Shortest Paths with Curvature and Torsion

Abstract

This paper describes a method of finding thin, elongated structures in images and volumes. We use shortest paths to minimize very general functionals of higher-order curve properties, such as curvature and torsion. Our globally optimal method uses line graphs and its runtime is polynomial in the size of the discretization, often in the order of seconds on a single computer. To our knowledge, we are the first to perform experiments in three dimensions with curvature and torsion regularization. The largest graphs we process have almost one hundred billion arcs. Experiments on medical images and in multi-view reconstruction show the significance and practical usefulness of regularization based on curvature while torsion is still only tractable for small-scale problems.

Cite

Text

Strandmark et al. "Shortest Paths with Curvature and Torsion." International Conference on Computer Vision, 2013. doi:10.1109/ICCV.2013.253

Markdown

[Strandmark et al. "Shortest Paths with Curvature and Torsion." International Conference on Computer Vision, 2013.](https://mlanthology.org/iccv/2013/strandmark2013iccv-shortest/) doi:10.1109/ICCV.2013.253

BibTeX

@inproceedings{strandmark2013iccv-shortest,
  title     = {{Shortest Paths with Curvature and Torsion}},
  author    = {Strandmark, Petter and Ulen, Johannes and Kahl, Fredrik and Grady, Leo},
  booktitle = {International Conference on Computer Vision},
  year      = {2013},
  doi       = {10.1109/ICCV.2013.253},
  url       = {https://mlanthology.org/iccv/2013/strandmark2013iccv-shortest/}
}