Title :
The 3D-3D Registration Problem Revisited
Author :
Li, Hongdong ; Hartley, Richard
Author_Institution :
Australian Nat. Univ., Canberra
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;
Conference_Titel :
Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on
Conference_Location :
Rio de Janeiro
Print_ISBN :
978-1-4244-1630-1
Electronic_ISBN :
1550-5499
DOI :
10.1109/ICCV.2007.4409077