Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

An Efficient Solution to the Homography-Based Relative Pose Problem With a Common Reference Direction

Ding, Yaqing LU ; Yang, Jian ; Ponce, Jean and Kong, Hui (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:
author
; ; and
organization
publishing date
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}},
}