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The Misty Three Point Algorithm for Relative Pose

Palmér, Tobias LU ; Åström, Karl LU orcid and Frahm, Jan Michael (2017) IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
Abstract
There is a significant interest in scene reconstruction
from underwater images given its utility for oceanic research
and for recreational image manipulation. In this paper
we propose a novel algorithm for two view camera motion
estimation for underwater imagery. Our method leverages
the constraints provided by the attenuation properties
of water and its effects on the appearance of the color to
determine the depth difference of a point with respect to the
two observing views of the underwater cameras. Additionally,
we propose an algorithm, leveraging the depth differences
of three such observed points, to estimate the relative
pose of the cameras. Given the unknown underwater
attenuation... (More)
There is a significant interest in scene reconstruction
from underwater images given its utility for oceanic research
and for recreational image manipulation. In this paper
we propose a novel algorithm for two view camera motion
estimation for underwater imagery. Our method leverages
the constraints provided by the attenuation properties
of water and its effects on the appearance of the color to
determine the depth difference of a point with respect to the
two observing views of the underwater cameras. Additionally,
we propose an algorithm, leveraging the depth differences
of three such observed points, to estimate the relative
pose of the cameras. Given the unknown underwater
attenuation coefficients, our method estimates the relative
motion up to scale. The results are represented as a generalized
camera. We evaluate our method on both real data
and simulated data. (Less)
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 Conference on Computer Vision and Pattern Recognition (CVPR), 2017
pages
9 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
conference location
Honolulu, United States
conference dates
2017-07-21 - 2017-07-26
external identifiers
  • scopus:85044284630
DOI
10.1109/CVPR.2017.484
language
English
LU publication?
yes
id
a7f27a90-618c-4691-acc6-a596893c5e39
alternative location
https://www.google.se/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=0ahUKEwj46uSLyvbYAhULiiwKHTSQB5oQFggoMAA&url=http%3A%2F%2Fopenaccess.thecvf.com%2Fcontent_cvpr_2017%2Fpapers%2FPalmer_The_Misty_Three_CVPR_2017_paper.pdf&usg=AOvVaw2GxTbAvQ6xSqXMKjCQcQ1H
date added to LUP
2018-01-26 22:36:51
date last changed
2022-05-03 01:05:39
@inproceedings{a7f27a90-618c-4691-acc6-a596893c5e39,
  abstract     = {{There is a significant interest in scene reconstruction<br/>from underwater images given its utility for oceanic research<br/>and for recreational image manipulation. In this paper<br/>we propose a novel algorithm for two view camera motion<br/>estimation for underwater imagery. Our method leverages<br/>the constraints provided by the attenuation properties<br/>of water and its effects on the appearance of the color to<br/>determine the depth difference of a point with respect to the<br/>two observing views of the underwater cameras. Additionally,<br/>we propose an algorithm, leveraging the depth differences<br/>of three such observed points, to estimate the relative<br/>pose of the cameras. Given the unknown underwater<br/>attenuation coefficients, our method estimates the relative<br/>motion up to scale. The results are represented as a generalized<br/>camera. We evaluate our method on both real data<br/>and simulated data.}},
  author       = {{Palmér, Tobias and Åström, Karl and Frahm, Jan Michael}},
  booktitle    = {{IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017}},
  language     = {{eng}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{The Misty Three Point Algorithm for Relative Pose}},
  url          = {{http://dx.doi.org/10.1109/CVPR.2017.484}},
  doi          = {{10.1109/CVPR.2017.484}},
  year         = {{2017}},
}