Factorization with erroneous data
Aanæs, Henrik ; Fisker, Rune ; Åström, Kalle LU
and Carstensen, Jens Michael
(2002)
2002 International Symposium of ISPRS Commission III on Photogrammetric Computer Vision, PCV 2002
- Abstract
Factorization algorithms for recovering structure and motion from an image stream have many advantages, but traditionally requires a set of well tracked feature points. This limits the usability since, correctly tracked feature points are not available in general. There is thus a need to make factorization algorithms deal successfully with incorrectly tracked feature points. We propose a new computationally efficient algorithm for applying an arbitrary error function in the factorization scheme, and thereby enable the use of robust statistical techniques and arbitrary noise models for individual feature points. These techniques and models effectively deal with feature point noise as well as feature mismatch and missing features.... (More)
Factorization algorithms for recovering structure and motion from an image stream have many advantages, but traditionally requires a set of well tracked feature points. This limits the usability since, correctly tracked feature points are not available in general. There is thus a need to make factorization algorithms deal successfully with incorrectly tracked feature points. We propose a new computationally efficient algorithm for applying an arbitrary error function in the factorization scheme, and thereby enable the use of robust statistical techniques and arbitrary noise models for individual feature points. These techniques and models effectively deal with feature point noise as well as feature mismatch and missing features. Furthermore, the algorithm includes a new method for Euclidean reconstruction that experimentally shows a significant improvement in convergence of the factorization algorithms. The proposed algorithm has been implemented in the Christy–Horaud factorization scheme and the results clearly illustrate a considerable increase in error tolerance.
(Less)
- author
- Aanæs, Henrik
; Fisker, Rune
; Åström, Kalle
LU
and Carstensen, Jens Michael
- organization
- publishing date
- 2002
- type
- Contribution to conference
- publication status
- published
- subject
- keywords
- Euclidean reconstruction, Feature tracking, Robust statistics, Structure from motion
- conference name
- 2002 International Symposium of ISPRS Commission III on Photogrammetric Computer Vision, PCV 2002
- conference location
- Graz, Austria
- conference dates
- 2002-09-09 - 2002-09-13
- external identifiers
-
- scopus:85052384472
- language
- English
- LU publication?
- yes
- id
- a779ec25-1131-4a08-b7d4-c8d56db54ed7
- alternative location
- https://www.isprs.org/proceedings/xxxiv/part3/papers/paper032.pdf
- date added to LUP
- 2020-11-02 08:59:49
- date last changed
- 2023-01-02 12:49:12
@misc{a779ec25-1131-4a08-b7d4-c8d56db54ed7,
abstract = {{<p>Factorization algorithms for recovering structure and motion from an image stream have many advantages, but traditionally requires a set of well tracked feature points. This limits the usability since, correctly tracked feature points are not available in general. There is thus a need to make factorization algorithms deal successfully with incorrectly tracked feature points. We propose a new computationally efficient algorithm for applying an arbitrary error function in the factorization scheme, and thereby enable the use of robust statistical techniques and arbitrary noise models for individual feature points. These techniques and models effectively deal with feature point noise as well as feature mismatch and missing features. Furthermore, the algorithm includes a new method for Euclidean reconstruction that experimentally shows a significant improvement in convergence of the factorization algorithms. The proposed algorithm has been implemented in the Christy–Horaud factorization scheme and the results clearly illustrate a considerable increase in error tolerance.</p>}},
author = {{Aanæs, Henrik and Fisker, Rune and Åström, Kalle and Carstensen, Jens Michael}},
keywords = {{Euclidean reconstruction; Feature tracking; Robust statistics; Structure from motion}},
language = {{eng}},
title = {{Factorization with erroneous data}},
url = {{https://www.isprs.org/proceedings/xxxiv/part3/papers/paper032.pdf}},
year = {{2002}},
}