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Minimal Conditions on Intrinsic Parameters for Euclidean Reconstruction

Heyden, Anders LU and Åström, Karl LU (1997) Computer Vision - ACCV'98 In Computer Vision - ACCV '98. Third Asian Conference on Computer Vision. Proceedings 2. p.169-176
Abstract
We investigate the constraints on the intrinsic parameters that are needed in order to reconstruct an unknown scene from a number of its projective images. Two such minimal cases are studied in detail. Firstly, it is shown that it is sufficient to know the skew parameter, even if all other parameters are unknown and varying, to obtain an Euclidean reconstruction. Secondly, the same thing can be done for known aspect ratio, again when all other intrinsic parameters are unknown and varying. In fact, we show that it is sufficient to know any of the 5 intrinsic parameters to make Euclidean reconstruction. An algorithm, based upon bundle adjustment techniques, to obtain Euclidean reconstruction in the above mentioned cases are presented.... (More)
We investigate the constraints on the intrinsic parameters that are needed in order to reconstruct an unknown scene from a number of its projective images. Two such minimal cases are studied in detail. Firstly, it is shown that it is sufficient to know the skew parameter, even if all other parameters are unknown and varying, to obtain an Euclidean reconstruction. Secondly, the same thing can be done for known aspect ratio, again when all other intrinsic parameters are unknown and varying. In fact, we show that it is sufficient to know any of the 5 intrinsic parameters to make Euclidean reconstruction. An algorithm, based upon bundle adjustment techniques, to obtain Euclidean reconstruction in the above mentioned cases are presented. Experiments are shown on the slightly simpler case of both known aspect ratio and skew (Less)
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
Computer Vision - ACCV '98. Third Asian Conference on Computer Vision. Proceedings
volume
2
pages
169 - 176
publisher
Springer
conference name
Computer Vision - ACCV'98
external identifiers
  • Scopus:84947552480
ISBN
3 540 63931 4
language
English
LU publication?
yes
id
1de6c9b3-7aaa-4e0c-b023-fb760dfb6bc1 (old id 787280)
date added to LUP
2008-05-26 16:41:40
date last changed
2016-10-13 04:37:08
@misc{1de6c9b3-7aaa-4e0c-b023-fb760dfb6bc1,
  abstract     = {We investigate the constraints on the intrinsic parameters that are needed in order to reconstruct an unknown scene from a number of its projective images. Two such minimal cases are studied in detail. Firstly, it is shown that it is sufficient to know the skew parameter, even if all other parameters are unknown and varying, to obtain an Euclidean reconstruction. Secondly, the same thing can be done for known aspect ratio, again when all other intrinsic parameters are unknown and varying. In fact, we show that it is sufficient to know any of the 5 intrinsic parameters to make Euclidean reconstruction. An algorithm, based upon bundle adjustment techniques, to obtain Euclidean reconstruction in the above mentioned cases are presented. Experiments are shown on the slightly simpler case of both known aspect ratio and skew},
  author       = {Heyden, Anders and Åström, Karl},
  isbn         = {3 540 63931 4},
  language     = {eng},
  pages        = {169--176},
  publisher    = {ARRAY(0xb260060)},
  series       = {Computer Vision - ACCV '98. Third Asian Conference on Computer Vision. Proceedings},
  title        = {Minimal Conditions on Intrinsic Parameters for Euclidean Reconstruction},
  volume       = {2},
  year         = {1997},
}