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2009 10th Workshop on Image Analysis for Multimedia Interactive Services
Robust facial expression recognition based on RPCA and AdaBoost
London, United Kingdom
May 06-May 08
ISBN: 978-1-4244-3609-5
ASCII Text
x 
 
Xia Mao, YuLi Xue, Zheng Li, Kang Huang, ShanWei Lv, "Robust facial expression recognition based on RPCA and AdaBoost," Image Analysis for Multimedia Interactive Services, International Workshop on, pp. 113-116, 2009 10th Workshop on Image Analysis for Multimedia Interactive Services, 2009.
 
 
BibTex
x
 
@article{ 10.1109/WIAMIS.2009.5031445,
author = {Xia Mao and YuLi Xue and Zheng Li and Kang Huang and ShanWei Lv},
title = {Robust facial expression recognition based on RPCA and AdaBoost},
journal ={Image Analysis for Multimedia Interactive Services, International Workshop on},
volume = {0},
year = {2009},
isbn = {978-1-4244-3609-5},
pages = {113-116},
doi = {http://doi.ieeecomputersociety.org/10.1109/WIAMIS.2009.5031445},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Image Analysis for Multimedia Interactive Services, International Workshop on
TI - Robust facial expression recognition based on RPCA and AdaBoost
SN - 978-1-4244-3609-5
SP113
EP116
A1 - Xia Mao,
A1 - YuLi Xue,
A1 - Zheng Li,
A1 - Kang Huang,
A1 - ShanWei Lv,
PY - 2009
VL - 0
JA - Image Analysis for Multimedia Interactive Services, International Workshop on
ER -
 
Xia Mao, School of Electronic and Information Engineering, Beihang University, China
YuLi Xue, School of Electronic and Information Engineering, Beihang University, China
Zheng Li, School of Electronic and Information Engineering, Beihang University, China
Kang Huang, School of Electronic and Information Engineering, Beihang University, China
ShanWei Lv, School of Electronic and Information Engineering, Beihang University, China
In this paper, we consider the problem of robust facial expression recognition and propose a novel scheme for facial expression recognition under facial occlusion. There are two main contributions in this work. Firstly, a novel method for facial occlusion detection based on robust principal component analysis (RPCA) and saliency detection performs efficiently to detect facial occlusions. Secondly, a novel method based on occlusion reconstruction and reweighted AdaBoost classification is prosed for facial expression recognition. Experimental results have shown the effectiveness of our proposed method for robust facial expression recognition.
Citation:
Xia Mao, YuLi Xue, Zheng Li, Kang Huang, ShanWei Lv, "Robust facial expression recognition based on RPCA and AdaBoost," wiamis, pp.113-116, 2009 10th Workshop on Image Analysis for Multimedia Interactive Services, 2009
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