Integrating a mixed-feature model and multiclass support vector machine for facial expression recognition

Integrated Computer-Aided Engineering

Volumn 16, Issue 1, 2009, Pages 61-74

  Lin, Daw Tung ^a   Pan, De Cheng ^a  

^a NATIONAL TAIPEI UNIVERSITY   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

DATABASE SYSTEMS; GESTURE RECOGNITION; HUMAN COMPUTER INTERACTION; IMAGE RETRIEVAL; INTERFACES (COMPUTER); KNOWLEDGE MANAGEMENT; MACHINE DESIGN; PRINCIPAL COMPONENT ANALYSIS; SUPPORT VECTOR MACHINES; VECTORS;

ANALYTICAL RESULTS; AUTOMATIC FACIAL EXPRESSION ANALYSIS; AUTOMATIC RECOGNITION SYSTEMS; BENCHMARK DATABASES; DECISION DIRECTED ACYCLIC GRAPHS; DISCRIMINATION MODELS; FACIAL EXPRESSION RECOGNITIONS; FACIAL EXPRESSIONS; FEATURE MODELS; HUMAN FACIAL EXPRESSIONS; HUMAN-COMPUTER INTERACTIONS; INTERFACE DESIGNS; LOCAL BINARY PATTERNS; LOCAL TEXTURES; MULTICLASS SUPPORT VECTOR MACHINES; NEW MODALITIES; PRINCIPAL COMPONENTS; STATIC IMAGES; SUPPORT VECTORS;

FACE RECOGNITION;

EID: 58149494499     PISSN: 10692509     EISSN: None     Source Type: Journal    
DOI: 10.3233/ICA-2009-0304     Document Type: Article

References (39)

