Many tasks in computer vision involve assigning a label (such as disparity) to every pixel. A
common constraint is that the labels should vary smoothly almost everywhere while …

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 …

Combinatorial graph cut algorithms have been successfully applied to a wide range of
problems in vision and graphics. This paper focusses on possibly the simplest application of …

We present a bottom-up aggregation approach to image segmentation. Beginning with an
image, we execute a sequence of steps in which pixels are gradually merged to produce …

In this paper we describe a novel algorithm for interactive multilabel segmentation of N-
dimensional images. Given a small number of user-labelled pixels, the rest of the image is …

Geodesic active contours and graph cuts are two standard image segmentation techniques.
We introduce a new segmentation method combining some of their benefits. Our main …

Advances in computer networking and database technologies have enabled the collection
and storage of vast quantities of data. Data mining can extract valuable knowledge from this …

In recent years, segmentation with graph cuts is increasingly used for a variety of
applications, such as photo/video editing, medical image processing, etc. One of the most …

Abstract After [10, 15, 12, 2, 4] minimum cut/maximum flow algorithms on graphs emerged as
an increasingly useful tool for exact or approximate energy minimization in low-level vision …

This paper proposes a new cost function, cut ratio, for segmenting images using graph-
based methods. The cut ratio is defined as the ratio of the corresponding sums of two …