Abstract
In this paper, we present a novel algorithm for establishing region correspondences across images by first matching global region configuration and then propagating the matches locally constrained by Delaunay triangulation. We exploit a global configuration constraint, which has not been explicitly used in existing matching algorithms. The proposed algorithm is comprised of two stages: First, stable regions are matched by enforcing global configuration constraint. This yields a set of global matches corresponding to stable regions distributed over the images. In the second stage, these matches are used to guide the matching of the remaining unmatched regions in the intervening spaces. This is done by enforcing local positioning constraint, which starts with the Delaunay triangulation defined by the global matches and performs progressive Delaunay triangulation for local matching. Experiments on both stereo and motion images are presented to show the effectiveness of the proposed algorithm.
Original language | English (US) |
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Pages (from-to) | 637-642 |
Number of pages | 6 |
Journal | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
Volume | 2 |
State | Published - 2000 |
Event | IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2000 - Hilton Head Island, SC, USA Duration: Jun 13 2000 → Jun 15 2000 |
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition