Kernel methods on the Riemannian manifold of symmetric positive definite matrices
Symmetric Positive Definite (SPD) matrices have become popular to encode image information. Accounting for the geometry of the Riemannian manifold of SPD matrices has proven key to the success of many algorithms. However, most existing methods only approx
|Collections||ANU Research Publications|
|Source:||Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition|
|01_Hirimbura Matara (Jayasumana)_Kernel_methods_on_the_2013.pdf||492.85 kB||Adobe PDF||Request a copy|
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