Covariance discriminative learning: A natural and efficient approach to image set classification

Abstract

We propose a novel discriminative learning approach to image set classification by modeling the image set with its natural second-order statistic, i.e. covariance matrix. Since nonsingular covariance matrices, a.k.a. symmetric positive definite (SPD) matrices, lie on a Riemannian manifold, classical learning algorithms cannot be directly utilized to… (More)
DOI: 10.1109/CVPR.2012.6247965

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