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18th International Conference on Pattern Recognition (ICPR'06) Volume 1
A Real-Time Facial Expression Recognition using the STAAM
Hong Kong
August 20-August 24
ISBN: 0-7695-2521-0
ASCII Text
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Jaewon Sung, Sangjae Lee, Daijin Kim, "A Real-Time Facial Expression Recognition using the STAAM," Pattern Recognition, International Conference on, vol. 1, pp. 275-278, 18th International Conference on Pattern Recognition (ICPR'06) Volume 1, 2006.
 
 
BibTex
x
 
@article{ 10.1109/ICPR.2006.158,
author = {Jaewon Sung and Sangjae Lee and Daijin Kim},
title = {A Real-Time Facial Expression Recognition using the STAAM},
journal ={Pattern Recognition, International Conference on},
volume = {1},
year = {2006},
issn = {1051-4651},
pages = {275-278},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.158},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Pattern Recognition, International Conference on
TI - A Real-Time Facial Expression Recognition using the STAAM
SN - 1051-4651
SP275
EP278
A1 - Jaewon Sung,
A1 - Sangjae Lee,
A1 - Daijin Kim,
PY - 2006
KW - null
VL - 1
JA - Pattern Recognition, International Conference on
ER -
 
Jaewon Sung, Pohang University of Science and Technology, Korea
Sangjae Lee, Pohang University of Science and Technology, Korea
Daijin Kim, Pohang University of Science and Technology, Korea
This paper proposes a real-time person independent facial expression recognition in two folds. One is using the stereo Active Appearance Model (STAAM) fitting algorithm that uses a geometric relationship between two tightly coupled views to increases the accuracy and speed of fitting. Also, a layered generalized discriminant analysis (GDA) classifier combines 3D shape and appearance to improve the recognition performance of person independent facial expressions. Experimental results show that the STAAM have a better fitting stability than the multi-view AAM (MVAAM), and the combination of the shape and appearance features using a layered GDA classifier improves the recognition performance of facial expressions greatly.
Citation:
Jaewon Sung, Sangjae Lee, Daijin Kim, "A Real-Time Facial Expression Recognition using the STAAM," icpr, vol. 1, pp.275-278, 18th International Conference on Pattern Recognition (ICPR'06) Volume 1, 2006
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