Improved SIFT-based image registration using belief propagation

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 (http://dx.doi.org/10.1109/ICASSP.2009.4960232)

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.

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• Item metadata

  Item type:	Book Section
  ID code:	12869
  Dates:	Date Event 30 April 2009 Published
  Subjects:	Technology > Electrical engineering. Electronics Nuclear engineering
  Department:	Faculty of Engineering > Electronic and Electrical Engineering
  Depositing user:	Strathprints Administrator
  Date deposited:	21 Sep 2010 15:56
  Last modified:	08 Apr 2024 12:34
  URI:	https://strathprints.strath.ac.uk/id/eprint/12869