Minimum cut/maximum flow algorithms on graphs have emerged as an increasingly useful
tool for exactor approximate energy minimization in low-level vision. The combinatorial …

State-of-the-art research on MRFs, successful MRF applications, and advanced topics for
future study. This volume demonstrates the power of the Markov random field (MRF) in …

In this paper, we present a comprehensive survey of Markov Random Fields (MRFs) in
computer vision and image understanding, with respect to the modeling, the inference and …

Combinatorial min-cut algorithms on graphs have emerged as an increaseingly useful tool
for problems in vision. Typically, the use of graph-cuts is motivated by one of the following …

We propose a novel MRF-based model for deformable image matching (also known as
registration). The deformation is described by a field of discrete variables, representing …

Optical flow estimation remains challenging due to untextured areas, motion boundaries,
occlusions, and more. Thus, the estimated flow is not equally reliable across the image. To …

Optimization with graph cuts became very popular in recent years. Progress in problems
such as stereo correspondence, image segmentation, etc., can be attributed, in part, to the …

In recent years, there has been an increased interest in using image processing, computer
vision, and machine learning in biological and medical imaging research. One area of this …

Nonrigid registration of contrast-enhanced MR images is a difficult problem due to the
change in pixel intensity caused by the wash-in and wash-out of the contrast agent. In this …

The paper elaborates on the previous research on the analysis of temporal and spatio-
temporal data done in statistical graphics and geo-visualization. We focus on the exploration …