Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Newton's Method for Large Bound-Constrained Optimization Problems
SIAM Journal on Optimization
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Journal of Cognitive Neuroscience
IEEE Transactions on Neural Networks
Sequential coordinate-wise DNMF for face recognition
ICAISC'10 Proceedings of the 10th international conference on Artificial intelligence and soft computing: Part I
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A novel Discriminant Non-negative Matrix Factorization (DNMF) method that uses projected gradients, is presented in this paper. The proposed algorithm guarantees the algorithm's convergence to a stationary point, contrary to the methods introduced so far, that only ensure the non-increasing behavior of the algorithm's cost function. The proposed algorithm employs some extra modifications that make the method more suitable for classification tasks. The usefulness of the proposed technique to the frontal face verification problem is also demonstrated.