Facial expression recognition from video sequences: Temporal and static modeling

Computer Vision and Image Understanding

Volumn 91, Issue 1-2, 2003, Pages 160-187

  Cohen, Ira ^a   Sebe, Nicu ^b   Garg, Ashutosh ^c   Chen, Lawrence S ^d   Huang, Thomas S ^a  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^b UNIVERSITY OF AMSTERDAM   (Netherlands)

^c IBM ALMADEN RESEARCH CENTER   (United States)

^d EASTMAN KODAK COMPANY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE SEGMENTATION; MATHEMATICAL TRANSFORMATIONS; MATRIX ALGEBRA; VIDEO SIGNAL PROCESSING;

COVARIANCE MATRIX;

FACE RECOGNITION;

EID: 0141860866     PISSN: 10773142     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1077-3142(03)00081-X     Document Type: Article

References (41)

1. S. Baluja, Probabilistic modelling for face orientation discrimination: learning from labeled and unlabeled data, in: Neural Information Processing Systems (NIPS'98), 1998, pp. 854-860.
2. M.J. Black, Y. Yacoob, Tracking and recognizing rigid and non-rigid facial motions using local parametric models of image motion, in: Proc. Internat. Conf. Computer Vision (ICCV'95), 1995, pp. 374-381.
3. J.T. Cacioppo, L.G. Tassinary, Inferring psychological significance from physiological signals, Amer. Psychologist 45 (1990) 16-28.
4. L.S. Chen, Joint processing of audio-visual information for the recognition of emotional expressions in human-computer interaction, Ph.D. Thesis, University of Illinois at Urbana-Champaign, Department of Electrical Engineering, 2000.
5. C.K. Chow, C.N. Liu, Approximating discrete probability distribution with dependence trees, IEEE Trans. Inform. Theory 14 (1968) 462-467.
6. I. Cohen, Automatic facial expression recognition from video sequences using temporal information. MS Thesis, University of Illinois at Urbana-Champaign, Department of Electrical Engineering, 2000.
7. T.H. Cormen, C.E. Leiserson, R.L. Rivest, Introduction to Algorithms, MIT Press, Cambridge, MA, 1990.
8. L.C. De Silva, T. Miyasato, R. Natatsu, Facial emotion recognition using multimodal information. in: Proc. IEEE Internat. Conf. on Information, Communications and Signal Processing (ICICS'97), 1997, pp. 397-401.
9. G. Donato, M.S. Bartlett, J.C. Hager, P. Ekman, T.J. Sejnowski, Classifying facial actions, IEEE Trans. Pattern Anal. Machine Intell. 21 (10) (1999) 974-989.
10. P. Ekman, Strong evidence for universals in facial expressions: a reply to Russell's mistaken critique, Psychol. Bull. 115 (2) (1994) 268-287.
11. P. Ekman, W.V. Friesen, Facial Action Coding System: Investigator's Guide, Consulting Psychologists Press, Palo Alto, CA, 1978.
12. I.A. Essa, A.P. Pentland, Coding, analysis, interpretation, and recognition of facial expressions, IEEE Trans. Pattern Anal. Machine Intell. 19 (7) (1997) 757-763.
13. J.H. Friedman, On bias, variance, 0/1-loss, and the curse-of-dimensionality, Data Mining Knowledge Discovery 1 (1) (1997) 55-77.
14. N. Friedman, D. Geiger, M. Goldszmidt, Bayesian network classifiers, Machine Learning 29 (2) (1997) 131-163.
15. A. Garg, D. Roth, Understanding probabilistic classifiers, in: Proc. Eur. Conf. on Machine Learning, 2001, pp. 179-191.
16. D. Goleman, Emotional Intelligence, Bantam Books, New York, 1995.
17. G. Haas, L. Bain, C. Antle, Inferences for the Cauchy distribution based on maximum likelihood estimators, Biometrika 57 (2) (1970) 403-408.
18. C.E. Izard, Innate and universal facial expressions: evidence from developmental and cross-cultural research, Psychol. Bull. 115 (2) (1994) 288-299.
