cvpr2012_oral

On Multiple Foreground Cosegmentation-In this paper, we address a challenging image segmentation

problem called multiple foreground cosegmentation

(MFC), which concerns a realistic scenario in general Webuser

photo sets where a finite number of K foregrounds of

interest repeatedly occur over the entire photo set, but only

an unknown subset of them is presented in each image. This

contrasts the classical cosegmentation problem dealt with

by most existing algorithms, which assume a much simpler

but less realistic setting where the same set of foregrounds

recurs in every image. We propose a novel optimization

method for MFC, which makes no assumption

on foreground configurations and does not suffer from the

aforementioned limitation, while still leverages all the benefits

of having co-occurring or (partially) recurring contents

across images. Our method builds on an iterative scheme

that alternates between a foreground modeling module and

a region assignment module, both highly efficient and scalable.

In part