AdaBoost gabor fisher classifier for face recognition

Authors:
Shiguang Shan;Peng Yang;Xilin Chen;Wen Gao
Affiliations:
ICT-ISVISION JDL for Face Recognition, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;Department of Computer Sciences at Rutgers, The State University of New Jersey;ICT-ISVISION JDL for Face Recognition, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;ICT-ISVISION JDL for Face Recognition, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
Venue:
AMFG'05 Proceedings of the Second international conference on Analysis and Modelling of Faces and Gestures
Year:
2005

Citing 12
Cited 12

Image Representation Using 2D Gabor Wavelets

IEEE Transactions on Pattern Analysis and Machine Intelligence
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection

IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition by Elastic Bunch Graph Matching

IEEE Transactions on Pattern Analysis and Machine Intelligence
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
The FERET Evaluation Methodology for Face-Recognition Algorithms

IEEE Transactions on Pattern Analysis and Machine Intelligence
Distortion Invariant Object Recognition in the Dynamic Link Architecture

IEEE Transactions on Computers
Gabor Wavelet Networks for Object Representation

Mustererkennung 2000, 22. DAGM-Symposium
Pattern Classification (2nd Edition)

Pattern Classification (2nd Edition)
FloatBoost Learning and Statistical Face Detection

IEEE Transactions on Pattern Analysis and Machine Intelligence
Review the Strength of Gabor Features for Face Recognition from the Angle of Its Robustness to Mis-Alignment

ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Face recognition using ada-boosted gabor features

FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Gabor feature based classification using the enhanced fisher linear discriminant model for face recognition

IEEE Transactions on Image Processing

A new extension of kernel feature and its application for visual recognition

Neurocomputing
Face Recognition with Biologically Motivated Boosted Features

Cognitive Vision
Local Gabor Binary Pattern Whitened PCA: A Novel Approach for Face Recognition from Single Image Per Person

ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Recognizing faces using Adaptively Weighted Sub-Gabor Array from a single sample image per enrolled subject

Image and Vision Computing
Recent advances in face biometrics with Gabor wavelets: A review

Pattern Recognition Letters
Improved face representation by nonuniform multilevel selection of Gabor convolution features

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Learning Gabor magnitude features for palmprint recognition

ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
A novel illumination-robust face recognition using statistical and non-statistical method

Pattern Recognition Letters
Large scale identity deduplication using face recognition based on facial feature points

CCBR'11 Proceedings of the 6th Chinese conference on Biometric recognition
Fast multi-scale local phase quantization histogram for face recognition

Pattern Recognition Letters
Selective generation of Gabor features for fast face recognition on mobile devices

Pattern Recognition Letters
An Embedded Co-AdaBoost based construction of software document relation coupled resource spaces for cyber-physical society

Future Generation Computer Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper proposes the AdaBoost Gabor Fisher Classifier (AGFC) for robust face recognition, in which a chain AdaBoost learning method based on Bootstrap re-sampling is proposed and applied to face recognition with impressive recognition performance. Gabor features have been recognized as one of the most successful face representations, but it is too high dimensional for fast extraction and accurate classification. In AGFC, AdaBoost is exploited to select optimally the most informative Gabor features (hereinafter as AdaGabor features). The selected low-dimensional AdaGabor features are then classified by Fisher discriminant analysis for final face identification. Our experiments on two large-scale face databases, FERET and CAS-PEAL (with 5789 images of 1040 subjects), have shown that the proposed method can effectively reduce the dimensionality of Gabor features and greatly increase the recognition accuracy. In addition, our experimental results show its robustness to variations in facial expression and accessories.