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Supervised Canonical Correlation Analysis Of Data On Symmetric Positive Definite Manifolds By Riemannian Dimensionality Reduction
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Supervised Canonical Correlation Analysis Of Data On Symmetric Positive Definite Manifolds By Riemannian Dimensionality Reduction
Most computer vision problems entail data that reside on Riemannian manifolds. Canonical correlation analysis (CCA) is a powerful method that captures correlations between any two sets of matrices. In this paper, we propose a framework for a supervised CC
Most computer vision problems entail data that reside on Riemannian manifolds. Canonical correlation analysis (CCA) is a powerful method that captures correlations between any two sets of matrices. In this paper, we propose a framework for a supervised CC
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