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Sparse coding and dictionary learning for symmetric positive definite matrices: A kernel approach

Harandi, Mehrtash T.; Sanderson, Conrad; Hartley, Richard; Lovell, Brian

Description

Recent advances suggest that a wide range of computer vision problems can be addressed more appropriately by considering non-Euclidean geometry. This paper tackles the problem of sparse coding and dictionary learning in the space of symmetric positive definite matrices, which form a Riemannian manifold. With the aid of the recently introduced Stein kernel (related to a symmetric version of Bregman matrix divergence), we propose to perform sparse coding by embedding Riemannian manifolds into...[Show more]

CollectionsANU Research Publications
Date published: 2012
Type: Conference paper
URI: http://hdl.handle.net/1885/69124
Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
DOI: 10.1007/978-3-642-33709-3_16

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