A remarkable standard for estimating the performance of 3D facial expression features

Neurocomputing

Volumn 82, Issue , 2012, Pages 99-108

  Li, Xiaoli ^a   Ruan, Qiuqi ^a   Ming, Yue ^a  

^a BEIJING JIAOTONG UNIVERSITY   (China)

Author keywords

3D facial expression recognition; Discrimination power; KL divergence; Performance evaluation; Relative entropy

Indexed keywords

3-D FACIAL EXPRESSION RECOGNITION; DISCRIMINATION POWER; KL-DIVERGENCE; PERFORMANCE EVALUATION; RELATIVE ENTROPY;

ENTROPY; FEATURE EXTRACTION; GESTURE RECOGNITION; STANDARDS; THREE DIMENSIONAL;

FACE RECOGNITION;

3 DIMENSIONAL FACIAL EXPRESSION RECOGNITION; ARTICLE; AUTOMATED PATTERN RECOGNITION; DATA BASE; DISCRIMINATION POWER; ENTROPY; EYE; EYEBROW; FACE CONTOUR; FACE PROFILE; FACIAL EXPRESSION; FEMALE; HUMAN; KULLBACK LEIBLER DIVERGENCE; MALE; MOUTH; NOSE; PRIORITY JOURNAL; RECOGNITION;

EID: 84862801138     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2011.10.029     Document Type: Article

References (32)

1. Shan C., Gong S., McOwan W. Facial expression recognition based on local binary patterns: a comprehensive study. Image Vision Comput. 2008, 27(6):803-816.
2. Song M., Tao D., Liu Z., Li X., Zhou M. Image ratio features for facial expression recognition application. IEEE Trans. Syst. Man Cybern. 2010, 40(3):779-788.
3. Xiao R., Zhao Q., Zhang D., Shi P. Facial expression recognition on multiple manifolds. Pattern Recognition 2011, 44(1):107-116.
4. X. Li, Q. Ruan, C. Ruan, Facial expression recognition with local Gabor filters, in: Proceedings of the 10th International Conference on Signal Processing, 2010, pp. 1013-1016.
5. Zhi R., Ruan Q. Facial expression recognition based on two-dimensional discriminant locality preserving projections. Neurocomputing 2008, 71(7):1730-1734.
6. Zhu Y., De Silva L.C., Ko C.C. Using moment invariants and HMM in facial expression recognition. Pattern Recognition Lett. 2002, 23(1-3):83-91.
7. Cohn I., Sebe N., Garg A., Chen L.S., Huang T.S. Facial expression recognition from video sequences: temporal and static modeling. Comput. Vision Image Understanding 2003, 91(1-2):160-187.
8. M.S. Bartlett, G. Littlewort, I. Fasel, J.R. Movellan, Real time face detection and facial expression recognition: development and applications to human computer interaction, in: Proceedings of the 2003 Conference on Computer Vision and Pattern Recognition Workshop, 2003, pp. 53-58.
9. Tian Y.L., Kanade T., Cohn J.F. Facial expression analysis. Handbook of Face Recognition 2005, 247-276. Springer-Verlag, New York. S.Z. Li, A.K. Jain (Eds.).
10. L. Yin, X. Wei, Y. Sun, J. Wang, M.J. Rosato, A 3D facial expression database for facial behavior research, in: Proceedings of the Seventh International Conference on Automatic Face and Gesture Recognition, 2006, pp. 211-216.
11. Russell J. Is there universal recognition of emotion from facial expression?. Psychol. Bull. 1994, 115(1):102-141.
12. U. Tekguc, H. Soyel, H. Demirel, Feature selection for person-independent 3D facial expression recognition using NSGA-II, in: Proceedings of 24th International Symposium on Computer and Information Sciences, 2009, pp. 35-38.
13. L. Zalewski, S. Gong, Synthesis and recognition of facial expressions in virtual 3d views, in: Proceedings of the Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004, pp. 493-498.
14. Z. Wen, T.S. Huang, Capturing subtle facial motions in 3d face tracking, in: Proceedings of the Ninth IEEE International Conference on Computer Vision, 2003, pp. 1343-1350.
15. Tao D., Song M., Li X., Shen J., Sun J., Wu X., Faloutsos C., Maybank S.J. Bayesian tensor approach for 3-D facial modeling. IEEE Trans. Circuits Syst. Video Technol. 2008, 18(10):1397-1410.
16. J. Wang, L. Yin, X. Wei, Y. Sun, 3D facial expression recognition based on primitive surface feature distribution, in: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision Pattern Recognition, 2006, pp. 1399-1406.
17. H. Soyel, H. Demirel, Facial expression recognition using 3D facial feature distances, in: Proceedings of International Conference on Image Analysis and Recognition, 2007, pp. 831-838.
18. H. Soyel, H. Demirel, 3D facial expression recognition with geometrically localized facial features, in: Proceedings of 23rd International Symposium on Computer and Information Sciences, 2008, pp. 1-4.
19. H. Tang, T.S. Huang, 3D facial expression recognition based on automatically selected features, in: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008, pp. 1-8.
20. H. Tang, T.S. Huang, 3D facial expression recognition based on properties of line segments connecting facial feature points, in: Proceedings of the Eighth IEEE International Conference on Automatic Face & Gesture Recognition, 2008, pp. 1-6.
21. Venkatesh Y.V., Kassim A.A., Murthy O.V.R. A novel approach to classification of facial expressions from 3D-mesh datasets using modified PCA. Pattern Recognition Lett. 2009, 30(12):1128-1137.
22. Y.V. Venkatesh, A.K. Kassim, O.V.R. Murthy, Resampling approach to facial expression recognition using 3D meshes, in: Proceedings of the 20th International Conference on Pattern Recognition, 2010, pp. 3772-3775.
23. Sha T., Song M., Bu J., Chen C., Tao D. Feature level analysis for 3D facial expression recognition. Neurocomputing 2011, 74:2135-2141.
24. Levy B.C., Nikoukhah R. Robust least-squares estimation with a relative entropy constraint. IEEE Trans. Inf. Theory 2004, 50(1):89-104.
25. Chang C.-I., Du Y., Wang J., Guo S.-M., Thouin P.D. Survey and comparative analysis of entropy and relative entropy thresholding techniques. IEEE Proc. Vision Image Signal Process. 2006, 837-850.
26. Kullback S. The Kullback-Leibler distance. Am. Stat. 1987, 41:340-341.
27. Belhumeur P.N., hespanha J.P., Kriegman D.J. Eigenfaces vs. fisherfaces: recognition using class specific linear projection. IEEE Trans. Pattern Anal. Mach. Intell. 1997, 19(7):711-720.
28. Martinez A.M., Kak A.C. PCA versus LDA. IEEE Trans. Pattern Anal. Mach. Intell. 2001, 23(2):228-233.
29. Song M., Dong Z., Theobalt C., Wang H., Liu Z., Seidel H.P. A generic framework for efficient 2D and 3D facial expression analogy. IEEE Trans. Multimedia 2007, 9(7):1384-1395.
30. Tao D., Li X., Wu X., Maybank S.J. Geometric mean for subspace selection. IEEE Trans. Pattern Anal. Mach. Intell. 2009, 31(2):260-274.
31. D. Tao, X. Li, X. Wu, S.J. Maybank, General averaged divergence analysis, in: Proceedings of the Seventh IEEE International Conference on Data Mining, 2007, pp. 302-311.
32. X. Li, Q. Ruan, Y. Ming, 3D facial expression recognition based on basic geometric features, in: Proceedings of the 10th International Conference on Signal Processing, 2010, pp. 1366-1369.