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Journal article

Single view metrology

Abstract:
We describe how 3D affine measurements may be computed from a single perspective view of a scene given only minimal geometric information determined from the image. This minimal information is typically the vanishing line of a reference plane, and a vanishing point for a direction not parallel to the plane. It is shown that affine scene structure may then be determined from the image, without knowledge of the camera’s internal calibration (e.g. focal length), nor of the explicit relation between camera and world (pose).
In particular, we show how to (i) compute the distance between planes parallel to the reference plane (up to a common scale factor); (ii) compute area and length ratios on any plane parallel to the reference plane; (iii) determine the camera’s (viewer’s) location. Simple geometric derivations are given for these results. We also develop an algebraic representation which unifies the three types of measurement and, amongst other advantages, permits a first order error propagation analysis to be performed, associating an uncertainty with each measurement.
We demonstrate the technique for a variety of applications, including height measurements in forensic images and 3D graphical modelling from single images.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1023/a:1026598000963

Authors

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
Brasenose College
Role:
Author
ORCID:
0000-0002-8945-8573


More from this funder
Funder identifier:
https://ror.org/00k4n6c32
Programme:
Esprit Project IMPROOFS


Publisher:
Springer
Journal:
International Journal of Computer Vision More from this journal
Volume:
40
Issue:
2
Pages:
123-148
Publication date:
2000-11-06
DOI:
EISSN:
1573-1405
ISSN:
0920-5691


Language:
English
Pubs id:
61815
Local pid:
pubs:61815
Deposit date:
2024-07-26
ARK identifier:

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