22 July 2014 Mismatch removal via coherent spatial relations
Jun Chen, Jiayi Ma, Changcai Yang, Jinwen Tian
Author Affiliations +
Abstract
We propose a method for removing mismatches from the given putative point correspondences in image pairs based on “coherent spatial relations.” Under the Bayesian framework, we formulate our approach as a maximum likelihood problem and solve a coherent spatial relation between the putative point correspondences using an expectation–maximization (EM) algorithm. Our approach associates each point correspondence with a latent variable indicating it as being either an inlier or an outlier, and alternatively estimates the inlier set and recovers the coherent spatial relation. It can handle not only the case of image pairs with rigid motions but also the case of image pairs with nonrigid motions. To parameterize the coherent spatial relation, we choose two-view geometry and thin-plate spline as models for rigid and nonrigid cases, respectively. The mismatches could be successfully removed via the coherent spatial relations after the EM algorithm converges. The quantitative results on various experimental data demonstrate that our method outperforms many state-of-the-art methods, it is not affected by low initial correct match percentages, and is robust to most geometric transformations including a large viewing angle, image rotation, and affine transformation.
© 2014 SPIE and IS&T 0091-3286/2014/$25.00 © 2014 SPIE and IS&T
Jun Chen, Jiayi Ma, Changcai Yang, and Jinwen Tian "Mismatch removal via coherent spatial relations," Journal of Electronic Imaging 23(4), 043012 (22 July 2014). https://doi.org/10.1117/1.JEI.23.4.043012
Published: 22 July 2014
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CITATIONS
Cited by 10 scholarly publications.
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KEYWORDS
Expectation maximization algorithms

Motion models

Statistical analysis

3D modeling

Image restoration

Performance modeling

Affine motion model

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