Automatic facial expression recognition

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

Volumn 3972 LNCS, Issue , 2006, Pages 63-68

  Lu, Huchuan ^a   Wu, Pei ^a   Lin, Hui ^a   Yang, Deli ^a  

^a DALIAN UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

FEATURE EXTRACTION; IMAGE ANALYSIS; IMAGE PROCESSING; REAL TIME SYSTEMS; SET THEORY; VECTOR QUANTIZATION;

GABOR ENERGY FILTERS; SCALED IMAGE PATCHES; SUPPORT VECTOR MACHINES; VIDEO STREAMS;

FACE RECOGNITION;

EID: 33745922346     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11760023_10     Document Type: Conference Paper

References (8)

1. Lyons, M., Budynek, J., Plante, A., Akamatsu, S.: Classifying Facial Attributes Using a 2-D Gabor Wavelet Representation and Discriminant Analysis. Proceedings of the 4th International conference on Automatic Face and Gesture Recognition (2000) 202-207
2. Littlewort, G., Bartlett, M. S., Fasel, I., Chenu, J., Movellan, J. R.: Analysis of Machine Learning Methods for Real-Time Recognition of Facial Expressions from Video. MPLab TR (2003)
3. Kanade, T., Cohn, J.F., Tian, Y.: Comprehensive Database for Facial Expression Analysis. Proceedings of the 4th IEEE International Conference on Automatic Face and Gesture Recognition (2000) 46-53
4. Viola, P., Jones, M.: Robust Real-time Object Detection. Technical Report CRL 2001/01, Cambridge Research-Laboratory (2001)
5. Osuna, E., Freund, R.: An Improved Training Algorithm for Support Vector Machine. Proceedings of 1997 IEEE Workshop on Neural Networks for Signal Processing (1997) 276-285
6. Platt, J.: Fast Training of Support Vector Machines using Sequential Minimal Optimization. MIT Press (1998)
7. Fan, R. E., Chen, P. H., Lin, C.J.: Working Set Selection Using the Second Order Information for Training SVM. http://www.csie.ntu.edu.tw/~cjlin/papers/quadworkset.pdf (2005)
8. Chen, P. H., Fan, R. E., Lin, C.J.: A Study on SMO-type Decomposition Methods for Support Vector Machines, Technical report. Department of Computer Science, National Taiwan University (2005), http://www.csie.ntu.edu.tw/~cjlin/papers/generalSMO.pdf