1. The Yale Face Database, http://cvc.yale.edu/projects/yalefaces/yalefaces. html.
2. T. Ahonen, A. Hadid and M. Pietikäinen, Face recognition with local binary patterns, in: Proceedings of the European Conference on Computer Vision, T. Pajdla and J. Matas, eds, (vol. 3021) (2004), pp. 469-481.
3. P.S. Aleksic and A.K. Katsaggelos, Automatic facial expression recognition using facial animation parameters and multi-stream HMMs, IEEE Trans. on Information Forensics and Security 1(1) (2006), 3-11.
4. M. Amin, N. Afzulpurkar, M. Dailey and V. Esichaikul, Fuzzy-C-mean determines the principle component pairs to estimate the degree of emotion from facial. In Proceedings of the 2nd International Conference on Fuzzy Systems and Knowledge Discovery, volume 1, 2005, p. 484.
5. I. Buciu, I. Kotsia and I. Pitas, Facial expression analysis under partial occlusion, In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005, 453-456.
6. I. Buciu and I. Pitas, Application of non-negative and local non-negative matrix factorization to facial expression recognition. In Proceedings of the 17th International Conference on Pattern Recognition, volume 1, Aug. 2004, 288-291.
7. J. Canny, A computational approach to edge detection, IEEE Trans. on Pattern Analysis and Machine Intelligence 6(8) (1986), 679-698.
8. H.Y. Chen, C.L. Huang and C.M. Fu, Hybrid-boost learning for multi-pose face detection and facial expression recognition, Pattern Recognition 41(3) (2008), 1173-1185.
9. I. Cohen, F.G. Cozman, N. Sebe, M.C. Cirelo and T.S. Huang, Semi-supervised learning of classifiers: Theory, algorithms, and their application to human-computer interaction, IEEE Trans. on Pattern Analysis and Machine Intelligence (2004), 1553-1567.
10. I. Cohen, N. Sebe, A. Garg, L.S. Chen and T.S. Huang, Facial expression recognition from video sequences: temporal and static modeling, Computer Vision and Image Understanding 91(1-2) (2003), 160-187.
11. I. Cohen, N. Sebe, F.G. Gozman, M.C. Cirelo and T.S. Huang, Learning Bayesian network classifiers for facial expression recognition both labeled and unlabeled data. In Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, volume 1, 2003, 595-601.
12. D. Datcu and L. Rothkrantz, Facial expression recognition with relevance vector machines. In Proceedings of the IEEE International Conference on Multimedia and Expo, July 2005, 193-196.
13. X. Feng, Facial expression recognition based on local binary patterns and coarse-to-fine classification. In Proceedings of the Fourth International Conference on Computer and Information Technology, 178-183, September 2004.
14. X. Feng, M. Pietikainen and A. Hadid, Facial expression recognition with local binary patterns and linear programming, Pattern Recognition and Image Analysis 15(2) (2005), 546-548.
15. N. Fragopanagos and J. Taylor, Emotion recognition in human-computer interaction, Neural Networks 18(4) (2005), 389-405.
16. J. Friedman, Another approach to polychotomous classification, Technical report. Department of Statistics, Standford University, 1996.
17. A. Geetha, V. Ramalingam, S. Palanivel and B. Palaniappan, Facial expression recognition - a real time approach. Expert Systems with Applications, 2007. doi: 10.1016/j.eswa.2007.09.002.
18. L. He, J. Zhou, D. Hu, C. Zou and L. Zhao, Boosted independent features for face expression recognition. In Proceedings of the Second International Symposium on Neural Networks, May 2005, 137-145.
19. L. He, C. Zou, L. Zhao and D. Hu, An enhanced LBP feature based on facial expression recognition, In Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, pages 3300-3303, September 2005.
20. Z. Jin, F. Davoine and Z. Lou, Facial expression analysis by using KPCA, In Proceedings of 2003 IEEE International Conference on Robotics Intelligent Systems and Signal Processing, volume 2, October 2003, 736-741.
21. T. Kanade, J. Cohn and Y. Tian, Comprehensive database for facial expression analysis. In International Conference on Automatic Face and Gesture Recognition, 2000, 46-53.
22. C.S. Lee and A. Elgammal, Nonlinear Shape and Appearance Models for Facial Expression Analysis and Synthesis. In Proceedings of the 18th International Conference on Pattern Recognition, volume 1, 2006, 497-502.
23. D.-T. Lin. Human facial expression recognition using hybrid network of PCA and RBFN, Lecture Notes on Computer Science 4132 (2006), 624-633.
24. W.F. Liu and Z.F. Wang, Facial expression recognition based on fusion of multiple Gabor features, In Proceedings of the 18th International Conference on Pattern Recognition, volume 3, August 2006, 536-539.
25. M. Lyons, J. Budynek and S. Akamatsu, Automatic classification of single facial images, IEEE Trans. on Pattern Analysis and Machine Intelligence 21(12) December 1999, 1357-1362.
26. M. J. Lyons, S. Akamatsu, M. Kamachi and J. Gyoba, Coding facial expressions with Gabor wavelets, In Proceedings of the Third IEEE International Conference on Automatic Face and Gesture Recognition, pages 200-205, April 1998.
27. D. Makris and T Botley, Facial expression recognition from still images, http://stffnet.kingston.ac.uk/~ku32195/FacialExpression.html, 2005.
28. M. Pantic and L. Rothkrantz, Automatic analysis of facial expressions: the state of the art, IEEE Trans. on Pattern Analysis and Machine Intelligence 22(12) (2000), 1424-1445.
29. J. Platt, N. Cristianini and J. Shawe-Taylor, Large margin DAGs for multiclass classification, in: Proceedings of the Advances in Neural Information Processing Systems, S.A. Solla, T.K. Leen and K.-R. Müller, eds, 2000, pp. 547-553.
30. N. Sebe, M.S. Lew, Y. Sun, I. Cohen, T. Gevers and T.S. Huang, Authentic facial expression analysis, Image and Vision Computing 25 (2007), 1856-1863.
31. C. Shan, S. Gong and P. McOwan, Robust facial expression recognition using local binary patterns, In IEEE International Conference on Image Processing (volume II), 2005, 370-373.
32. Y. Shinohara and N. Otsu, Facial expression recognition using Fisher weight maps. In Proceedings of the Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004, 499-504.
33. W. Sun and Q. Ruan, Two-Dimension PCA for Facial Expression Recognition, In Proceedings of the 8th International Conference on Signal Processing, volume 3, 2006.
34. M. Pietikäinen T. Ojala and T. Mäenpää, Multi-resolution gray-scale and rotation invariant texture classification with local binary patterns, IEEE Trans. on Pattern Analysis and Machine Intelligence 24(7) (2002), 971-987.
35. N. Tottenham, A. Borscheid, K. Ellertsen, D. Marcus and C. Nelson, Categorization of facial expressions in children and adults: establishing a larger stimulus, Journal of Cognitive Neuroscience 14 (2002), S74.
36. M. Visani, C. Garcia and C. Laurent, Comparing robustness of two-dimensional PCA and Eigenfaces for face recognition. In Proceedings of the International Conference on Image Analysis and Recognition, 2003, 717-724.
37. J. Wang and L. Yin, Static topographic modeling for facial expression recognition and analysis, Computer Vision and Image Understanding 108 (2007), 19-34.
38. Y. Wang, H. Ai, B. Wu and C. Huang, Real time facial expression recognition with Adaboost. In Proceedings of the 17th International Conference on Pattern Recognition, volume 3, Aug. 2004, pp. 926-929.
39. J. Yang, D. Zhang, A. Frangi and J.-Y. Yang, Two-dimensional PCA: a new approach to appearance-based face representation and recognition, IEEE Trans. on Pattern Analysis and Machine Intelligence 26(1) (2004), 131-137.