We describe a new optimization scheme for finding high-quality clusterings in planar graphs that uses weighted perfect matching as a subroutine. Our method provides lower-bounds on the energy of the optimal correlation clustering that are typically fast to compute and tight in practice. We demonstrate our algorithm on the problem of image segmentation where this approach outperforms existing global optimization techniques in minimizing the objective and is competitive with the state of the art in producing high-quality segmentations. © 2012 Springer-Verlag.
CITATION STYLE
Yarkony, J., Ihler, A., & Fowlkes, C. C. (2012). Fast planar correlation clustering for image segmentation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7577 LNCS, pp. 568–581). https://doi.org/10.1007/978-3-642-33783-3_41
Mendeley helps you to discover research relevant for your work.