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 Multilinear Independent Components Analysis
Multilinear Independent Components Analysis M. Alex O. Vasilescu1,2 and Demetri Terzopoulos2,1 1Department of Computer Science, University of Toronto, Toronto ON M5S 3G4, Canada 2Courant Institute of Mathematical Sciences, New York University, New York, NY 10003, USA Abstract IndependentComponentsAnalysis(ICA)maximizesthesta-tistical independence of the representational components of...
(PDF) Multilinear independent component analysis | Demetri ...
In particular, the linear, After reviewing the mathematical foundations of our appearance-based face recognition method known as Eigen- work in the next section, we introduce our multilinear ICA faces [9] is founded on the principal components analysis algorithm in Section 3 and develop the associated recogni- (PCA) of facial image ensembles [7]....
Research - M. Alex O. Vasilescu - MIT Media Lab
In the context of facial image ensembles, we demonstrate that the statistical regularities learned by MICA capture information that improves automatic face recognition. "Multilinear (Tensor) ICA and Dimensionality Reduction", M.A.O. Vasilescu, D. Terzopoulos, Proc. 7th International Conference on Independent Component Analysis and Signal ......
CiteSeerX — Multilinear Independent Components Analysis
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Independent Components Analysis (ICA) maximizes the statistical independence of the representational components of a training image ensemble, but it cannot distinguish between the different factors, or modes, inherent to image formation, including scene structure, illumination, and imaging.
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