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Robust Fitting for Multiple View Geometry

Enqvist, Olof LU ; Ask, Erik LU ; Kahl, Fredrik LU and Åström, Karl LU (2012) 12th European Conference on Computer Vision (ECCV 2012) In Lecture Notes in Computer Science (Computer Vision - ECCV 2012, Proceedings of the 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Part I ) 7572. p.738-751
Abstract
How hard are geometric vision problems with outliers? We show that for most fitting problems, a solution that minimizes the num- ber of outliers can be found with an algorithm that has polynomial time- complexity in the number of points (independent of the rate of outliers). Further, and perhaps more interestingly, other cost functions such as the truncated L2 -norm can also be handled within the same framework with the same time complexity. We apply our framework to triangulation, relative pose problems and stitching, and give several other examples that fulfill the required condi- tions. Based on efficient polynomial equation solvers, it is experimentally demonstrated that these problems can be solved reliably, in particular for... (More)
How hard are geometric vision problems with outliers? We show that for most fitting problems, a solution that minimizes the num- ber of outliers can be found with an algorithm that has polynomial time- complexity in the number of points (independent of the rate of outliers). Further, and perhaps more interestingly, other cost functions such as the truncated L2 -norm can also be handled within the same framework with the same time complexity. We apply our framework to triangulation, relative pose problems and stitching, and give several other examples that fulfill the required condi- tions. Based on efficient polynomial equation solvers, it is experimentally demonstrated that these problems can be solved reliably, in particular for low-dimensional models. Comparisons to standard random sampling solvers are also given. (Less)
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
geometry, optimization, computer vision
in
Lecture Notes in Computer Science (Computer Vision - ECCV 2012, Proceedings of the 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Part I )
editor
Fitzgibbon, Andrew; Lazebnik, Svetlana; Perona, Pietro; Sato, Yoichi; Schmid, Cordelia; ; ; ; and
volume
7572
pages
14 pages
publisher
Springer
conference name
12th European Conference on Computer Vision (ECCV 2012)
external identifiers
  • scopus:84867878992
ISSN
1611-3349
0302-9743
ISBN
978-3-642-33717-8 (print)
978-3-642-33718-5 (online)
DOI
10.1007/978-3-642-33718-5_53
language
English
LU publication?
yes
id
981178b1-2700-4606-af41-534ee7ee2fdb (old id 3218091)
date added to LUP
2013-01-31 17:41:58
date last changed
2017-10-22 03:10:53
@inproceedings{981178b1-2700-4606-af41-534ee7ee2fdb,
  abstract     = {How hard are geometric vision problems with outliers? We show that for most fitting problems, a solution that minimizes the num- ber of outliers can be found with an algorithm that has polynomial time- complexity in the number of points (independent of the rate of outliers). Further, and perhaps more interestingly, other cost functions such as the truncated L2 -norm can also be handled within the same framework with the same time complexity. We apply our framework to triangulation, relative pose problems and stitching, and give several other examples that fulfill the required condi- tions. Based on efficient polynomial equation solvers, it is experimentally demonstrated that these problems can be solved reliably, in particular for low-dimensional models. Comparisons to standard random sampling solvers are also given.},
  author       = {Enqvist, Olof and Ask, Erik and Kahl, Fredrik and Åström, Karl},
  booktitle    = {Lecture Notes in Computer Science (Computer Vision - ECCV 2012, Proceedings of the 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Part I )},
  editor       = {Fitzgibbon, Andrew and Lazebnik, Svetlana and Perona, Pietro and Sato, Yoichi and Schmid, Cordelia},
  isbn         = {978-3-642-33717-8 (print)},
  issn         = {1611-3349},
  keyword      = {geometry,optimization,computer vision},
  language     = {eng},
  pages        = {738--751},
  publisher    = {Springer},
  title        = {Robust Fitting for Multiple View Geometry},
  url          = {http://dx.doi.org/10.1007/978-3-642-33718-5_53},
  volume       = {7572},
  year         = {2012},
}