Membership authentication in the dynamic group by face classification using SVM ensemble
Pattern Recognition Letters
Face Recognition Based on Efficient Facial Scale Estimation
AMDO '02 Proceedings of the Second International Workshop on Articulated Motion and Deformable Objects
Gabor-Based Kernel PCA with Fractional Power Polynomial Models for Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
IRIS Recognition based on multi-channel feature extraction using gabor filters
ACST'06 Proceedings of the 2nd IASTED international conference on Advances in computer science and technology
An experimental comparison of gender classification methods
Pattern Recognition Letters
A method towards face recognition
International Journal of Intelligent Systems Technologies and Applications
Multi-band Gradient Component Pattern (MGCP): A New Statistical Feature for Face Recognition
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
PCM'10 Proceedings of the Advances in multimedia information processing, and 11th Pacific Rim conference on Multimedia: Part II
Ethnicity estimation with facial images
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Computer Vision and Image Understanding
Automatic facial expression recognition
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Gabor-Kernel fisher analysis for face recognition
PCM'04 Proceedings of the 5th Pacific Rim Conference on Advances in Multimedia Information Processing - Volume Part II
Ethnicity classification based on a hierarchical fusion
CCBR'12 Proceedings of the 7th Chinese conference on Biometric Recognition
Linear subspaces for facial expression recognition
Image Communication
Gender classification of human face images based on adaptive features and support vector machines
Optical Memory and Neural Networks
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A method for automatically classifying facial images is proposed. Faces are represented using elastic graphs labeled with 2-D Gabor wavelet features. The system is trained from examples to classify faces on the basis of high-level attributes, such as sex, "race", and expression, using linear discriminant analysis (LDA). Use of the Gabor representation relaxes the requirement for precise normalization of the face: approximate registration of a facial graph is sufficient. LDA allows simple and rapid training from examples, as well as a straightforward interpretation of the role of the input features for classification. The algorithm is tested on three different facial image datasets, one of which was acquired under relatively uncontrolled conditions, on tasks of sex, "race" and expression classification. Results of these tests are presented. The discriminant vectors may be interpreted in terms of the saliency of the input features for the different classification tasks, which we portray visually with feature saliency maps for node position as well as filter spatial frequency and orientation.