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MDL Patch Correspondences on Unlabeled Images with Occlusions

Karlsson, Johan LU and Åström, Karl LU (2008) IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR Workshops), 2008 In 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR Workshops) p.999-1006
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
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
computational geometry, image processing, MDL patch correspondence, unlabeled images, occlusions, automatic construction, shape model, appearance model, training set, minimum description length, automatic model building
in
2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR Workshops)
pages
999 - 1006
conference name
IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR Workshops), 2008
external identifiers
  • WOS:000260371900136
  • Scopus:51849093425
ISBN
978-1-4244-2339-2
DOI
10.1109/CVPRW.2008.4563085
language
English
LU publication?
yes
id
0b858499-e8be-4388-9938-489eb96a9665 (old id 1219496)
date added to LUP
2008-09-02 13:29:03
date last changed
2016-10-13 05:02:49
@misc{0b858499-e8be-4388-9938-489eb96a9665,
  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 images.},
  author       = {Karlsson, Johan and Åström, Karl},
  isbn         = {978-1-4244-2339-2},
  keyword      = {computational geometry,image processing,MDL patch correspondence,unlabeled images,occlusions,automatic construction,shape model,appearance model,training set,minimum description length,automatic model building},
  language     = {eng},
  pages        = {999--1006},
  series       = {2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR Workshops)},
  title        = {MDL Patch Correspondences on Unlabeled Images with Occlusions},
  url          = {http://dx.doi.org/10.1109/CVPRW.2008.4563085},
  year         = {2008},
}