Minimal Solutions for Panoramic Stitching

Matthew Brown; Richard I Hartley; David Nister

doi:10.1109/CVPR.2007.383082

Minimal Solutions for Panoramic Stitching

Matthew Brown, Richard I Hartley, David Nister

Department of Computer Science

Research output: Contribution to conference › Paper › peer-review

62 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
DOIs	https://doi.org/10.1109/CVPR.2007.383082
Publication status	Published - Jun 2007
Event	CVPR '07: IEEE Conference on Computer Vision and Pattern Recognition, 2007 - Minneapolis Duration: 17 Jun 2007 → 22 Jun 2007

Conference

Conference	CVPR '07: IEEE Conference on Computer Vision and Pattern Recognition, 2007
City	Minneapolis
Period	17/06/07 → 22/06/07

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10.1109/CVPR.2007.383082

Cite this

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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 Nister",

year = "2007",

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AU - Hartley, Richard I

AU - Nister, David

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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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U2 - 10.1109/CVPR.2007.383082

DO - 10.1109/CVPR.2007.383082

M3 - Paper

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

Y2 - 17 June 2007 through 22 June 2007

ER -

Minimal Solutions for Panoramic Stitching

Abstract

Conference

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