Robust and Accurate Cylinder Triangulation
Gummeson, Anna LU and Oskarsson, Magnus LU
(2023)
23nd Scandinavian Conference on Image Analysis, SCIA 2023
In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
13886 LNCS.
p.451-466
- Abstract
In this paper we present methods for triangulation of infinite cylinders from image line silhouettes. We show numerically that linear estimation of a general quadric surface is inherently a badly posed problem. Instead we propose to constrain the conic section to a circle, and give algebraic constraints on the dual conic, that models this manifold. Using these constraints we derive a fast minimal solver based on three image silhouette lines, that can be used to bootstrap robust estimation schemes such as RANSAC. We also present a constrained least squares solver that can incorporate all available image lines for accurate estimation. The algorithms are tested on both synthetic and real data, where they are shown to give accurate results,... (More)
In this paper we present methods for triangulation of infinite cylinders from image line silhouettes. We show numerically that linear estimation of a general quadric surface is inherently a badly posed problem. Instead we propose to constrain the conic section to a circle, and give algebraic constraints on the dual conic, that models this manifold. Using these constraints we derive a fast minimal solver based on three image silhouette lines, that can be used to bootstrap robust estimation schemes such as RANSAC. We also present a constrained least squares solver that can incorporate all available image lines for accurate estimation. The algorithms are tested on both synthetic and real data, where they are shown to give accurate results, compared to previous methods.
(Less)
- author
- Gummeson, Anna
LU
and Oskarsson, Magnus
LU
- organization
- publishing date
- 2023
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Cylinders, Reconstruction, Robust estimation
- host publication
- Image Analysis - 23rd Scandinavian Conference, SCIA 2023, Proceedings
- series title
- Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
- editor
- Gade, Rikke ; Felsberg, Michael and Kämäräinen, Joni-Kristian
- volume
- 13886 LNCS
- pages
- 16 pages
- publisher
- Springer Science and Business Media B.V.
- conference name
- 23nd Scandinavian Conference on Image Analysis, SCIA 2023
- conference location
- Lapland, Finland
- conference dates
- 2023-04-18 - 2023-04-21
- external identifiers
-
- scopus:85161428689
- ISSN
- 1611-3349
- 0302-9743
- ISBN
- 9783031314377
- DOI
- 10.1007/978-3-031-31438-4_30
- language
- English
- LU publication?
- yes
- id
- 7c9681ba-299f-4ef9-bbc8-69c588049d08
- date added to LUP
- 2023-08-22 13:24:11
- date last changed
- 2024-04-20 01:15:40
@inproceedings{7c9681ba-299f-4ef9-bbc8-69c588049d08,
abstract = {{<p>In this paper we present methods for triangulation of infinite cylinders from image line silhouettes. We show numerically that linear estimation of a general quadric surface is inherently a badly posed problem. Instead we propose to constrain the conic section to a circle, and give algebraic constraints on the dual conic, that models this manifold. Using these constraints we derive a fast minimal solver based on three image silhouette lines, that can be used to bootstrap robust estimation schemes such as RANSAC. We also present a constrained least squares solver that can incorporate all available image lines for accurate estimation. The algorithms are tested on both synthetic and real data, where they are shown to give accurate results, compared to previous methods.</p>}},
author = {{Gummeson, Anna and Oskarsson, Magnus}},
booktitle = {{Image Analysis - 23rd Scandinavian Conference, SCIA 2023, Proceedings}},
editor = {{Gade, Rikke and Felsberg, Michael and Kämäräinen, Joni-Kristian}},
isbn = {{9783031314377}},
issn = {{1611-3349}},
keywords = {{Cylinders; Reconstruction; Robust estimation}},
language = {{eng}},
pages = {{451--466}},
publisher = {{Springer Science and Business Media B.V.}},
series = {{Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}},
title = {{Robust and Accurate Cylinder Triangulation}},
url = {{http://dx.doi.org/10.1007/978-3-031-31438-4_30}},
doi = {{10.1007/978-3-031-31438-4_30}},
volume = {{13886 LNCS}},
year = {{2023}},
}