Shortest Paths with Curvature and Torsion
(2013) IEEE International Conference on Computer Vision (ICCV), 2013 p.2024-2031- 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... (More)
- 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 (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4433632
- author
- Strandmark, Petter LU ; Ulén, Johannes LU ; Kahl, Fredrik LU and Grady, Leo
- organization
- publishing date
- 2013
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Computer Vision (ICCV), 2013 IEEE International Conference on
- pages
- 8 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- IEEE International Conference on Computer Vision (ICCV), 2013
- conference location
- Sydney, Australia
- conference dates
- 2013-12-01 - 2013-12-08
- external identifiers
-
- scopus:84898817363
- wos:000351830500253
- ISSN
- 1550-5499
- DOI
- 10.1109/ICCV.2013.253
- language
- English
- LU publication?
- yes
- id
- 0eae30db-c36a-4026-948e-26b46437bba5 (old id 4433632)
- alternative location
- http://www.cv-foundation.org/openaccess/content_iccv_2013/papers/Strandmark_Shortest_Paths_with_2013_ICCV_paper.pdf
- date added to LUP
- 2016-04-01 13:13:01
- date last changed
- 2022-05-19 18:13:32
@inproceedings{0eae30db-c36a-4026-948e-26b46437bba5, 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}}, author = {{Strandmark, Petter and Ulén, Johannes and Kahl, Fredrik and Grady, Leo}}, booktitle = {{Computer Vision (ICCV), 2013 IEEE International Conference on}}, issn = {{1550-5499}}, language = {{eng}}, pages = {{2024--2031}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Shortest Paths with Curvature and Torsion}}, url = {{https://lup.lub.lu.se/search/files/3233805/4433635.pdf}}, doi = {{10.1109/ICCV.2013.253}}, year = {{2013}}, }