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From two rolling shutters to one global shutter

Albl, Cenek ; Kukelova, Zuzana ; Larsson, Viktor LU ; Polic, Michal ; Pajdla, Tomas and Schindler, Konrad (2020) 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2020 p.2502-2510
Abstract
Most consumer cameras are equipped with electronic rolling shutter, leading to image distortions when the camera moves during image capture. We explore a surprisingly simple camera configuration that makes it possible to undo the rolling shutter distortion: two cameras mounted to have different rolling shutter directions. Such a setup is easy and cheap to build and it possesses the geometric constraints needed to correct rolling shutter distortion using only a sparse set of point correspondences between the two images. We derive equations that describe the underlying geometry for general and special motions and present an efficient method for finding their solutions. Our synthetic and real experiments demonstrate that our approach is able... (More)
Most consumer cameras are equipped with electronic rolling shutter, leading to image distortions when the camera moves during image capture. We explore a surprisingly simple camera configuration that makes it possible to undo the rolling shutter distortion: two cameras mounted to have different rolling shutter directions. Such a setup is easy and cheap to build and it possesses the geometric constraints needed to correct rolling shutter distortion using only a sparse set of point correspondences between the two images. We derive equations that describe the underlying geometry for general and special motions and present an efficient method for finding their solutions. Our synthetic and real experiments demonstrate that our approach is able to remove large rolling shutter distortions of all types without relying on any specific scene structure. (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
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
pages
9 pages
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:85094806988
DOI
10.1109/CVPR42600.2020.00258
language
English
LU publication?
no
id
99e63534-4cdb-479a-9d99-4ce677151e71
date added to LUP
2022-09-06 11:50:24
date last changed
2022-09-21 14:44:55
@inproceedings{99e63534-4cdb-479a-9d99-4ce677151e71,
  abstract     = {{Most consumer cameras are equipped with electronic rolling shutter, leading to image distortions when the camera moves during image capture. We explore a surprisingly simple camera configuration that makes it possible to undo the rolling shutter distortion: two cameras mounted to have different rolling shutter directions. Such a setup is easy and cheap to build and it possesses the geometric constraints needed to correct rolling shutter distortion using only a sparse set of point correspondences between the two images. We derive equations that describe the underlying geometry for general and special motions and present an efficient method for finding their solutions. Our synthetic and real experiments demonstrate that our approach is able to remove large rolling shutter distortions of all types without relying on any specific scene structure.}},
  author       = {{Albl, Cenek and Kukelova, Zuzana and Larsson, Viktor and Polic, Michal and Pajdla, Tomas and Schindler, Konrad}},
  booktitle    = {{2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}},
  language     = {{eng}},
  pages        = {{2502--2510}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{From two rolling shutters to one global shutter}},
  url          = {{http://dx.doi.org/10.1109/CVPR42600.2020.00258}},
  doi          = {{10.1109/CVPR42600.2020.00258}},
  year         = {{2020}},
}