Cheng, S. and Stankovic, Vladimir M. and Stankovic, L. (2009) Improved SIFT-based image registration using belief propagation. In: IEEE International Conference on Acoustics, Speech and Signal Processing, 2009. IEEE, pp. 2909-2912. ISBN 978-1-4244-2353-8
Full text not available in this repository. (Request a copy from the Strathclyde author)Abstract
Scale Invariant Feature Transform (SIFT) is a very powerful technique for image registration. While SIFT descriptors accurately extract invariant image characteristics around keypoints, the commonly used matching approach for registration is overly simplified, because it completely ignores the geometric information among descriptors. In this paper, we formulate keypoint matching as a global optimization problem and provide a suboptimum solution using belief propagation. Experimental results show significant improvement over previous approaches.
| Item type: | Book Section |
|---|---|
| ID code: | 12869 |
| Keywords: | belief networks, image matching, image registration, optimisation, transforms, belief propagation, descriptors, image registration, invariant image characteristics, scale invariant feature transform, Electrical engineering. Electronics Nuclear engineering |
| Subjects: | Technology > Electrical engineering. Electronics Nuclear engineering |
| Department: | Faculty of Engineering > Electronic and Electrical Engineering |
| Related URLs: | |
| Depositing user: | Strathprints Administrator |
| Date Deposited: | 21 Sep 2010 16:56 |
| Last modified: | 12 Mar 2012 10:55 |
| URI: | http://strathprints.strath.ac.uk/id/eprint/12869 |
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