259 citations · 803 across the 48 of their papers we have counts for
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Optimizing Over Radial Kernels on Compact Manifolds
Sadeep Jayasumana, Richard Hartley, Mathieu Salzmann +2
We tackle the problem of optimizing over all possible positive definite radial kernels on Riemannian manifolds for classification. Kernel methods on Riemannian manifolds have recen…
Kernel Methods on the Riemannian Manifold of Symmetric Positive Definite Matrices
Sadeep Jayasumana, Richard Hartley, Mathieu Salzmann +2
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…
Kernel Methods on Riemannian Manifolds with Gaussian RBF Kernels
Sadeep Jayasumana, Richard Hartley, Mathieu Salzmann +2
In this paper, we develop an approach to exploiting kernel methods with manifold-valued data. In many computer vision problems, the data can be naturally represented as points on a…
Iteratively Reweighted Graph Cut for Multi-label MRFs with Non-convex Priors
Thalaiyasingam Ajanthan, Richard Hartley, Mathieu Salzmann +1
While widely acknowledged as highly effective in computer vision, multi-label MRFs with non-convex priors are difficult to optimize. To tackle this, we introduce an algorithm that…
Sparse Coding on Symmetric Positive Definite Manifolds using Bregman Divergences
Mehrtash Harandi, Richard Hartley, Brian Lovell +1
This paper introduces sparse coding and dictionary learning for Symmetric Positive Definite (SPD) matrices, which are often used in machine learning, computer vision and related ar…
Expanding the Family of Grassmannian Kernels: An Embedding Perspective
Mehrtash T. Harandi, Mathieu Salzmann, Sadeep Jayasumana +2
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 sub…
From Manifold to Manifold: Geometry-Aware Dimensionality Reduction for SPD Matrices
Mehrtash T. Harandi, Mathieu Salzmann, Richard Hartley
Representing images and videos with Symmetric Positive Definite (SPD) matrices and considering the Riemannian geometry of the resulting space has proven beneficial for many recogni…
Extrinsic Methods for Coding and Dictionary Learning on Grassmann Manifolds
Mehrtash Harandi, Richard Hartley, Chunhua Shen +2
Sparsity-based representations have recently led to notable results in various visual recognition tasks. In a separate line of research, Riemannian manifolds have been shown useful…