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Camera Pose Estimation with Unknown Principal Point

Larsson, Viktor LU ; Kukelova, Zuzana and Zheng, Yinqiang (2018) 31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018 p.2984-2992
Abstract

To estimate the 6-DoF extrinsic pose of a pinhole camera with partially unknown intrinsic parameters is a critical sub-problem in structure-from-motion and camera localization. In most of existing camera pose estimation solvers, the principal point is assumed to be in the image center. Unfortunately, this assumption is not always true, especially for asymmetrically cropped images. In this paper, we develop the first exactly minimal solver for the case of unknown principal point and focal length by using four and a half point correspondences (P4.5Pfuv). We also present an extremely fast solver for the case of unknown aspect ratio (P5Pfuva). The new solvers outperform the previous state-of-the-art in terms of stability and speed. Finally,... (More)

To estimate the 6-DoF extrinsic pose of a pinhole camera with partially unknown intrinsic parameters is a critical sub-problem in structure-from-motion and camera localization. In most of existing camera pose estimation solvers, the principal point is assumed to be in the image center. Unfortunately, this assumption is not always true, especially for asymmetrically cropped images. In this paper, we develop the first exactly minimal solver for the case of unknown principal point and focal length by using four and a half point correspondences (P4.5Pfuv). We also present an extremely fast solver for the case of unknown aspect ratio (P5Pfuva). The new solvers outperform the previous state-of-the-art in terms of stability and speed. Finally, we explore the extremely challenging case of both unknown principal point and radial distortion, and develop the first practical non-minimal solver by using seven point correspondences (P7Pfruv). Experimental results on both simulated data and real Internet images demonstrate the usefulness of our new solvers.

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type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
Proceedings - 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018
article number
8578413
pages
9 pages
publisher
IEEE Computer Society
conference name
31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018
conference location
Salt Lake City, United States
conference dates
2018-06-18 - 2018-06-22
external identifiers
  • scopus:85062873188
ISBN
9781538664209
DOI
10.1109/CVPR.2018.00315
language
English
LU publication?
yes
id
ea9bd918-8435-4266-ab4c-4b1b0bb71cfe
date added to LUP
2019-04-01 09:38:01
date last changed
2020-12-29 02:00:51
@inproceedings{ea9bd918-8435-4266-ab4c-4b1b0bb71cfe,
  abstract     = {<p>To estimate the 6-DoF extrinsic pose of a pinhole camera with partially unknown intrinsic parameters is a critical sub-problem in structure-from-motion and camera localization. In most of existing camera pose estimation solvers, the principal point is assumed to be in the image center. Unfortunately, this assumption is not always true, especially for asymmetrically cropped images. In this paper, we develop the first exactly minimal solver for the case of unknown principal point and focal length by using four and a half point correspondences (P4.5Pfuv). We also present an extremely fast solver for the case of unknown aspect ratio (P5Pfuva). The new solvers outperform the previous state-of-the-art in terms of stability and speed. Finally, we explore the extremely challenging case of both unknown principal point and radial distortion, and develop the first practical non-minimal solver by using seven point correspondences (P7Pfruv). Experimental results on both simulated data and real Internet images demonstrate the usefulness of our new solvers.</p>},
  author       = {Larsson, Viktor and Kukelova, Zuzana and Zheng, Yinqiang},
  booktitle    = {Proceedings - 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018},
  isbn         = {9781538664209},
  language     = {eng},
  month        = {12},
  pages        = {2984--2992},
  publisher    = {IEEE Computer Society},
  title        = {Camera Pose Estimation with Unknown Principal Point},
  url          = {http://dx.doi.org/10.1109/CVPR.2018.00315},
  doi          = {10.1109/CVPR.2018.00315},
  year         = {2018},
}