Binary Partitioning, Perceptual Grouping, and Restoration with Semidefinite Programming1

Binary Partitioning, Perceptual Grouping, and Restoration with Semidefinite Programming

We introduce a novel optimization method based on semidefinite programming relaxations to the field of computer vision and apply it to the combinatorial problem of minimizing quadratic functionals in binary decision variables subject to linear constraints. The approach is (tuning) parameter-free and computes high-quality combinatorial solutions using interior-point methods (convex programming) ...

Image Labeling and Grouping by Minimizing Linear Functionals over Cones

We consider energy minimization problems related to image labeling, partitioning, and grouping, which typically show up at mid-level stages of computer vision systems. A common feature of these problems is their intrinsic combinatorial complexity from an optimization pointof-view. Rather than trying to compute the global minimum a goal we consider as elusive in these cases we wish to design opt...

Convex Relaxations for Binary Image Partitioning and Perceptual Grouping

Incorporating local image structure in normalized cut based graph partitioning for grouping of pixels

Keywords: Perceptual grouping Early human vision Image pixel grouping Local image structure Graph partitioning Normalized cut a b s t r a c t Graph partitioning for grouping of image pixels has been explored a lot, with normalized cut based graph partitioning being one of the popular ones. In order to have a credible allegiance to the perceptual grouping taking place in early human vision, we p...

Guest Editors' Introduction to the Special Section on Energy Minimization Methods in Computer Vision and Pattern Recognition

ENERGY minimization techniques are central to many methods in computer vision and pattern recognition. Stated simply, if a task can be posed as the minimization of an energy measure, which may, for instance, be the negative logarithm of a probability or an entropy, then a variety of optimization methods may be applied to locate the solution. The solution may be a vector of parameters representi...