19. T. Kanade, J. Cohn, Y. Tian, Comprehensive database for facial expression analysis, 2000.
20. R.M. Kay, Entropy and Information Theory, Springer, Berlin, 1990.
21. A. Lanitis, C.J. Taylor, T.F. Cootes, A unified approach to coding and interpreting face images, in: Proc. 5th Internat. Conf. on Computer Vision (ICCV'95), 1995, pp. 368-373.
22. S.E. Levinson, L.R. Rabiner, M.M. Sondhi, An introduction to the application of the theory of probabilitic functions of a Markov process to automatic speech recognition, Bell Lab System Technical J. 62 (4) (1983) 1035-1072.
23. J. Lien, Automatic recognition of facial expressions using hidden Markov models and estimation of expression intensity. Ph.D. Thesis, Carnegie Mellon University, 1998.
24. A. Martinez, Face image retrieval using HMMs, in: IEEE Workshop on Content-based Access of Images and Video Libraries, 1999, pp. 35-39.
25. K. Mase, Recognition of facial expression from optical flow, IEICE Trans. E74 (10) (1991) 3474-3483.
26. A. Nefian, M. Hayes, Face recognition using an embedded HMM, in: IEEE Conf. on Audio and Video-based Biometric Person Authentication, 1999, pp. 19-24.
27. K. Nigam, A. McCallum, S. Thrun, T. Mitchell, Text classification from labeled and unlabeled documents using EM, Machine Learning 39 (2000) 103-134.
28. N. Oliver, A. Pentland, F. Bérard, LAFTER: a real-time face and lips tracker with facial expression recognition, Pattern Recognition 33 (2000) 1369-1382.
29. N. Oliver, A. Pentland, F. Bérard, LAFTER: lips and face real time tracker, in: Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR'97), 1997, pp. 123-129.
30. T. Otsuka, J. Ohya, Recognizing multiple persons' facial expressions using HMM based on automatic extraction of significant frames from image sequences, in: Proc. Internat. Conf. on Image Processing (ICIP'97), 1997, pp. 546-549.
31. T. Otsuka, J. Ohya, A study of transformation of facial expressions based on expression recognition from temproal image sequences, Technical Report, Institute of Electronic, Information, and Communications Engineers (IEICE), 1997.
32. M. Pantic, L.J.M. Rothkrantz, Automatic analysis of facial expressions: the state of the art, IEEE Trans. Pattern Anal. Machine Intell. 22 (12) (2000) 1424-1445.
33. L.R. Rabiner, A tutorial on hidden Markov models and selected applications in speech processing, Proc. IEEE 77 (2) (1989) 257-286.
34. L.R. Rabiner, B. Juang, Fundamentals of Speech Recognition, Prentice-Hall, Englewood Cliffs, NJ, 1993.
35. M. Rosenblum, Y. Yacoob, L.S. Davis, Human expression recognition from motion using a radial basis function network architecture, IEEE Trans. Neural Network 7 (5) (1996) 1121-1138.
36. P. Salovey, J.D. Mayer, Emotional intelligence, Imagination, Cognition, Personality 9 (3) (1990) 185-211.
37. N. Sebe, M.S. Lew, D.P. Huijsmans, Toward improved ranking metrics, IEEE Trans. Pattern Anal. Machine Intell. 22 (10) (2000) 1132-1143.
38. H. Starks, J. Woods, Probability, Random Processes, and Estimation Theory for Engineers, Prentice-Hall, Englewood Cliffs, NJ, 1994.
39. H. Tao, T.S. Huang, Connected vibrations: a modal analysis approach to non-rigid motion tracking, in: Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR'98), 1998, pp. 735-740.
40. N. Ueki, S. Morishima, H. Yamada, H. Harashima, Expression analysis/synthesis system based on emotion space constructed by multilayered neural network, Systems Comput. Japan 25 (13) (1994) 95-103.
41. Y. Yacoob, L.S. Davis, Recognizing human facial expressions from long image sequences using optical flow, IEEE Trans. Pattern Anal. Machine Intell. 18 (6) (1996) 636-642.