Paper Info
Title
Face recognition using ada-boosted gabor features
Abstract
Face representation based on Gabor features has attracted much attention and achieved great success in face recognition area for the advantages of the Gabor features. However, Gabor features currently adopted by most systems are redundant and too high dimensional. In this paper, we propose a face recognition method using AdaBoosted Gabor features, which are not only low dimensional but also discriminant. The main contribution of the paper lies in two points: (1) AdaBoost is successfully applied to face recognition by introducing the intra-face and extra-face difference space in the Gabor feature space; (2) An appropriate re-sampling scheme is adopted to deal with the imbalance between the amount of the positive samples and that of the negative samples. By using the proposed method, only hundreds of Gabor features are selected. Experiments on FERET database have shown that these hundreds of Gabor features are enough to achieve good performance comparable to that of methods using the complete set of Gabor features.
Year
DOI
Venue
2004
10.1109/AFGR.2004.1301556
FGR
Keywords
Field
DocType
low dimensional,gabor feature,high dimensional,gabor feature space,face recognition area,face recognition method,face representation,extra-face difference space,ada-boosted gabor feature,adaboosted gabor feature,face recognition,feret database,face detection,feature space,independent component analysis,bayesian methods,feature extraction,flowcharts,system testing,image classification,information security
Facial recognition system,Computer vision,Feature vector,AdaBoost,Three-dimensional face recognition,Pattern recognition,Discriminant,Feature extraction,Artificial intelligence,FERET database,Contextual image classification,Mathematics
Conference
ISBN
Citations 
PageRank 
0-7695-2122-3
79
5.19
References 
Authors
8
5
Name
Order
Citations
PageRank
Peng Yang133818.07
Shiguang Shan26322283.75
Wen Gao311374741.77
Stan Z. Li48951535.26
Dong Zhang512517.08