Facial expression recognition in various internal states using independent component analysis

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4069 LNCS, Issue , 2006, Pages 291-299

  Shin, Young Suk ^a  

^a Chosun University   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; FACE RECOGNITION; INDEPENDENT COMPONENT ANALYSIS; PRINCIPAL COMPONENT ANALYSIS;

ARTICULATED MOTION; COGNITIVE PROCESSES; FACIAL EXPRESSIONS; INTERNAL STATES;

PATTERN RECOGNITION;

EID: 33746626473     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11789239_30     Document Type: Conference Paper

References (20)

1. Bartlett, M., Viola, P., Sejnowski, T., Larsen, J., Hager, J., Ekman, P.: Classfying Facial Action. In: Advances in Neural Information Processing Systems 8. D. Touretzky et al. editors, MIT Press, Cambridge, MA (1996)
2. Essa, I., Pentland, A.:Coding, analysis, interpretation, and recognition of facial expressions. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19 (1997) 757-763
3. Lien, J.: Automatic recognition of facial expressions using hidden Markov models and estimation of expression intensity. Ph.D. Thesis, Carnegie Mellon University, (1998)
4. Oliver, N. Pentland, A., Berard, F.: LAFTER:a real-time face and lips tracker with facial expression recognition. Pattern Recognition 33 (2000) 1369-1382
5. Cohen, I., Sebe, N., Garg, A., Chen, L. S., Huang, T. S.: Facial expression recognition from video sequence. Proc. Int'l Conf. Multimedia and Exp(ICME) (2002) 121-124
6. Peter J. L.: The emotion probe: Studies of motivation and attention. American Psychologist, 50(5) (1995) 372-385
7. Russell, J. A.: Evidence of convergent validity on the dimension of affect. Journal of Personality and Social Psychology, 30, (1978) 1152-1168
8. Donato, G., Bartlett, M., Hager, J., Ekman, P. and Sejnowski, T.: Classifying facial actions, IEEE PAMI, 21(10) (1999) 974-989
9. Pantic, M., Rothkrantz, L.J.M.: Towards an Affect-Sensitive Multimodal Human Computer Interaction, Proc. Of IEEE. 91 1370-1390
10. Youngsuk S., Youngjoon A.: Facial expression recognition based on two dimensions without neutral expressions, LNCS(3711) (2005) 215-222
11. Bartlett, M.: Face Image analysis by unsupervised learning, Kluwer Academic Publishers (2001)
12. Comon, P.: Independent component analysis - a new concept? Signal processing 36 (1994) 287-314
13. Saebum, B., Jaehyun, H., Chansub, C.: Facial expression database for mapping facial expression onto internal state. '97 Emotion Conference of Korea, (1997) 215-219
14. Osgood, C. E., May, W.H. and Miron, M.S.: Cross-curtral universals of affective meaning. Urbana:University of Illinoise Press, (1975)
15. Russell, J. A., Lewicka, M. and Nitt, T.: A cross-cultural study of a circumplex model of affect. Journal of Personality and Social Psychology, 57, (1989) 848-856
16. Younga, K., Jinkwan, K., Sukyung, P., Kyungja, O., Chansub, C.: The study of dimension of internal states through word analysis about emotion. Korean Journal of the Science of Emotion and Sensibility, 1 (1998) 145-152
17. Atick, J., Redlich, A.: What does the retina know about natural scenes?, Neural Computation (4) (1992) 196-210
18. Olshasen, B. Field, D.: Natural image statistics and efficient coding, Network:computation in neural systems, 7(2) (1996) 333-340
19. Bell,A. Sejnowski, T.: The independent components of natural scenes areedge filters, Vision Research, 37(23) (1997) 3327-3338
20. Hyvarinen, A., Karhunen, J., Oja, E.: Independent component analysis, John Wiley & Sons, Inc. (2001)