Rotation averaging with application to camera-rig calibration

Yuchao Dai; Jochen Trumpf; Hongdong Li; Nick Barnes; Richard Hartley

doi:10.1007/978-3-642-12304-7_32

Rotation averaging with application to camera-rig calibration

Yuchao Dai, Jochen Trumpf, Hongdong Li, Nick Barnes, Richard Hartley

School of Electronics and Information

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

33 Scopus citations

Abstract

We present a method for calibrating the rotation between two cameras in a camera rig in the case of non-overlapping fields of view and in a globally consistent manner. First, rotation averaging strategies are discussed and an L₁-optimal rotation averaging algorithm is presented which is more robust than the L₂-optimal mean and the direct least squares mean. Second, we alternate between rotation averaging across several views and conjugate rotation averaging to achieve a global solution. Various experiments both on synthetic data and a real camera rig are conducted to evaluate the performance of the proposed algorithm. Experimental results suggest that the proposed algorithm realizes global consistency and a high precision estimate.

Original language	English
Title of host publication	Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers
Pages	335-346
Number of pages	12
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-12304-7_32
State	Published - 2010
Event	9th Asian Conference on Computer Vision, ACCV 2009 - Xi'an, China Duration: 23 Sep 2009 → 27 Sep 2009

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	5995 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	9th Asian Conference on Computer Vision, ACCV 2009
Country/Territory	China
City	Xi'an
Period	23/09/09 → 27/09/09

Access to Document

10.1007/978-3-642-12304-7_32

Cite this

Dai, Y., Trumpf, J., Li, H., Barnes, N., & Hartley, R. (2010). Rotation averaging with application to camera-rig calibration. In Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers (PART 2 ed., pp. 335-346). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5995 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-12304-7_32

Dai, Yuchao ; Trumpf, Jochen ; Li, Hongdong et al. / Rotation averaging with application to camera-rig calibration. Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers. PART 2. ed. 2010. pp. 335-346 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

@inproceedings{fcf34ec892ee41e3887fe61da135b291,

title = "Rotation averaging with application to camera-rig calibration",

abstract = "We present a method for calibrating the rotation between two cameras in a camera rig in the case of non-overlapping fields of view and in a globally consistent manner. First, rotation averaging strategies are discussed and an L1-optimal rotation averaging algorithm is presented which is more robust than the L2-optimal mean and the direct least squares mean. Second, we alternate between rotation averaging across several views and conjugate rotation averaging to achieve a global solution. Various experiments both on synthetic data and a real camera rig are conducted to evaluate the performance of the proposed algorithm. Experimental results suggest that the proposed algorithm realizes global consistency and a high precision estimate.",

author = "Yuchao Dai and Jochen Trumpf and Hongdong Li and Nick Barnes and Richard Hartley",

year = "2010",

doi = "10.1007/978-3-642-12304-7_32",

language = "英语",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

number = "PART 2",

pages = "335--346",

booktitle = "Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers",

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note = "9th Asian Conference on Computer Vision, ACCV 2009 ; Conference date: 23-09-2009 Through 27-09-2009",

}

Dai, Y, Trumpf, J, Li, H, Barnes, N & Hartley, R 2010, Rotation averaging with application to camera-rig calibration. in Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 5995 LNCS, pp. 335-346, 9th Asian Conference on Computer Vision, ACCV 2009, Xi'an, China, 23/09/09. https://doi.org/10.1007/978-3-642-12304-7_32

Rotation averaging with application to camera-rig calibration. / Dai, Yuchao; Trumpf, Jochen; Li, Hongdong et al.
Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers. PART 2. ed. 2010. p. 335-346 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5995 LNCS, No. PART 2).

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

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N2 - We present a method for calibrating the rotation between two cameras in a camera rig in the case of non-overlapping fields of view and in a globally consistent manner. First, rotation averaging strategies are discussed and an L1-optimal rotation averaging algorithm is presented which is more robust than the L2-optimal mean and the direct least squares mean. Second, we alternate between rotation averaging across several views and conjugate rotation averaging to achieve a global solution. Various experiments both on synthetic data and a real camera rig are conducted to evaluate the performance of the proposed algorithm. Experimental results suggest that the proposed algorithm realizes global consistency and a high precision estimate.

AB - We present a method for calibrating the rotation between two cameras in a camera rig in the case of non-overlapping fields of view and in a globally consistent manner. First, rotation averaging strategies are discussed and an L1-optimal rotation averaging algorithm is presented which is more robust than the L2-optimal mean and the direct least squares mean. Second, we alternate between rotation averaging across several views and conjugate rotation averaging to achieve a global solution. Various experiments both on synthetic data and a real camera rig are conducted to evaluate the performance of the proposed algorithm. Experimental results suggest that the proposed algorithm realizes global consistency and a high precision estimate.

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Dai Y, Trumpf J, Li H, Barnes N, Hartley R. Rotation averaging with application to camera-rig calibration. In Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers. PART 2 ed. 2010. p. 335-346. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-12304-7_32

Rotation averaging with application to camera-rig calibration

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