Practical Solutions to the Relative Pose of Three Calibrated Cameras
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00387216" target="_blank" >RIV/68407700:21230/25:00387216 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21730/25:00387216
Result on the web
<a href="https://doi.org/10.1109/CVPR52734.2025.02041" target="_blank" >https://doi.org/10.1109/CVPR52734.2025.02041</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CVPR52734.2025.02041" target="_blank" >10.1109/CVPR52734.2025.02041</a>
Alternative languages
Result language
angličtina
Original language name
Practical Solutions to the Relative Pose of Three Calibrated Cameras
Original language description
We study the challenging problem of estimating the relative pose of three calibrated cameras from four point correspondences. We propose novel efficient solutions to this problem that are based on the simple idea of using four correspondences to estimate an approximate geometry of the first two views. We model this geometry either as an affine or a fully perspective geometry estimated using one additional approximate correspondence. We generate such an approximate correspondence using a very simple and efficient strategy, where the new point is the mean point of three corresponding input points. The new solvers are efficient and easy to implement, since they are based on existing efficient minimal solvers, i.e., the 4-point affine fundamental matrix, the well-known 5-point relative pose solver, and the texttt P3P solver. Extensive experiments on real data show that the proposed solvers, when properly coupled with local optimization, achieve state-of-the-art results, with the novel solver based on approximate mean-point correspondences being more robust and accurate than the affine-based solver.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GM22-23183M" target="_blank" >GM22-23183M: New generation of camera geometry solvers</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
ISBN
979-8-3315-4364-8
ISSN
1063-6919
e-ISSN
2575-7075
Number of pages
11
Pages from-to
21913-21923
Publisher name
IEEE Computer Society
Place of publication
Los Alamitos
Event location
Nashville
Event date
Jun 11, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001601158200363