Partially calibrated semi-generalized pose from hybrid point correspondences |
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Author: | Bhayani, Snehal1; Sattler, Torsten2; Larsson, Viktor3; |
Organizations: |
1Center for Machine Vision and Signal Analysis, University of Oulu, Finland 2Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague 3Lund University, Sweden
4Visual Recognition Group, Faculty of Electrical Engineering, Czech Technical University in Prague
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Format: | article |
Version: | accepted version |
Access: | open |
Online Access: | PDF Full Text (PDF, 1 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe2023031331343 |
Language: | English |
Published: |
Institute of Electrical and Electronics Engineers,
2023
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Publish Date: | 2023-03-13 |
Description: |
AbstractWe study the problem of estimating the semi-generalized pose of a partially calibrated camera, i.e., the pose of a perspective camera with unknown focal length w.r.t. a generalized camera, from a hybrid set of 2D-2D and 2D-3D point correspondences. We study all possible camera configurations within the generalized camera system. To derive practical solvers to previously unsolved challenging configurations, we test different parameterizations as well as different solving strategies based on state-of-the-art methods for generating efficient polynomial solvers. We evaluate the three most promising solvers, i.e., the H51f solver with five 2D-2D correspondences and one 2D-3D match viewed by the same camera inside the generalized camera, the H32f solver with three 2D-2D and two 2D-3D correspondences, and the H13f solver with one 2D-2D and three 2D-3D matches, on synthetic and real data. We show that in the presence of noise in the 3D points these solvers provide better estimates than the corresponding absolute pose solvers. see all
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Series: |
IEEE Winter Conference on Applications of Computer Vision |
ISSN: | 2472-6737 |
ISSN-E: | 2642-9381 |
ISSN-L: | 2472-6737 |
ISBN: | 978-1-6654-9346-8 |
ISBN Print: | 978-1-6654-9347-5 |
Pages: | 2881 - 2890 |
DOI: | 10.1109/WACV56688.2023.00290 |
OADOI: | https://oadoi.org/10.1109/WACV56688.2023.00290 |
Host publication: |
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) |
Conference: |
IEEE/CVF Winter Conference on Applications of Computer Vision |
Type of Publication: |
A4 Article in conference proceedings |
Field of Science: |
113 Computer and information sciences |
Subjects: | |
Funding: |
Torsten Sattler was supported by the EU Horizon 2020 project RICAIP (grant agreement No. 857306) and the European Regional Development Fund under project IMPACT (No. CZ.02.1.01/0.0/0.0/15 003/0000468). Zuzana Kukelova was supported by the OP VVV funded project CZ.02.1.01/0.0/0.0/16 019/0000765 “Research Center for Informatics”. Viktor Larsson was supported by the strategic research project ELLIIT. |
Copyright information: |
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