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IEEE Transactions on Pattern Analysis and Machine Intelligence
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Color by Correlation: A Simple, Unifying Framework for Color Constancy
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Detection in Color Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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Robust Discriminant Analysis Based on Nonparametric Maximum Entropy
ACML '09 Proceedings of the 1st Asian Conference on Machine Learning: Advances in Machine Learning
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Pattern Recognition Letters
A multi-manifold discriminant analysis method for image feature extraction
Pattern Recognition
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Extracting discriminative color features for face recognition
Pattern Recognition Letters
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IEEE Transactions on Pattern Analysis and Machine Intelligence
Describable Visual Attributes for Face Verification and Image Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Color face recognition based on statistically orthogonal analysis of projection transforms
CCBR'11 Proceedings of the 6th Chinese conference on Biometric recognition
Fuzzy local maximal marginal embedding for feature extraction
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Pattern Recognition Letters
Learning the Uncorrelated, Independent, and Discriminating Color Spaces for Face Recognition
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Color object detection using spatial-color joint probability functions
IEEE Transactions on Image Processing
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Nonstationary color tracking for vision-based human-computer interaction
IEEE Transactions on Neural Networks
Color clustering and learning for image segmentation based on neural networks
IEEE Transactions on Neural Networks
Color Image Discriminant Models and Algorithms for Face Recognition
IEEE Transactions on Neural Networks
Tensor Discriminant Color Space for Face Recognition
IEEE Transactions on Image Processing
Color Local Texture Features for Color Face Recognition
IEEE Transactions on Image Processing
Face recognition by discriminant analysis with gabor tensor representation
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
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This paper presents a novel color face recognition method called two-dimensional color uncorrelated discriminant analysis (2DCUDA), which can extract two-dimensional color uncorrelated features and simultaneously retain the face spatial structure information. The 2DCUDA method seeks to explore color uncorrelated discriminant properties of the color face images and eliminate the correlations between color-based features. The novelties of this paper are twofold. First, this paper develops a new color-based feature for face recognition, which can provide substantial mutual complementation information and improve the recognition performance. Second, theoretical analysis guarantees the uncorrelated property of the obtained color-based features. Comparative experiments on AR and FRGC-2 color face databases have been conducted to investigate the effectiveness of the proposed algorithm. Experimental results show that the proposed algorithm performs better than other color face recognition methods and the two-dimensional color uncorrelated discriminant features are more effective for low-resolution image compared with conventional gray-based features. Finally, we explain why the proposed algorithm can improve the recognition performance compared with other color face recognition methods.