Kernel methods on the riemannian manifold of symmetric positive definite matrices

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2013, Pages 73-80

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

^a AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

^b CSIRO   (Australia)

Author keywords

Hilbert space embedding; kernel methods; positive definite kernels; Riemannian manifolds; RKHS; Symmetric positive definite matrices

Indexed keywords

HILBERT SPACE EMBEDDING; KERNEL METHODS; POSITIVE DEFINITE KERNELS; RIEMANNIAN MANIFOLD; RKHS; SYMMETRIC POSITIVE DEFINITE MATRICES;

ALGORITHMS; DIFFUSION TENSOR IMAGING; ENCODING (SYMBOLS); HILBERT SPACES; MAGNETIC RESONANCE IMAGING; PATTERN RECOGNITION; TENSORS; VECTOR SPACES;

GEOMETRY;

EID: 84887400913     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2013.17     Document Type: Conference Paper

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