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Shift-map Image Registration

Svärm, Linus LU and Strandmark, Petter LU (2010) Swedish Symposium on Image Analysis (SSBA) 2010
Abstract
Shift-map image processing is a new framework based on energy minimization over a large space of labels. The optimization utilizes $\alpha$-expansion moves and iterative refinement over a Gaussian pyramid. In this paper we extend the range of applications to image registration.

To do this, new data and smoothness terms have to be constructed. We note a great improvement when we measure pixel similarities with the dense \daisy\ descriptor. The main contributions of this paper are:



* The extension of the shift-map framework to include image registration. We register images for which \sift\ only provides 3 correct matches.



* The first publicly available implementation of shift-map image... (More)
Shift-map image processing is a new framework based on energy minimization over a large space of labels. The optimization utilizes $\alpha$-expansion moves and iterative refinement over a Gaussian pyramid. In this paper we extend the range of applications to image registration.

To do this, new data and smoothness terms have to be constructed. We note a great improvement when we measure pixel similarities with the dense \daisy\ descriptor. The main contributions of this paper are:



* The extension of the shift-map framework to include image registration. We register images for which \sift\ only provides 3 correct matches.



* The first publicly available implementation of shift-map image processing (e.g. inpainting, registration).



We conclude by comparing shift-map registration to a recent method for optical flow with favorable results. (Less)
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author
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organization
publishing date
type
Contribution to conference
publication status
unpublished
subject
conference name
Swedish Symposium on Image Analysis (SSBA) 2010
conference location
Uppsala, Sweden
conference dates
2010-03-11 - 2010-03-12
language
English
LU publication?
yes
id
ae1d6e0a-c0f0-404d-aba1-2d19c854f704 (old id 1554167)
date added to LUP
2016-04-04 14:09:53
date last changed
2025-04-04 14:08:47
@misc{ae1d6e0a-c0f0-404d-aba1-2d19c854f704,
  abstract     = {{Shift-map image processing is a new framework based on energy minimization over a large space of labels. The optimization utilizes $\alpha$-expansion moves and iterative refinement over a Gaussian pyramid. In this paper we extend the range of applications to image registration. <br/><br>
To do this, new data and smoothness terms have to be constructed. We note a great improvement when we measure pixel similarities with the dense \daisy\ descriptor. The main contributions of this paper are:<br/><br>
<br/><br>
 * The extension of the shift-map framework to include image registration. We register images for which \sift\ only provides 3 correct matches.<br/><br>
<br/><br>
 * The first publicly available implementation of shift-map image processing (e.g. inpainting, registration).<br/><br>
<br/><br>
We conclude by comparing shift-map registration to a recent method for optical flow with favorable results.}},
  author       = {{Svärm, Linus and Strandmark, Petter}},
  language     = {{eng}},
  title        = {{Shift-map Image Registration}},
  url          = {{https://lup.lub.lu.se/search/files/6295742/1554169.pdf}},
  year         = {{2010}},
}