Motion estimation for multi-camera systems using global optimization

Jae Hak Kim; Hongdong Li; Richard Hartley

doi:10.1109/CVPR.2008.4587680

Motion estimation for multi-camera systems using global optimization

Jae Hak Kim^*, Hongdong Li, Richard Hartley

^*Corresponding author for this work

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

17 Citations (Scopus)

Abstract

We present a motion estimation algorithm for multi-camera systems consisting of more than one calibrated camera securely attached on a moving object. So, they move all together, but do not require to have overlapping views across the cameras. The geometrically optimal solution of the motion for the multi-camera systems under L_∞ norm is provided in this paper using a global optimization technique which has been introduced recently in the computer vision research field. Taking advantage of an optimal estimate of the essential matrix through searching rotation space, we provide the optimal solution for translation by using linear programming and Branch & Bound algorithm. Synthetic and real data experiments are conducted, and they show more robust and improved performance than the previous methods.

Original language	English
Title of host publication	26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
DOIs	https://doi.org/10.1109/CVPR.2008.4587680
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.2008.4587680

Cite this

@inproceedings{b20328ea1a834f72a38f66ea0498acd8,

title = "Motion estimation for multi-camera systems using global optimization",

abstract = "We present a motion estimation algorithm for multi-camera systems consisting of more than one calibrated camera securely attached on a moving object. So, they move all together, but do not require to have overlapping views across the cameras. The geometrically optimal solution of the motion for the multi-camera systems under L∞ norm is provided in this paper using a global optimization technique which has been introduced recently in the computer vision research field. Taking advantage of an optimal estimate of the essential matrix through searching rotation space, we provide the optimal solution for translation by using linear programming and Branch & Bound algorithm. Synthetic and real data experiments are conducted, and they show more robust and improved performance than the previous methods.",

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

year = "2008",

doi = "10.1109/CVPR.2008.4587680",

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",

}

Kim, JH, Li, H & Hartley, R 2008, Motion estimation for multi-camera systems using global optimization. in 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR., 4587680, 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.2008.4587680

Motion estimation for multi-camera systems using global optimization. / Kim, Jae Hak; Li, Hongdong; Hartley, Richard.
26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR. 2008. 4587680 (26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR).

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

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T1 - Motion estimation for multi-camera systems using global optimization

AU - Kim, Jae Hak

AU - Li, Hongdong

AU - Hartley, Richard

PY - 2008

Y1 - 2008

N2 - We present a motion estimation algorithm for multi-camera systems consisting of more than one calibrated camera securely attached on a moving object. So, they move all together, but do not require to have overlapping views across the cameras. The geometrically optimal solution of the motion for the multi-camera systems under L∞ norm is provided in this paper using a global optimization technique which has been introduced recently in the computer vision research field. Taking advantage of an optimal estimate of the essential matrix through searching rotation space, we provide the optimal solution for translation by using linear programming and Branch & Bound algorithm. Synthetic and real data experiments are conducted, and they show more robust and improved performance than the previous methods.

AB - We present a motion estimation algorithm for multi-camera systems consisting of more than one calibrated camera securely attached on a moving object. So, they move all together, but do not require to have overlapping views across the cameras. The geometrically optimal solution of the motion for the multi-camera systems under L∞ norm is provided in this paper using a global optimization technique which has been introduced recently in the computer vision research field. Taking advantage of an optimal estimate of the essential matrix through searching rotation space, we provide the optimal solution for translation by using linear programming and Branch & Bound algorithm. Synthetic and real data experiments are conducted, and they show more robust and improved performance than the previous methods.

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U2 - 10.1109/CVPR.2008.4587680

DO - 10.1109/CVPR.2008.4587680

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 -

Motion estimation for multi-camera systems using global optimization

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