Joint Cuts and Matching of Partitions in One Graph

Tianshu Yu, Junchi Yan, Jieyi Zhao, Baoxin Li; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018, pp. 705-713

Abstract


As two fundamental problems, graph cuts and graph matching have been intensively investigated over the decades, resulting in vast literature in these two topics respectively. However the way of jointly applying and solving graph cuts and matching receives few attention. In this paper, we first formalize the problem of simultaneously cutting a graph into two partitions i.e. graph cuts and establishing their correspondence i.e. graph matching. Then we develop an optimization algorithm by updating matching and cutting alternatively, provided with theoretical analysis. The efficacy of our algorithm is verified on both synthetic dataset and real-world images containing similar regions or structures.

Related Material


[pdf] [arXiv]
[bibtex]
@InProceedings{Yu_2018_CVPR,
author = {Yu, Tianshu and Yan, Junchi and Zhao, Jieyi and Li, Baoxin},
title = {Joint Cuts and Matching of Partitions in One Graph},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2018}
}