@inproceedings{rother2006cosegmenting,
author = {Rother, Carsten and Kolmogorov, Vladimir and Minka, Tom and Blake, Andrew},
title = {Cosegmenting Image Pairs by Matching Global Histograms},
booktitle = {Proc. IEEE Computer Vision and Pattern Recognition (CVPR)},
year = {2006},
month = {June},
abstract = {We introduce the term cosegmentation which denotes the task of segmenting simultaneously the common parts of an image pair. A generative model for cosegmentation is presented. Inference in the model leads to minimizing an energy with an MRF term encoding spatial coherency and a global constraint which attempts to match the appearance histograms of the common parts. This energy has not been proposed previously and its optimization is challenging and NP-hard. For this problem a novel optimization scheme which we call trust region graph cuts is presented. We demonstrate that this framework has the potential to improve a wide range of research: Object driven image retrieval, video tracking and segmentation, and interactive image editing. The power of the framework lies in its generality, the common part can be a rigid/non-rigid object (or scene), observed from different viewpoints or even similar objects of the same class.},
url = {http://approjects.co.za/?big=en-us/research/publication/cosegmenting-image-pairs-by-matching-global-histograms/},
edition = {Proc. IEEE Computer Vision and Pattern Recognition (CVPR)},
}