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MDL Patch Correspondences on Unlabeled Images

Karlsson, Johan LU and Åström, Karl LU orcid (2008) 19th International Conference on Pattern Recognition (ICPR 2008) p.3249-3253
Abstract
Automatic construction of Shape and Appearance Models from examples

via establishing correspondences across the training set has been successful in the last decades.

One successful measure for establishing correspondences of high quality is minimum description length (MDL).

In other approaches it has been shown that parts+geometry models which model the appearance of parts of the object and the geometric relation between the parts

have been successful for automatic model building.

In this paper it is shown how to fuse the above approaches and use MDL to

fully automatically build optimal parts+geometry models from unlabeled

images.
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
19th International Conference on Pattern Recognition, vols 1-6
pages
3249 - 3253
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
19th International Conference on Pattern Recognition (ICPR 2008)
conference location
Tampa, FL
conference dates
2008-12-08 - 2008-12-11
external identifiers
  • wos:000264729001314
ISSN
1051-4651
ISBN
978-1-4244-2174-9
language
English
LU publication?
yes
id
341c0787-7aac-47d9-b8a4-37d2b2eef3d2 (old id 1275697)
date added to LUP
2016-04-01 13:48:19
date last changed
2020-12-22 02:16:17
@inproceedings{341c0787-7aac-47d9-b8a4-37d2b2eef3d2,
  abstract     = {{Automatic construction of Shape and Appearance Models from examples <br/><br>
via establishing correspondences across the training set has been successful in the last decades.<br/><br>
One successful measure for establishing correspondences of high quality is minimum description length (MDL).<br/><br>
In other approaches it has been shown that parts+geometry models which model the appearance of parts of the object and the geometric relation between the parts<br/><br>
have been successful for automatic model building.<br/><br>
In this paper it is shown how to fuse the above approaches and use MDL to<br/><br>
fully automatically build optimal parts+geometry models from unlabeled <br/><br>
images.}},
  author       = {{Karlsson, Johan and Åström, Karl}},
  booktitle    = {{19th International Conference on Pattern Recognition, vols 1-6}},
  isbn         = {{978-1-4244-2174-9}},
  issn         = {{1051-4651}},
  language     = {{eng}},
  pages        = {{3249--3253}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{MDL Patch Correspondences on Unlabeled Images}},
  year         = {{2008}},
}