@inproceedings{3188, 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.}, author = {Rother, Carsten and Vladimir Kolmogorov and Minka, Thomas P and Blake, Andrew}, pages = {993 -- 1000}, publisher = {IEEE}, title = {{Cosegmentation of image pairs by histogram matching - Incorporating a global constraint into MRFs}}, doi = {10.1109/CVPR.2006.91}, year = {2006}, }