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Fast Planar Correlation Clustering for Image Segmentation
Julian Yarkony, Alexander Ihler, and Charless C. Fowlkes
Department of Computer Science, University of California, Irvine, USAjyarkony@ics.uci.edu
ihler@ics.uci.edu
fowlkes@ics.uci.edu
Abstract. 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.
LNCS 7577, p. 568 ff.
lncs@springer.com
© Springer-Verlag Berlin Heidelberg 2012