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Euclidean structure from uncalibrated images

Armstrong, M; Zisserman, A and Beardsley, P (1994) BMVC94. Proceedings of the 5th British Machine Vision Conference In BMVC94. Proceedings of the 5th British Machine Vision Conference 2. p.509-518
Abstract
A number of recent papers have demonstrated that camera “self-calibration” can be accomplished purely from image measurements, without requiring special calibration objects or known camera motion. We describe a method, based on self-calibration, for obtaining (scaled) Euclidean structure from multiple uncalibrated perspective images using only point matches between views. The method is in two stages. First, using an uncalibrated camera, structure is recovered up to an affine ambiguity from two views. Second, from one or more further views of this affine structure the camera intrinsic parameters are determined, and the structure ambiguity reduced to scaled Euclidean. The technique is independent of how the affine structure is obtained. We... (More)
A number of recent papers have demonstrated that camera “self-calibration” can be accomplished purely from image measurements, without requiring special calibration objects or known camera motion. We describe a method, based on self-calibration, for obtaining (scaled) Euclidean structure from multiple uncalibrated perspective images using only point matches between views. The method is in two stages. First, using an uncalibrated camera, structure is recovered up to an affine ambiguity from two views. Second, from one or more further views of this affine structure the camera intrinsic parameters are determined, and the structure ambiguity reduced to scaled Euclidean. The technique is independent of how the affine structure is obtained. We analyse its limitations and degeneracies. Results are given for images of real scenes. An application is described for active vision, where a Euclidean reconstruction is obtained during normal operation with an initially uncalibrated camera. Finally, it is demonstrated that Euclidean reconstruction can be obtained from a single perspective image of a repeated structure (Less)
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author
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
active vision, image reconstruction, uncalibrated images, self-calibration, image measurements, Euclidean structure, perspective images, Euclidean reconstruction, camera intrinsic parameters
in
BMVC94. Proceedings of the 5th British Machine Vision Conference
volume
2
pages
509 - 518
publisher
BMVA Press
conference name
BMVC94. Proceedings of the 5th British Machine Vision Conference
ISBN
0 9521898 1 X
language
English
LU publication?
no
id
14445a24-daef-4a97-9057-4e64fe6068b5 (old id 787182)
date added to LUP
2008-09-16 14:31:15
date last changed
2016-06-29 09:15:16
@misc{14445a24-daef-4a97-9057-4e64fe6068b5,
  abstract     = {A number of recent papers have demonstrated that camera “self-calibration” can be accomplished purely from image measurements, without requiring special calibration objects or known camera motion. We describe a method, based on self-calibration, for obtaining (scaled) Euclidean structure from multiple uncalibrated perspective images using only point matches between views. The method is in two stages. First, using an uncalibrated camera, structure is recovered up to an affine ambiguity from two views. Second, from one or more further views of this affine structure the camera intrinsic parameters are determined, and the structure ambiguity reduced to scaled Euclidean. The technique is independent of how the affine structure is obtained. We analyse its limitations and degeneracies. Results are given for images of real scenes. An application is described for active vision, where a Euclidean reconstruction is obtained during normal operation with an initially uncalibrated camera. Finally, it is demonstrated that Euclidean reconstruction can be obtained from a single perspective image of a repeated structure},
  author       = {Armstrong, M and Zisserman, A and Beardsley, P},
  isbn         = {0 9521898 1 X},
  keyword      = {active vision,image reconstruction,uncalibrated images,self-calibration,image measurements,Euclidean structure,perspective images,Euclidean reconstruction,camera intrinsic parameters},
  language     = {eng},
  pages        = {509--518},
  publisher    = {ARRAY(0xb3b2ac0)},
  series       = {BMVC94. Proceedings of the 5th British Machine Vision Conference},
  title        = {Euclidean structure from uncalibrated images},
  volume       = {2},
  year         = {1994},
}