Please use this identifier to cite or link to this item:
|Scopus||Web of Science®||Altmetric|
|Title:||Motion estimation for multi-camera systems using global optimization|
|Citation:||Proceedings / CVPR, IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2008, pp.1-8|
|Conference Name:||IEEE Conference on Computer Vision and Pattern Recognition (23 Jun 2013 - 28 Jun 2013 : Anchorage, AK)|
|Jae-Hak Kim, Hongdong Li, Richard Hartley|
|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 Linfin 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.|
|Appears in Collections:||Aurora harvest 7|
Computer Science publications
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.