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Minimal Solutions to Relative Pose Estimation From Two Views Sharing a Common Direction With Unknown Focal Length

Ding, Yaqing LU ; Yang, Jian ; Ponce, Jean and Kong, Hui (2020) 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2020
Abstract
We propose minimal solutions to relative pose estimation problem from two views sharing a common direction with unknown focal length. This is relevant for cameras equipped with an IMU (inertial measurement unit), e.g., smart phones, tablets. Similar to the 6-point algorithm for two cameras with unknown but equal focal lengths and 7-point algorithm for two cameras with different and unknown focal lengths, we derive new 4- and 5-point algorithms for these two cases, respectively. The proposed algorithms can cope with coplanar points, which is a degenerate configuration for these 6- and 7-point counterparts. We present a detailed analysis and comparisons with the state of the art. Experimental results on both synthetic data and real images... (More)
We propose minimal solutions to relative pose estimation problem from two views sharing a common direction with unknown focal length. This is relevant for cameras equipped with an IMU (inertial measurement unit), e.g., smart phones, tablets. Similar to the 6-point algorithm for two cameras with unknown but equal focal lengths and 7-point algorithm for two cameras with different and unknown focal lengths, we derive new 4- and 5-point algorithms for these two cases, respectively. The proposed algorithms can cope with coplanar points, which is a degenerate configuration for these 6- and 7-point counterparts. We present a detailed analysis and comparisons with the state of the art. Experimental results on both synthetic data and real images from a smart phone demonstrate the usefulness of the proposed algorithms. (Less)
Please use this url to cite or link to this publication:
author
; ; and
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2020
conference location
Virtual, Online, United States
conference dates
2020-06-14 - 2020-06-19
external identifiers
  • scopus:85094825049
ISBN
978-1-7281-7168-5
978-1-7281-7169-2
DOI
10.1109/CVPR42600.2020.00707
language
English
LU publication?
no
id
ebfb7d23-6596-4e43-b47b-acbf162390cc
date added to LUP
2022-09-08 11:34:55
date last changed
2024-05-15 12:01:50
@inproceedings{ebfb7d23-6596-4e43-b47b-acbf162390cc,
  abstract     = {{We propose minimal solutions to relative pose estimation problem from two views sharing a common direction with unknown focal length. This is relevant for cameras equipped with an IMU (inertial measurement unit), e.g., smart phones, tablets. Similar to the 6-point algorithm for two cameras with unknown but equal focal lengths and 7-point algorithm for two cameras with different and unknown focal lengths, we derive new 4- and 5-point algorithms for these two cases, respectively. The proposed algorithms can cope with coplanar points, which is a degenerate configuration for these 6- and 7-point counterparts. We present a detailed analysis and comparisons with the state of the art. Experimental results on both synthetic data and real images from a smart phone demonstrate the usefulness of the proposed algorithms.}},
  author       = {{Ding, Yaqing and Yang, Jian and Ponce, Jean and Kong, Hui}},
  booktitle    = {{IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}},
  isbn         = {{978-1-7281-7168-5}},
  language     = {{eng}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Minimal Solutions to Relative Pose Estimation From Two Views Sharing a Common Direction With Unknown Focal Length}},
  url          = {{http://dx.doi.org/10.1109/CVPR42600.2020.00707}},
  doi          = {{10.1109/CVPR42600.2020.00707}},
  year         = {{2020}},
}