A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
Distortion Invariant Object Recognition in the Dynamic Link Architecture
IEEE Transactions on Computers
Unified Subspace Analysis for Face Recognition
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Journal of Cognitive Neuroscience
Frame synchronization and multi-level subspace analysis for video based face recognition
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Face recognition using ada-boosted gabor features
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
IEEE Transactions on Image Processing
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In this paper, we propose a new scheme of Gabor-based face recognition. Based on the fact that different Gabor filters have different properties, we first learn discriminating subspace for each kind of Gabor images respectively. Then the boosting learning is performed to fuse all the Gabor discriminating subspaces for recognition. Compared with previous work, the proposed method has three contributions: (1). We make sufficiently use of the respective properties of the Gabor filters, and learn different discriminant subspaces for different Gabor images respectively; (2). Boosting based fusing method adaptively determines the discriminating vectors and dimensionality of each subspace according to its discriminating capacity, so as to further improve the recognition performance; (3). The problem of computational complexity is well handled by subspace analysis and boosting based fusion. Extensive experiments show its encouraging performance.