13 citations
- Centre National de la Recherche ScientifiqueFR2 papers
- African Centre for Technology StudiesKE1 paper
- American Institute of Aeronautics and AstronauticsUS1 paper
- Austrian Institute of TechnologyAT1 paper
- École Centrale de LilleFR1 paper
- Eindhoven University of TechnologyNL1 paper
- Graz University of TechnologyAT1 paper
- Institut de Mathématiques de BordeauxFR1 paper
- IT University of CopenhagenDK1 paper
- Johannes Gutenberg University MainzDE1 paper
- Jönköping UniversitySE1 paper
- KU LeuvenBE1 paper
7 papers · 1 filter
On the Choice of Tensor Estimation for Corner Detection, Optical Flow and Denoising
Freddie Åström, Michael Felsberg
Many image processing methods such as corner detection, optical flow and iterative enhancement make use of image tensors. Generally, these tensors are estimated using the structure…
On Tensor-Based PDEs and their Corresponding Variational Formulations with Application to Color Image Denoising
Freddie Åström, George Baravdish, Michael Felsberg
The case when a partial differential equation (PDE) can be considered as an Euler-Lagrange (E-L) equation of an energy functional, consisting of a data term and a smoothness term i…
Targeted Iterative Filtering
Freddie Åström, Michael Felsberg, George Baravdish +1
The assessment of image denoising results depends on the respective application area, i.e. image compression, still-image acquisition, and medical images require entirely different…
Fast Iterative Five point Relative Pose Estimation
Johan Hedborg, Michael Felsberg
Robust estimation of the relative pose between two cameras is a fundamental part of Structure and Motion methods. For calibrated cameras, the five point method together with a robu…
Online Learning of Correspondences between Images
Michael Felsberg, Fredrik Larsson, Johan Wiklund +2
We propose a novel method for iterative learning of point correspondences between image sequences. Points moving on surfaces in 3D space are projected into two images. Given a poin…
Distractor-Aware Video Object Segmentation
Andreas Robinson, Abdelrahman Eldesokey, Michael Felsberg
Semi-supervised video object segmentation is a challenging task that aims to segment a target throughout a video sequence given an initial mask at the first frame. Discriminative a…