The Misty Three Point Algorithm for Relative Pose
Palmér, Tobias; Åström, Karl; Frahm, Jan Michael (2017-06). The Misty Three Point Algorithm for Relative Pose IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. Honolulu, United States: IEEE - Institute of Electrical and Electronics Engineers Inc.
Conference Proceeding/Paper
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Published
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English
Authors:
Palmér, Tobias
;
Åström, Karl
;
Frahm, Jan Michael
Department:
Mathematics (Faculty of Engineering)
eSSENCE: The e-Science Collaboration
Mathematical Imaging Group
ELLIIT: the Linköping-Lund initiative on IT and mobile communication
Research Group:
Mathematical Imaging Group
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 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.
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