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Machine Vision and Applications
Published in: Machine Vision and Applications 5/2013

01-07-2013 | Original Paper

Feature matching based on unsupervised manifold alignment

Authors: Weidong Yan, Zheng Tian, Xifa Duan, Lulu Pan

Published in: Machine Vision and Applications | Issue 5/2013

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Abstract

Feature-based methods for image registration frequently encounter the correspondence problem. In this paper, we formulate feature-based image registration as a manifold alignment problem, and present a novel matching method for finding the correspondences among different images containing the same object. Different from the semi-supervised manifold alignment, our methods map the data sets to the underlying common manifold without using correspondence information. An iterative multiplicative updating algorithm is proposed to optimize the objective, and its convergence is guaranteed theoretically. The proposed approach has been tested for matching accuracy, and robustness to outliers. Its performance on synthetic and real images is compared with the state-of-the-art reference algorithms.
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Appendix
Available only for authorised users
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Metadata
Title
Feature matching based on unsupervised manifold alignment
Authors
Weidong Yan
Zheng Tian
Xifa Duan
Lulu Pan
Publication date
01-07-2013
Publisher
Springer-Verlag
Published in
Machine Vision and Applications / Issue 5/2013
Print ISSN: 0932-8092
Electronic ISSN: 1432-1769
DOI
https://doi.org/10.1007/s00138-012-0479-4

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