Relative Pose from Cylinder Silhouettes
Gummeson, Anna LU and Oskarsson, Magnus LU
(2025)
17th Asian Conference on Computer Vision, ACCV 2024
In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
15480 LNCS.
p.245-261
- Abstract
In this paper we propose minimal solvers for relative pose estimation for two views of the projected silhouettes of two 3D cylinders. Using such line features instead of the standard point feature correspondences means more stable information (i.e. more stable to lighting condition, seasons, changes in environment etc.). Such features also lead to more compact and semantically interpretable representations in 3D as opposed to standard 3D point feature clouds. In this paper we show how it is possible to transform the problem into a simple parameterization where we can represent the problem as a set of six polynomials and provide solvers for their solutions. Through tests in synthetic and real settings we show that the solver is accurate... (More)
In this paper we propose minimal solvers for relative pose estimation for two views of the projected silhouettes of two 3D cylinders. Using such line features instead of the standard point feature correspondences means more stable information (i.e. more stable to lighting condition, seasons, changes in environment etc.). Such features also lead to more compact and semantically interpretable representations in 3D as opposed to standard 3D point feature clouds. In this paper we show how it is possible to transform the problem into a simple parameterization where we can represent the problem as a set of six polynomials and provide solvers for their solutions. Through tests in synthetic and real settings we show that the solver is accurate and stable in the presence of added and inherent noise. Our code is publicly available. (https://github.com/hamburgerlady/cylinder-SfM).
(Less)
- author
- Gummeson, Anna
LU
and Oskarsson, Magnus
LU
- organization
- publishing date
- 2025
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Cylinder geometry, Minimal solvers, Relative pose
- host publication
- Computer Vision – ACCV 2024 - 17th Asian Conference on Computer Vision, Proceedings
- series title
- Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
- editor
- Cho, Minsu ; Laptev, Ivan ; Tran, Du ; Yao, Angela and Zha, Hongbin
- volume
- 15480 LNCS
- pages
- 17 pages
- publisher
- Springer Science and Business Media B.V.
- conference name
- 17th Asian Conference on Computer Vision, ACCV 2024
- conference location
- Hanoi, Viet Nam
- conference dates
- 2024-12-08 - 2024-12-12
- external identifiers
-
- scopus:85212951791
- ISSN
- 0302-9743
- 1611-3349
- ISBN
- 9789819609680
- DOI
- 10.1007/978-981-96-0969-7_15
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
- id
- 35c684b4-f7ca-4b43-9416-0e3d7c6c1031
- date added to LUP
- 2025-01-22 11:34:38
- date last changed
- 2025-07-10 01:15:25
@inproceedings{35c684b4-f7ca-4b43-9416-0e3d7c6c1031,
abstract = {{<p>In this paper we propose minimal solvers for relative pose estimation for two views of the projected silhouettes of two 3D cylinders. Using such line features instead of the standard point feature correspondences means more stable information (i.e. more stable to lighting condition, seasons, changes in environment etc.). Such features also lead to more compact and semantically interpretable representations in 3D as opposed to standard 3D point feature clouds. In this paper we show how it is possible to transform the problem into a simple parameterization where we can represent the problem as a set of six polynomials and provide solvers for their solutions. Through tests in synthetic and real settings we show that the solver is accurate and stable in the presence of added and inherent noise. Our code is publicly available. (https://github.com/hamburgerlady/cylinder-SfM).</p>}},
author = {{Gummeson, Anna and Oskarsson, Magnus}},
booktitle = {{Computer Vision – ACCV 2024 - 17th Asian Conference on Computer Vision, Proceedings}},
editor = {{Cho, Minsu and Laptev, Ivan and Tran, Du and Yao, Angela and Zha, Hongbin}},
isbn = {{9789819609680}},
issn = {{0302-9743}},
keywords = {{Cylinder geometry; Minimal solvers; Relative pose}},
language = {{eng}},
pages = {{245--261}},
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 = {{Relative Pose from Cylinder Silhouettes}},
url = {{http://dx.doi.org/10.1007/978-981-96-0969-7_15}},
doi = {{10.1007/978-981-96-0969-7_15}},
volume = {{15480 LNCS}},
year = {{2025}},
}