We introduce the term cosegmentation which denotes the task of segmenting
simultaneously the common parts of an image pair. A generative model for cosegmentation …

We study the cosegmentation problem where the objective is to segment the same object
(ie, region) from a pair of images. The segmentation for each image can be cast using a …

Given the knowledge that the same or similar objects appear in a set of images, our goal is
to simultaneously segment that object from the set of images. To solve this problem, known …

We propose a new technique to jointly recover cosegmentation and dense per-pixel
correspondence in two images. Our method parameterizes the correspondence field using …

Co-segmentation is defined as jointly partitioning multiple images depicting the same or
similar object, into foreground and background. Our method consists of a multiple-scale …

We address two key issues of co-segmentation over multiple images. The first is whether a
pure unsupervised algorithm can satisfactorily solve this problem. Without the user's …

We recast the Cosegmentation problem using Random Walker (RW) segmentation as the
core segmentation algorithm, rather than the traditional MRF approach adopted in the …

This paper is focused on the Co-segmentation problem [1]-where the objective is to segment
a similar object from a pair of images. The background in the two images may be arbitrary; …

This paper presents an algorithm for Interactive Co-segmentation of a foreground object
from a group of related images. While previous approaches focus on unsupervised co …

Feature space clustering is a popular approach to image segmentation, in which a feature
vector of local properties (such as intensity, texture or motion) is computed at each pixel. The …