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Cited by 555

The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.

Computing geodesics and minimal surfaces via graph cuts

Boykov, Kolmogorov·2003·Proceedings Ninth IEEE International Conference on Computer Vision

Abstract

Geodesic active contours and graph cuts are two standard image segmentation techniques. We introduce a new segmentation method combining some of their benefits. Our main intuition is that any cut on a graph embedded in some continuous space can be interpreted as a contour (in 2D) or a surface (in 3D). We show how to build a grid graph and set its edge weights so that the cost of cuts is arbitrarily close to the length (area) of the corresponding contours (surfaces) for any anisotropic Riemannian metric. There are two interesting consequences of this technical result. First, graph cut algorithms can be used to find globally minimum geodesic contours (minimal surfaces in 3D) under arbitrary Riemannian metric for a given set of boundary conditions. Second, we show how to minimize metrication artifacts in existing graph-cut based methods in vision. Theoretically speaking, our work provides an interesting link between several branches of mathematics -differential geometry, integral geometry, and combinatorial optimization. The main technical problem is solved using Cauchy-Crofton formula from integral geometry.

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Metadata

Authors
Boykov, & Kolmogorov
Venue
Proceedings Ninth IEEE International Conference on Computer Vision
Publisher
IEEE
Published
2003
Pages
26-33 vol.1
OpenAlex
W2105365768
Cited by
555
References
26
FWCI
15.55
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Computing geodesics and minimal surfaces via graph cuts. https://app.cochat.ai/papers/10.1109/iccv.2003.1238310
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Boykov, & Kolmogorov. (2003). Computing geodesics and minimal surfaces via graph cuts. Proceedings Ninth IEEE International Conference on Computer Vision. https://doi.org/10.1109/iccv.2003.1238310

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