The Misty Three Point Algorithm for Relative Pose
(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:
https://lup.lub.lu.se/record/a7f27a90-618c-4691-acc6-a596893c5e39
- author
- Palmér, Tobias LU ; Åström, Karl LU and Frahm, Jan Michael
- organization
- publishing date
- 2017-06
- 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}}, }