DocumentCode
2462143
Title
The 3D-3D Registration Problem Revisited
Author
Li, Hongdong ; Hartley, Richard
Author_Institution
Australian Nat. Univ., Canberra
fYear
2007
fDate
14-21 Oct. 2007
Firstpage
1
Lastpage
8
Abstract
We describe a new framework for globally solving the 3D-3D registration problem with unknown point correspondences. This problem is significant as it is frequently encountered in many applications. Existing methods are not fully satisfactory, mainly due to the risk of local minima. Our framework is grounded on the Lipschitz global optimization theory. It achieves a guaranteed global optimality without any initialization. By exploiting the special structure of the problem itself and of the 3D rotation space SO(3), we propose a box-and-ball algorithm, which solves the problem efficiently. The main idea of the work can be applied to many other problems as well.
Keywords
computer vision; image registration; octrees; optimisation; 3D rotation space; 3D-3D registration problem; Lipschitz global optimization theory; computer vision; local minima risk; octree box-and-ball algorithm; Application software; Australia; Biomedical imaging; Computer vision; Graphics; Iterative algorithms; Iterative closest point algorithm; Medical robotics; Object recognition; Principal component analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on
Conference_Location
Rio de Janeiro
ISSN
1550-5499
Print_ISBN
978-1-4244-1630-1
Electronic_ISBN
1550-5499
Type
conf
DOI
10.1109/ICCV.2007.4409077
Filename
4409077
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