Robust Fitting for Multiple View Geometry
(2012) 12th European Conference on Computer Vision (ECCV 2012) 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:
https://lup.lub.lu.se/record/3218091
- author
- Enqvist, Olof LU ; Ask, Erik LU ; Kahl, Fredrik LU and Åström, Karl LU
- organization
- publishing date
- 2012
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- geometry, optimization, computer vision
- host publication
- 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 and Schmid, Cordelia
- volume
- 7572
- pages
- 14 pages
- publisher
- Springer
- conference name
- 12th European Conference on Computer Vision (ECCV 2012)
- conference location
- Florence, Italy
- conference dates
- 2012-10-07 - 2012-10-13
- 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
- 2016-04-01 10:15:02
- date last changed
- 2024-09-08 20:23:38
@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}}, keywords = {{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}}, doi = {{10.1007/978-3-642-33718-5_53}}, volume = {{7572}}, year = {{2012}}, }