An Efficient Solution to the Homography-Based Relative Pose Problem With a Common Reference Direction
(2019) 2019 IEEE/CVF International Conference on Computer Vision (ICCV)- Abstract
- In this paper, we propose a novel approach to two-view minimal-case relative pose problems based on homography with a common reference direction. We explore the rank-1 constraint on the difference between the Euclidean homography matrix and the corresponding rotation, and propose an efficient two-step solution for solving both the calibrated and partially calibrated (unknown focal length) problems. We derive new 3.5-point, 3.5-point, 4-point solvers for two cameras such that the two focal lengths are unknown but equal, one of them is unknown, and both are unknown and possibly different, respectively. We present detailed analyses and comparisons with existing 6 and 7-point solvers, including results with smart phone images.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/74f298dc-8fe2-4620-b28c-040ffe75a881
- author
- Ding, Yaqing LU ; Yang, Jian ; Ponce, Jean and Kong, Hui
- organization
- publishing date
- 2019
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- IEEE/CVF International Conference on Computer Vision (ICCV)
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 2019 IEEE/CVF International Conference on Computer Vision (ICCV)
- conference location
- Seoul, Korea, Republic of
- conference dates
- 2019-10-27 - 2019-11-02
- external identifiers
-
- scopus:85081893412
- ISBN
- 978-1-7281-4804-5
- 978-1-7281-4803-8
- DOI
- 10.1109/ICCV.2019.00174
- language
- English
- LU publication?
- yes
- id
- 74f298dc-8fe2-4620-b28c-040ffe75a881
- date added to LUP
- 2022-09-08 11:36:57
- date last changed
- 2024-03-19 12:49:52
@inproceedings{74f298dc-8fe2-4620-b28c-040ffe75a881, abstract = {{In this paper, we propose a novel approach to two-view minimal-case relative pose problems based on homography with a common reference direction. We explore the rank-1 constraint on the difference between the Euclidean homography matrix and the corresponding rotation, and propose an efficient two-step solution for solving both the calibrated and partially calibrated (unknown focal length) problems. We derive new 3.5-point, 3.5-point, 4-point solvers for two cameras such that the two focal lengths are unknown but equal, one of them is unknown, and both are unknown and possibly different, respectively. We present detailed analyses and comparisons with existing 6 and 7-point solvers, including results with smart phone images.}}, author = {{Ding, Yaqing and Yang, Jian and Ponce, Jean and Kong, Hui}}, booktitle = {{IEEE/CVF International Conference on Computer Vision (ICCV)}}, isbn = {{978-1-7281-4804-5}}, language = {{eng}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{An Efficient Solution to the Homography-Based Relative Pose Problem With a Common Reference Direction}}, url = {{http://dx.doi.org/10.1109/ICCV.2019.00174}}, doi = {{10.1109/ICCV.2019.00174}}, year = {{2019}}, }