberg, 2005), pp. 221-230.
54. C. Shan, S. Gong and P. W. McOwan, Robust facial expression recognition using local binary patterns, IEEE Int. Conf. Image Processing, Genoa, Vol. 2(2005), pp. 370-373.
55. C. Shan, S. Gong and P. W. McOwan, Facial expression recognition based on local binary patterns: A comprehensive study, Image Vis. Comput. 27 (2009) 803-816.
56. F. Y. Shih, C.-F. Chuang and P. S. P. Wang, Performance comparisons of facial expression recognition in JAFFE database, Int. J. Pattern Recogn. Artif. Intell. 22 (3) (2008) 445-459.
57. A. S. M. D. Sohail and P. Bhattacharya, Classifying facial expressions using level set method based lip contour detection and multi-class support vector machines, Int. J. Pattern Recogn. Artif. Intell. 25 (6) (2011) 835-862.
58. H. Tang, H.-J. Mark and T. Huang, Non-frontal view facial expression recognition based on ergodic hidden Markov model supervectors, IEEE Int. Conf. Multimedia and Expo. (2010), pp. 1202-1207.
59. Y.-L. Tian, Evaluation of face resolution for expression analysis, in Proc. IEEE Conf. Computer Vision and Pattern Recognition Workshop (CVPRW'04), June 2004, pp. 82-88.
60. Y.-L. Tian, T. Kanade and J. Cohn, Recognizing action units for facial expression analysis, IEEE Trans. Pattern Anal. Mach. Intell. 23 (2) (2001) 97-115.
61. Y.-L. Tian, T. Kanade and J. F. Cohn, Facial expression analysis, in Handbook of Face Recognition, Chap. 11 (Springer, Heidelberg, 2005).
62. M. Turk and A. P. Pentland, Face recognition using eigenfaces, in Proc. IEEE Conf. Computer Vision and Pattern Recognition (1991), pp. 586-591.
63. M. Valstar and M. Pantic, Fully automatic facial action unit detection and temporal analysis, in Proc. IEEE Conf. Computer Vision and Pattern Recognition Workshop (CVPRW'06), June 2006, pp. 149-156.
64. M. Valstar, I. Patras and M. Pantic, Facial action unit detection using probabilistic actively learned support vector machines on tracked facial point data, in Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR'05) (2005), pp. 76-84.
65. V. N. Vapnik, An overview of statistical learning theory, IEEE Trans. Neural Netw. 10 (5) (1999) 988-999.
66. P. Viola and M. Jones, Robust real-time face detection, Int. J. Comput. Vis. 57 (2) (2004) 137-154.
67. Y. Yacoob and L. S. Davis, Recognizing human facial expression from long image sequences using optical flow, IEEE Trans. Pattern Anal. Mach. Intell. 18 (6) (1996) 636-642.
68. M. Yeasin, B. Bullot and R. Sharma, From facial expression to level of interests: A spatiotemporal approach, IEEE Conf. Computer Vision and Pattern Recognition, Vol. 2(2004), pp. 922-927.
69. Z. Ying, L. Cai, J. Gan and S. He, Facial expression recognition with local binary pattern and laplacian eigenmaps, Int. Conf. Intelligent Computing, eds. D. S. Huang et al. (Springer Berlin Heidelberg, 2009), pp. 228-235.
70. Y. Zhang and Q. Ji, Active and dynamic information fusion for facial expression understanding from image sequences, IEEE Trans. Pattern Anal. Mach. Intell. 27 (5) (2005) 1-16.
71. Z. Zhang, M. J. Lyons, M. Schuster and S. Akamatsu, Comparison between geometrybased and Gabor-wavelets-based facial expression recognition using multi-layer perceptron, in Proc. 3rd IEEE Int. Conf. Automatic Face and Gesture Recognition (1998), pp. 454-459.
72. X. Zhao and S. Zhang, Facial expression recognition using local binary patterns and discriminant kernel locally linear embedding, EURASIP J. Adv. Signal Process. 2012 (1) (2012), pp. 1-9.