21 citations · 75 across the 7 of their papers we have counts for
7 papers
A Joint Intensity and Depth Co-Sparse Analysis Model for Depth Map Super-Resolution
Martin Kiechle, Simon Hawe, Martin Kleinsteuber
High-resolution depth maps can be inferred from low-resolution depth measurements and an additional high-resolution intensity image of the same scene. To that end, we introduce a b…
pROST : A Smoothed Lp-norm Robust Online Subspace Tracking Method for Realtime Background Subtraction in Video
Florian Seidel, Clemens Hage, Martin Kleinsteuber
An increasing number of methods for background subtraction use Robust PCA to identify sparse foreground objects. While many algorithms use the L1-norm as a convex relaxation of the…
Analysis Based Blind Compressive Sensing
Julian Wörmann, Simon Hawe, Martin Kleinsteuber
In this work we address the problem of blindly reconstructing compressively sensed signals by exploiting the co-sparse analysis model. In the analysis model it is assumed that a si…
Separable Dictionary Learning
Simon Hawe, Matthias Seibert, Martin Kleinsteuber
Many techniques in computer vision, machine learning, and statistics rely on the fact that a signal of interest admits a sparse representation over some dictionary. Dictionaries ar…
Robust PCA and subspace tracking from incomplete observations using L0-surrogates
Clemens Hage, Martin Kleinsteuber
Many applications in data analysis rely on the decomposition of a data matrix into a low-rank and a sparse component. Existing methods that tackle this task use the nuclear norm an…
Averaging Complex Subspaces via a Karcher Mean Approach
Knut Hüper, Martin Kleinsteuber, Hao Shen
We propose a conjugate gradient type optimization technique for the computation of the Karcher mean on the set of complex linear subspaces of fixed dimension, modeled by the so-cal…