Simplifications of Multilinear forms for Sequences of Images
Heyden, Anders LU
and Åström, Karl
LU
(1997)
In Image and Vision Computing
15(10).
p.749-757
- Abstract
- This paper contains a simplified framework for the analysis of sequences of images taken by uncalibrated cameras. It is assumed that the correspondences between the points in the different images are known. Corresponding points in a sequence of n images are related to each other by a fixed n-linear form. This form is an object invariant property, closely linked to the motion of the camera relative to the fixed world. We first describe a reduced setting in which these multilinear forms are easier to understand and analyse. This new formulation of the multilinear forms is then extended to the calibrated case and the traditional uncalibrated case, thus highlighting the similarities between the different settings. The framework is of... (More)
- This paper contains a simplified framework for the analysis of sequences of images taken by uncalibrated cameras. It is assumed that the correspondences between the points in the different images are known. Corresponding points in a sequence of n images are related to each other by a fixed n-linear form. This form is an object invariant property, closely linked to the motion of the camera relative to the fixed world. We first describe a reduced setting in which these multilinear forms are easier to understand and analyse. This new formulation of the multilinear forms is then extended to the calibrated case and the traditional uncalibrated case, thus highlighting the similarities between the different settings. The framework is of importance as a theoretical tool for understanding the algebra of multiple view geometry, but it is also a basis for constructing linear algorithms for the recovery of structure and motion from image sequences. This is illustrated in experiments. (C) 1997 Elsevier Science B.V. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/788208
- author
- Heyden, Anders
LU
and Åström, Karl
LU
- organization
- publishing date
- 1997
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- computer vision, visual reconstruction, projective geometry, multiple-view, invarian
- in
- Image and Vision Computing
- volume
- 15
- issue
- 10
- pages
- 749 - 757
- publisher
- Elsevier
- external identifiers
-
- scopus:0031257950
- ISSN
- 0262-8856
- DOI
- 10.1016/S0262-8856(97)00005-X
- language
- English
- LU publication?
- yes
- id
- e679f42b-0ea2-45b8-9c79-b9b22db338ba (old id 788208)
- alternative location
- http://www.sciencedirect.com/science?_ob=MImg&_imagekey=B6V09-3SP2RHV-2-1&_cdi=5641&_user=745831&_orig=search&_coverDate=10%2F01%2F1997&_sk=999849989&view=c&wchp=dGLbVlz-zSkzk&md5=b4df4bd5470f26db8c7302ad455504e6&ie=/sdarticle.pdf
- date added to LUP
- 2016-04-04 09:32:21
- date last changed
- 2023-10-18 04:15:32
@article{e679f42b-0ea2-45b8-9c79-b9b22db338ba,
abstract = {{This paper contains a simplified framework for the analysis of sequences of images taken by uncalibrated cameras. It is assumed that the correspondences between the points in the different images are known. Corresponding points in a sequence of n images are related to each other by a fixed n-linear form. This form is an object invariant property, closely linked to the motion of the camera relative to the fixed world. We first describe a reduced setting in which these multilinear forms are easier to understand and analyse. This new formulation of the multilinear forms is then extended to the calibrated case and the traditional uncalibrated case, thus highlighting the similarities between the different settings. The framework is of importance as a theoretical tool for understanding the algebra of multiple view geometry, but it is also a basis for constructing linear algorithms for the recovery of structure and motion from image sequences. This is illustrated in experiments. (C) 1997 Elsevier Science B.V.}},
author = {{Heyden, Anders and Åström, Karl}},
issn = {{0262-8856}},
keywords = {{computer vision; visual reconstruction; projective geometry; multiple-view; invarian}},
language = {{eng}},
number = {{10}},
pages = {{749--757}},
publisher = {{Elsevier}},
series = {{Image and Vision Computing}},
title = {{Simplifications of Multilinear forms for Sequences of Images}},
url = {{http://dx.doi.org/10.1016/S0262-8856(97)00005-X}},
doi = {{10.1016/S0262-8856(97)00005-X}},
volume = {{15}},
year = {{1997}},
}