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In this, paper general solutions for nonlinear non-negative component analysis for data representation and recognition are proposed. Motivated by a combination of the non-negative matrix factorization (NMF) algorithm and kernel theory, which has lead to a recently proposed NMF algorithm in a polynomial feature space, we propose a general framework where one can build a nonlinear non-negative component...
In this paper general solutions for nonlinear nonnegative component analysis for data representation and recognition are proposed. That is, motivated by a combination of the Nonnegative Matrix Factorization (NMF) algorithm and kernel theory, which has lead to an NMF algorithm in a polynomial feature space, we propose a general framework where one can build a nonlinear nonnegative component analysis...
A novel method that fuses texture and shape information to achieve Facial Action Unit (FAU) recognition from video sequences is proposed. In order to extract the texture information, a subspace method based on Discriminant Non- negative Matrix Factorization (DNMF) is applied on the difference images of the video sequence, calculated taking under consideration the neutral and the most expressive frame,...
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