Fast Non-minimal Solvers for Planar Motion Compatible Homographies
(2019) 8th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2019 p.40-51- Abstract
This paper presents a novel polynomial constraint for homographies compatible with the general planar motion model. In this setting, compatible homographies have five degrees of freedom-instead of the general case of eight degrees of freedom-and, as a consequence, a minimal solver requires 2.5 point correspondences. The existing minimal solver, however, is computationally expensive, and we propose using non-minimal solvers, which significantly reduces the execution time of obtaining a compatible homography, with accuracy and robustness comparable to that of the minimal solver. The proposed solvers are compared with the minimal solver and the traditional 4-point solver on synthetic and real data, and demonstrate good performance, in... (More)
This paper presents a novel polynomial constraint for homographies compatible with the general planar motion model. In this setting, compatible homographies have five degrees of freedom-instead of the general case of eight degrees of freedom-and, as a consequence, a minimal solver requires 2.5 point correspondences. The existing minimal solver, however, is computationally expensive, and we propose using non-minimal solvers, which significantly reduces the execution time of obtaining a compatible homography, with accuracy and robustness comparable to that of the minimal solver. The proposed solvers are compared with the minimal solver and the traditional 4-point solver on synthetic and real data, and demonstrate good performance, in terms of speed and accuracy. By decomposing the homographies obtained from the different methods, it is shown that the proposed solvers have future potential to be incorporated in a complete Simultaneous Localization and Mapping (SLAM) framework.
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- author
- Örnhag, Marcus Valtonen LU
- organization
- publishing date
- 2019
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Homography, Planar Motion, Polynomial Solver, Trajectory Recovery, Visual Odometry
- host publication
- ICPRAM 2019 - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods
- editor
- Fred, Ana ; De Marsico, Maria and di Baja, Gabriella Sanniti
- pages
- 12 pages
- publisher
- SciTePress
- conference name
- 8th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2019
- conference location
- Prague, Czech Republic
- conference dates
- 2019-02-19 - 2019-02-21
- external identifiers
-
- scopus:85064672606
- ISBN
- 9789897583513
- DOI
- 10.5220/0007258600400051
- language
- English
- LU publication?
- yes
- id
- c66a4767-d45d-44c4-a606-d3518afa9334
- date added to LUP
- 2019-05-06 14:41:14
- date last changed
- 2022-05-11 08:21:58
@inproceedings{c66a4767-d45d-44c4-a606-d3518afa9334,
abstract = {{<p>This paper presents a novel polynomial constraint for homographies compatible with the general planar motion model. In this setting, compatible homographies have five degrees of freedom-instead of the general case of eight degrees of freedom-and, as a consequence, a minimal solver requires 2.5 point correspondences. The existing minimal solver, however, is computationally expensive, and we propose using non-minimal solvers, which significantly reduces the execution time of obtaining a compatible homography, with accuracy and robustness comparable to that of the minimal solver. The proposed solvers are compared with the minimal solver and the traditional 4-point solver on synthetic and real data, and demonstrate good performance, in terms of speed and accuracy. By decomposing the homographies obtained from the different methods, it is shown that the proposed solvers have future potential to be incorporated in a complete Simultaneous Localization and Mapping (SLAM) framework.</p>}},
author = {{Örnhag, Marcus Valtonen}},
booktitle = {{ICPRAM 2019 - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods}},
editor = {{Fred, Ana and De Marsico, Maria and di Baja, Gabriella Sanniti}},
isbn = {{9789897583513}},
keywords = {{Homography; Planar Motion; Polynomial Solver; Trajectory Recovery; Visual Odometry}},
language = {{eng}},
pages = {{40--51}},
publisher = {{SciTePress}},
title = {{Fast Non-minimal Solvers for Planar Motion Compatible Homographies}},
url = {{http://dx.doi.org/10.5220/0007258600400051}},
doi = {{10.5220/0007258600400051}},
year = {{2019}},
}