Minimal solutions for panoramic stitching

Matthew Brown; Richard I. Hartley; David Nistér

doi:10.1109/CVPR.2007.383082

Minimal solutions for panoramic stitching

Matthew Brown^*, Richard I. Hartley, David Nistér

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › peer-review

63 Citations (SciVal)

Abstract

This paper presents minimal solutions for the geometric parameters of a camera rotating about its optical centre. In particular we present new 2 and 3 point solutions for the homography induced by a rotation with 1 and 2 unknown focal length parameters. Using tests on real data, we show that these algorithms outperform the standard 4 point linear homography solution in terms of accuracy of focal length estimation and image based projection errors.

Original language	English
Title of host publication	2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07
DOIs	https://doi.org/10.1109/CVPR.2007.383082
Publication status	Published - 2007
Event	2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07 - Minneapolis, MN, United States Duration: 17 Jun 2007 → 22 Jun 2007

Publication series

Name	Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN (Print)	1063-6919

Conference

Conference	2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07
Country/Territory	United States
City	Minneapolis, MN
Period	17/06/07 → 22/06/07

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10.1109/CVPR.2007.383082

Cite this

@inproceedings{b43118a1204343d7a5cb01db7a534af0,

title = "Minimal solutions for panoramic stitching",

abstract = "This paper presents minimal solutions for the geometric parameters of a camera rotating about its optical centre. In particular we present new 2 and 3 point solutions for the homography induced by a rotation with 1 and 2 unknown focal length parameters. Using tests on real data, we show that these algorithms outperform the standard 4 point linear homography solution in terms of accuracy of focal length estimation and image based projection errors.",

author = "Matthew Brown and Hartley, {Richard I.} and David Nist{\'e}r",

year = "2007",

doi = "10.1109/CVPR.2007.383082",

language = "English",

isbn = "1424411807",

series = "Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition",

booktitle = "2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07",

note = "2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07 ; Conference date: 17-06-2007 Through 22-06-2007",

}

Brown, M, Hartley, RI & Nistér, D 2007, Minimal solutions for panoramic stitching. in 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07., 4270107, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07, Minneapolis, MN, United States, 17/06/07. https://doi.org/10.1109/CVPR.2007.383082

Minimal solutions for panoramic stitching. / Brown, Matthew; Hartley, Richard I.; Nistér, David.
2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07. 2007. 4270107 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › peer-review

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AU - Hartley, Richard I.

AU - Nistér, David

PY - 2007

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N2 - This paper presents minimal solutions for the geometric parameters of a camera rotating about its optical centre. In particular we present new 2 and 3 point solutions for the homography induced by a rotation with 1 and 2 unknown focal length parameters. Using tests on real data, we show that these algorithms outperform the standard 4 point linear homography solution in terms of accuracy of focal length estimation and image based projection errors.

AB - This paper presents minimal solutions for the geometric parameters of a camera rotating about its optical centre. In particular we present new 2 and 3 point solutions for the homography induced by a rotation with 1 and 2 unknown focal length parameters. Using tests on real data, we show that these algorithms outperform the standard 4 point linear homography solution in terms of accuracy of focal length estimation and image based projection errors.

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M3 - Conference Paper

SN - 1424411807

SN - 9781424411801

T3 - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

BT - 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07

T2 - 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07

Y2 - 17 June 2007 through 22 June 2007

ER -

Minimal solutions for panoramic stitching

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