TY - GEN
T1 - Robust face recognition using multiple self-organized Gabor features and local similarity matching
AU - Aly, Saleh
AU - Shimada, Atsushi
AU - Tsuruta, Naoyuki
AU - Taniguchi, Rin Ichiro
PY - 2010/11/18
Y1 - 2010/11/18
N2 - Gabor-based face representation has achieved enormous success in face recognition. However, one drawback of Gabor-based face representation is the huge amount of data that must be stored. Due to the nonlinear structure of the data obtained from Gabor response, classical linear projection methods like principal component analysis fail to learn the distribution of the data. A nonlinear projection method based on a set of self-organizing maps is employed to capture this nonlinearity and to represent face in a new reduced feature space. The Multiple Self-Organized Gabor Features (MSOGF) algorithm is used to represent the input image using all winner indices from each SOM map. A new local matching algorithm based on the similarity between local features is also proposed to classify unlabeled data. Experimental results on FERET database prove that the proposed method is robust to expression variations.
AB - Gabor-based face representation has achieved enormous success in face recognition. However, one drawback of Gabor-based face representation is the huge amount of data that must be stored. Due to the nonlinear structure of the data obtained from Gabor response, classical linear projection methods like principal component analysis fail to learn the distribution of the data. A nonlinear projection method based on a set of self-organizing maps is employed to capture this nonlinearity and to represent face in a new reduced feature space. The Multiple Self-Organized Gabor Features (MSOGF) algorithm is used to represent the input image using all winner indices from each SOM map. A new local matching algorithm based on the similarity between local features is also proposed to classify unlabeled data. Experimental results on FERET database prove that the proposed method is robust to expression variations.
UR - http://www.scopus.com/inward/record.url?scp=78149481376&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78149481376&partnerID=8YFLogxK
U2 - 10.1109/ICPR.2010.713
DO - 10.1109/ICPR.2010.713
M3 - Conference contribution
AN - SCOPUS:78149481376
SN - 9780769541099
T3 - Proceedings - International Conference on Pattern Recognition
SP - 2909
EP - 2912
BT - Proceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010
T2 - 2010 20th International Conference on Pattern Recognition, ICPR 2010
Y2 - 23 August 2010 through 26 August 2010
ER -