Kernel Methods on Riemannian Manifolds with Gaussian RBF Kernels

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 37, Issue 12, 2015, Pages 2464-2477

  Jayasumana, Sadeep ^a,b   Hartley, Richard ^a,b   Salzmann, Mathieu ^a,b   Li, Hongdong ^a,b   Harandi, Mehrtash ^a,b  

^a AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

^b CSIRO   (Australia)

Author keywords

Gaussian RBF kernels; Grassmann manifolds; kernel methods; positive definite kernels; Riemannian manifolds; symmetric positive definite matrices

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER VISION; DISCRIMINANT ANALYSIS; GAUSSIAN DISTRIBUTION; LEARNING ALGORITHMS; LEARNING SYSTEMS; MATRIX ALGEBRA; PRINCIPAL COMPONENT ANALYSIS; RADIAL BASIS FUNCTION NETWORKS; VECTOR SPACES;

GRASSMANN MANIFOLD; KERNEL METHODS; POSITIVE DEFINITE KERNELS; RBF KERNELS; RIEMANNIAN MANIFOLD; SYMMETRIC POSITIVE DEFINITE MATRICES;

GEOMETRY;

EID: 84957828695     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2015.2414422     Document Type: Article

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