79 citations · 101 across the 7 of their papers we have counts for
7 papers
Convexity Shape Constraints for Image Segmentation
Loic A. Royer, David L. Richmond, Carsten Rother +2
Segmenting an image into multiple components is a central task in computer vision. In many practical scenarios, prior knowledge about plausible components is available. Incorporati…
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems
Jörg H. Kappes, Bjoern Andres, Fred A. Hamprecht +10
Szeliski et al. published an influential study in 2006 on energy minimization methods for Markov Random Fields (MRF). This study provided valuable insights in choosing the best opt…
OpenGM: A C++ Library for Discrete Graphical Models
Bjoern Andres, Thorsten Beier, Joerg H. Kappes
OpenGM is a C++ template library for defining discrete graphical models and performing inference on these models, using a wide range of state-of-the-art algorithms. No restrictions…
Multi-Hypothesis CRF-Segmentation of Neural Tissue in Anisotropic EM Volumes
Jan Funke, Björn Andres, Fred Hamprecht +2
We present an approach for the joint segmentation and grouping of similar components in anisotropic 3D image data and use it to segment neural tissue in serial sections electron mi…
How to Extract the Geometry and Topology from Very Large 3D Segmentations
Bjoern Andres, Ullrich Koethe, Thorben Kroeger +1
Segmentation is often an essential intermediate step in image analysis. A volume segmentation characterizes the underlying volume image in terms of geometric information--segments,…
The Lazy Flipper: MAP Inference in Higher-Order Graphical Models by Depth-limited Exhaustive Search
Bjoern Andres, Joerg H. Kappes, Ullrich Koethe +1
This article presents a new search algorithm for the NP-hard problem of optimizing functions of binary variables that decompose according to a graphical model. It can be applied to…