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Cited by 228

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Critical motion sequences for monocular self-calibration and uncalibrated Euclidean reconstruction

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Sturm, P.·2002·Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition
DOI 10.1109/cvpr.1997.609467
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Abstract

In this paper sequences of camera motions that lead to inherent ambiguities in uncalibrated Euclidean reconstruction or self-calibration are studied. Our main contribution is a complete, detailed classification of these critical motion sequences (CMS). The practically important classes are identified and their degrees of ambiguity are derived. We also discuss some practical issues, especially concerning the reduction of the ambiguity of a reconstruction.

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Metadata

Authors
Sturm, P.
Venue
Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Publisher
IEEE Comput. Soc
Published
2002-11-22
Pages
1100-1105
ISSN
1063-6919 (ISSN-L)
DOI
10.1109/cvpr.1997.609467
OpenAlex
W2119577120
Cited by
228
References
0
FWCI
16.69
Type
conference paper
Language
en
Open access
green

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CoChat. (2026). Citation check: Critical motion sequences for monocular self-calibration and uncalibrated Euclidean reconstruction. https://app.cochat.ai/papers/10.1109/cvpr.1997.609467
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Sturm, P. (2002). Critical motion sequences for monocular self-calibration and uncalibrated Euclidean reconstruction. Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. https://doi.org/10.1109/cvpr.1997.609467

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.