Object contour plays an important role in fields such as semantic segmentation and image
classification. However, the extraction of contour is a difficult task, especially when the …

Optimization is a powerful paradigm for expressing and solving problems in a wide range of
areas, and has been successfully applied to many vision problems. Discrete optimization …

This paper addresses the problem of segmenting an image into regions. We define a
predicate for measuring the evidence for a boundary between two regions using a graph …

We describe a geometric-flow-based algorithm for computing a dense oversegmentation of
an image, often referred to as superpixels. It produces segments that, on one hand, respect …

There is a growing demand for image processing in a wide range of applications such as
photography, robotics, television, remote sensing, industrial inspection, and medical …

Efficient segmentation of globally optimal surfaces representing object boundaries in
volumetric data sets is important and challenging in many medical image analysis …

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 …

Graph cut is a popular technique for interactive image segmentation. However, it has certain
shortcomings. In particular, graph cut has problems with segmenting thin elongated objects …

In this correspondence, we develop a novel approach that provides effective and robust
segmentation of color images. By incorporating the advantages of the mean shift (MS) …

Occlusion reasoning is a fundamental problem in computer vision. In this paper, we propose
an algorithm to recover the occlusion boundaries and depth ordering of free-standing …