Independent component analysis, a new concept?
Signal Processing - Special issue on higher order statistics
The nature of statistical learning theory
The nature of statistical learning theory
Probabilistic Visual Learning for Object Representation
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
Automatic Interpretation and Coding of Face Images Using Flexible Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition by Elastic Bunch Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Principal Manifolds and Probabilistic Subspaces for Visual Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Cognitive Neuroscience
Survey of Distance Measures for NMF-Based Face Recognition
Computational Intelligence and Security
Face recognition using the feature fusion technique based on LNMF and NNSC algorithms
ICIC'10 Proceedings of the 6th international conference on Advanced intelligent computing theories and applications: intelligent computing
Sequential coordinate-wise DNMF for face recognition
ICAISC'10 Proceedings of the 10th international conference on Artificial intelligence and soft computing: Part I
Pattern Recognition Letters
Parts-Based holistic face recognition with RBF neural networks
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Commute time guided transformation for feature extraction
Computer Vision and Image Understanding
Face recognition from color images using sparse projection analysis
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part I
Efficient Nonnegative Matrix Factorization via projected Newton method
Pattern Recognition
Nonnegative matrix factorizations performing object detection and localization
Applied Computational Intelligence and Soft Computing
Spatially correlated nonnegative matrix factorization for image analysis
IScIDE'12 Proceedings of the third Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
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The computer vision problem of face classification under several ambient and unfavorable conditions is considered in this study. Changes in expression, different lighting conditions and occlusions are the relevant factors that are studied in this present contribution. Non-negative Matrix Factorization (NMF) technique is introduced in the context of face classification and a direct comparison with Principal Component Analysis (PCA) is also analyzed. Two leading techniques in face recognition are also considered in this study noticing that NMF is able to improve these techniques when a high dimensional feature space is used. Finally, different distance metrics (L1, L2 and correlation) are evaluated in the feature space defined by NMF in order to determine the best one for this specific problem. Experiments demonstrate that the correlation is the most suitable metric for this problem.