Abstract
We present an adaptive parametrization scheme for dynamic mesh refinement in the application of parametric image registration. The scheme is based on a refinement measure ensuring that the control points give an efficient representation of the warp fields, in terms of minimizing the registration cost function. In the current work we introduce multivariate B-splines as a novel alternative to the widely used tensor B-splines enabling us to make efficient use of the derived measure.The multivariate B-splines of order n are Cn- 1 smooth and are based on Delaunay configurations of arbitrary 2D or 3D control point sets. Efficient algorithms for finding the configurations are presented, and B-splines are through their flexibility shown to feature several advantages over the tensor B-splines. In spite of efforts to make the tensor product B-splines more flexible, the knots are still bound to reside on a regular grid. In contrast, by efficient non- constrained placement of the knots, the multivariate B- splines are shown to give a good representation of inho- mogeneous objects in natural settings. The wide applicability of the method is illustrated through its application on medical data and for optical flow estimation.
Original language | English |
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Title of host publication | Proceedings of CVPR |
Publisher | IEEE |
Publication date | 2008 |
Pages | 1-8 |
ISBN (Print) | 978-1-4244-2242-5 |
DOIs | |
Publication status | Published - 2008 |
Event | 2008 IEEE Conference on Computer Vision and Pattern Recognition - Anchorage, United States Duration: 23 Jun 2008 → 28 Jun 2008 http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=4558014 |
Conference
Conference | 2008 IEEE Conference on Computer Vision and Pattern Recognition |
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Country/Territory | United States |
City | Anchorage |
Period | 23/06/2008 → 28/06/2008 |
Internet address |