Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Overview of the Face Recognition Grand Challenge
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Journal of Cognitive Neuroscience
Fusion of the complementary Discrete Cosine Features in the YIQ color space for face recognition
Computer Vision and Image Understanding
Face Recognition Using a Color Subspace LDA Approach
ICTAI '08 Proceedings of the 2008 20th IEEE International Conference on Tools with Artificial Intelligence - Volume 01
ICA color space for pattern recognition
IEEE Transactions on Neural Networks
Score normalization in multimodal biometric systems
Pattern Recognition
Face recognition using Intrinsicfaces
Pattern Recognition
Enhanced local texture feature sets for face recognition under difficult lighting conditions
IEEE Transactions on Image Processing
Linear Regression for Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Color Image Discriminant Models and Algorithms for Face Recognition
IEEE Transactions on Neural Networks
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Research on color face recognition in the existing literature is aimed to establish a color space that can have the most of the discriminative information from the original data. This mainly includes optimal combination of different color components from the original color space. Recently proposed discriminate color space (DCS) is theoretically optimal for classification, in which one seeks a set of optimal coefficients in terms of linear combinations of the R, G and B components (based on a discriminate criterion). This work proposes an innovative block-wise DCS (BWDCS) method, which allows each block of the image to be in a distinct DCS. This is an interesting alternative to the methods relying on converting whole image to DCS. This idea is evaluated with four appearance-based subspace state-of-the-art methods on five different publicly available databases including the well-known FERET and FRGC databases. Experimental results show that the performance of these four gray-scale based methods can be improved by 17% on average when they are used with the proposed color space.