Expanding the Family of Grassmannian Kernels: An Embedding Perspective

Abstract

Modeling videos and image-sets as linear subspaces has proven beneficial for many visual recognition tasks. However, it also incurs challenges arising from the fact that linear subspaces do not obey Euclidean geometry, but lie on a special type of Riemannian manifolds known as Grassmannian. To leverage the techniques developed for Euclidean spaces (e.g… (More)
DOI: 10.1007/978-3-319-10584-0_27

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