Abstract 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.
Boosting Multi-gabor Subspaces for Face Recognition
Computer Vision – ACCV 2006 ; 5 ; 539-548
Lecture Notes in Computer Science ; 3851 , 5
2006-01-01
10 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Principal Component Analysis , Face Recognition , Gabor Feature , Subspace Analysis , Face Recognition Method Computer Science , Computer Imaging, Vision, Pattern Recognition and Graphics , Pattern Recognition , Image Processing and Computer Vision , Artificial Intelligence (incl. Robotics) , Algorithm Analysis and Problem Complexity
Boosting Multi-gabor Subspaces for Face Recognition
British Library Conference Proceedings | 2006
|Pseudo-Gabor wavelet for face recognition
British Library Online Contents | 2013
|A Gabor Feature Classifier for Face Recognition
British Library Conference Proceedings | 2001
|A Gabor feature classifier for face recognition
IEEE | 2001
|