A linear approach to motion estimation using generalized camera models

Hongdong Li; Richard Hartley; Jae Hak Kim

doi:10.1109/CVPR.2008.4587545

A linear approach to motion estimation using generalized camera models

Hongdong Li^*, Richard Hartley, Jae Hak Kim

^*Corresponding author for this work

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

106 Citations (Scopus)

Abstract

A well-known theoretical result for motion estimation using the generalized camera model is that 17 corresponding image rays can be used to solve linearly for the motion of a generalized camera. However, this paper shows that for many common configurations of the generalized camera models (e.g., multi-camera rig, catadioptric camera etc.), such a simple 17-point algorithm does not exist, due to some previously overlooked ambiguities. We further discover that, despite the above ambiguities, we are still able to solve the motion estimation problem effectively by a new algorithm proposed in this paper. Our algorithm is essentially linear, easy to implement, and the computational efficiency is very high. Experiments on both real and simulated data show that the new algorithm achieves reasonably high accuracy as well.

Original language	English
Title of host publication	26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
DOIs	https://doi.org/10.1109/CVPR.2008.4587545
Publication status	Published - 2008
Event	26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR - Anchorage, AK, United States Duration: 23 Jun 2008 → 28 Jun 2008

Publication series

Name	26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR

Conference

Conference	26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
Country/Territory	United States
City	Anchorage, AK
Period	23/06/08 → 28/06/08

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10.1109/CVPR.2008.4587545

Cite this

@inproceedings{7352faf8a1db474db90036f9c49f10e6,

title = "A linear approach to motion estimation using generalized camera models",

abstract = "A well-known theoretical result for motion estimation using the generalized camera model is that 17 corresponding image rays can be used to solve linearly for the motion of a generalized camera. However, this paper shows that for many common configurations of the generalized camera models (e.g., multi-camera rig, catadioptric camera etc.), such a simple 17-point algorithm does not exist, due to some previously overlooked ambiguities. We further discover that, despite the above ambiguities, we are still able to solve the motion estimation problem effectively by a new algorithm proposed in this paper. Our algorithm is essentially linear, easy to implement, and the computational efficiency is very high. Experiments on both real and simulated data show that the new algorithm achieves reasonably high accuracy as well.",

author = "Hongdong Li and Richard Hartley and Kim, {Jae Hak}",

year = "2008",

doi = "10.1109/CVPR.2008.4587545",

language = "English",

isbn = "9781424422432",

series = "26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR",

booktitle = "26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR",

note = "26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR ; Conference date: 23-06-2008 Through 28-06-2008",

}

Li, H, Hartley, R & Kim, JH 2008, A linear approach to motion estimation using generalized camera models. in 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR., 4587545, 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR, Anchorage, AK, United States, 23/06/08. https://doi.org/10.1109/CVPR.2008.4587545

A linear approach to motion estimation using generalized camera models. / Li, Hongdong; Hartley, Richard; Kim, Jae Hak.
26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR. 2008. 4587545 (26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR).

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

TY - GEN

T1 - A linear approach to motion estimation using generalized camera models

AU - Li, Hongdong

AU - Hartley, Richard

AU - Kim, Jae Hak

PY - 2008

Y1 - 2008

N2 - A well-known theoretical result for motion estimation using the generalized camera model is that 17 corresponding image rays can be used to solve linearly for the motion of a generalized camera. However, this paper shows that for many common configurations of the generalized camera models (e.g., multi-camera rig, catadioptric camera etc.), such a simple 17-point algorithm does not exist, due to some previously overlooked ambiguities. We further discover that, despite the above ambiguities, we are still able to solve the motion estimation problem effectively by a new algorithm proposed in this paper. Our algorithm is essentially linear, easy to implement, and the computational efficiency is very high. Experiments on both real and simulated data show that the new algorithm achieves reasonably high accuracy as well.

AB - A well-known theoretical result for motion estimation using the generalized camera model is that 17 corresponding image rays can be used to solve linearly for the motion of a generalized camera. However, this paper shows that for many common configurations of the generalized camera models (e.g., multi-camera rig, catadioptric camera etc.), such a simple 17-point algorithm does not exist, due to some previously overlooked ambiguities. We further discover that, despite the above ambiguities, we are still able to solve the motion estimation problem effectively by a new algorithm proposed in this paper. Our algorithm is essentially linear, easy to implement, and the computational efficiency is very high. Experiments on both real and simulated data show that the new algorithm achieves reasonably high accuracy as well.

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U2 - 10.1109/CVPR.2008.4587545

DO - 10.1109/CVPR.2008.4587545

M3 - Conference contribution

SN - 9781424422432

T3 - 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR

BT - 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR

T2 - 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR

Y2 - 23 June 2008 through 28 June 2008

ER -

A linear approach to motion estimation using generalized camera models

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