Learning expressionlets on spatio-temporal manifold for dynamic facial expression recognition

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2014, Pages 1749-1756

  Liu, Mengyi ^a,b   Shan, Shiguang ^a   Wang, Ruiping ^a   Chen, Xilin ^a,c  

^a INSTITUTE OF COMPUTING TECHNOLOGY   (China)

^b UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

^c UNIVERSITY OF OULU   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

SEMANTICS;

DISCRIMINANT EMBEDDING; DISCRIMINATIVE POWER; DYNAMIC FACIAL EXPRESSION; DYNAMIC REPRESENTATION; EXPRESSION RECOGNITION; LOW-LEVEL FEATURES; MID-LEVEL REPRESENTATION; TEMPORAL ALIGNMENT;

FACE RECOGNITION;

EID: 84911447595     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2014.226     Document Type: Conference Paper

References (35)

1. V. Arsigny, P. Fillard, X. Pennec, and N. Ayache. Geometric means in a novel vector space structure on symmetric positive-definite matrices. SIAM Journal on Matrix Analysis and Applications, 29(1):328-347, 2007.
2. S. W. Chew, P. Lucey, S. Lucey, J. Saragih, J. F. Cohn, and S. S-ridharan. Person-independent facial expression detection using constrained local models. In FG, 2011.
3. S. W. Chew, S. Lucey, P. Lucey, S. Sridharan, and J. F. Conn. Improved facial expression recognition via uni-hyperplane classification. In CVPR, 2012.
4. G. Csurka, C. Dance, L. Fan, J. Willamowski, and C. Bray. Visual categorization with bags of keypoints. In ECCVW, 2004.
5. A. Dhall, R. Goecke, J. Joshi, M. Wagner, and T. Gedeon. Emotion recognition in the wild challenge 2013. In ICMI, 2013.
6. A. Dhall, R. Goecke, S. Lucey, and T. Gedeon. Collecting large, richly annotated facial-expression databases from movies. IEEE MultiMedia, 19(3):0034, 2012.
7. P. Ekman and W. V. Friesen. Facial action coding system: a technique for the measurement of facial movement. Consulting Psychologists Press, 1978.
8. R.-E. Fan, K.-W. Chang, C.-J. Hsieh, X.-R. Wang, and C.-J. Lin. Liblinear: A library for large linear classification. JMLR, 9:1871-1874, 2008.
9. Y. Guo, G. Zhao, and M. Pietikäinen. Dynamic facial expression recognition using longitudinal facial expression atlases. In ECCV, 2012.
10. T. Hasan and J. H. Hansen. A study on universal background model training in speaker verification. IEEE T ASLP, 19(7):1890-1899, 2011.
11. X. Hong, H. Chang, S. Shan, X. Chen, and W. Gao. Sigma set: A small second order statistical region descriptor. In CVPR, 2009.
12. S. Jain, C. Hu, and J. K. Aggarwal. Facial expression recognition with temporal modeling of shapes. In ICCVW, 2011.
13. T. Kanade, J. F. Cohn, and Y. Tian. Comprehensive database for facial expression analysis. In FG, 2000.
14. A. Klaser and M. Marszalek. A spatio-temporal descriptor based on 3d-gradients. In BMVC, 2008.
15. Q. V. Le, W. Y. Zou, S. Y. Yeung, and A. Y. Ng. Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis. In CVPR, 2011.
16. H. Li, G. Hua, Z. Lin, J. Brandt, and J. Yang. Probabilistic elastic matching for pose variant face verification. In CVPR, 2013.
17. G. Littlewort, J. Whitehill, T. Wu, I. Fasel, M. Frank, J. Movellan, and M. Bartlett. The computer expression recognition toolbox (cert). In FG, 2011.
18. M. Liu, S. Li, S. Shan, and X. Chen. Au-aware deep networks for facial expression recognition. In FG, 2013.
19. P. Lucey, J. F. Cohn, T. Kanade, J. Saragih, Z. Ambadar, and I. Matthews. The extended cohn-kanade dataset (ck+): A complete dataset for action unit and emotion-specified expression. In CVPRW, 2010.
20. M. Pantic and L. J. M. Rothkrantz. Automatic analysis of facial expressions: The state of the art. IEEE T PAMI, 22(12):1424-1445, 2000.
21. R. Ptucha, G. Tsagkatakis, and A. Savakis. Manifold based sparse representation for robust expression recognition without neutral subtraction. In ICCVW, 2011.
22. A. Sanin, C. Sanderson, M. T. Harandi, and B. C. Lovell. Spatiotemporal covariance descriptors for action and gesture recognition. In WACV, 2013.
23. P. Scovanner, S. Ali, and M. Shah. A 3-dimensional sift descriptor and its application to action recognition. In ACM MM, 2007.
24. C. Shan, S. Gong, and P. W. McOwan. Facial expression recognition based on local binary patterns: A comprehensive study. IVC, 27(6):803-816, 2009.
25. O. Tuzel, F. Porikli, and P. Meer. Pedestrian detection via classification on riemannian manifolds. IEEE T PAMI, 30(10):1713-1727, 2008.
26. M. Valstar and M. Pantic. Induced disgust, happiness and surprise: an addition to the mmi facial expression database. In LRECW, 2010.
27. L. Wang, Y. Qiao, and X. Tang. Motionlets: Mid-level 3d parts for human motion recognition. In CVPR, 2013.
28. R. Wang and X. Chen. Manifold discriminant analysis. In CVPR, 2009.
29. R. Wang, H. Guo, L. S. Davis, and Q. Dai. Covariance discriminative learning: A natural and efficient approach to image set classification. In CVPR, 2012.
30. Z. Wang, S. Wang, and Q. Ji. Capturing complex spatio-temporal relations among facial muscles for facial expression recognition. In CVPR, 2013.
31. S. Yan, D. Xu, B. Zhang, H.-J. Zhang, Q. Yang, and S. Lin. Graph embedding and extensions: a general framework for dimensionality reduction. IEEE T PAMI, 29(1):40-51, 2007.
32. P. Yang, Q. Liu, X. Cui, and D. N. Metaxas. Facial expression recognition using encoded dynamic features. In CVPR, 2008.
33. G. Zhao, X. Huang, M. Taini, S. Z. Li, and M. Pietikäinen. Facial expression recognition from near-infrared videos. IVC, 29(9):607-619, 2011.
34. G. Zhao and M. Pietikainen. Dynamic texture recognition using local binary patterns with an application to facial expressions. IEEE T PAMI, 29(6):915-928, 2007.
35. L. Zhong, Q. Liu, P. Yang, B. Liu, J. Huang, and D. N. Metaxas. Learning active facial patches for expression analysis. In CVPR, 2012.