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A spectral technique for correspondence problems using pairwise constraints
Open accessAbstract
We present an efficient spectral method for finding consistent correspondences between two sets of features. We build the adjacency matrix M of a graph whose nodes represent the potential correspondences and the weights on the links represent pairwise agreements between potential correspondences. Correct assignments are likely to establish links among each other and thus form a strongly connected cluster. Incorrect correspondences establish links with the other correspondences only accidentally, so they are unlikely to belong to strongly connected clusters. We recover the correct assignments based on how strongly they belong to the main cluster of M, by using the principal eigenvector of M and imposing the mapping constraints required by the overall correspondence mapping (one-to-one or one-to-many). The experimental evaluation shows that our method is robust to outliers, accurate in terms of matching rate, while being much faster than existing methods
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Cites
Object recognition from local scale-invariant features
Lowe, D. G. (1999) · Proceedings of the Seventh IEEE International Conference on Computer Vision · doi:10.1109/iccv.1999.790410 · Cited by 16,472
Spline Models for Observational Data
Wahba, G. (1990) · doi:10.1137/1.9781611970128 · Cited by 4,184
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“Leordeanu and Hebert [287] proposed a spectral technique to solve the matching problem.”
BackgroundMethodRegistration of 3D Point Clouds and Meshes: A Survey from Rigid to Nonrigid
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Ma, J., Zhao, J., Jiang, J., Zhou, H., & Guo, X. (2019) · International Journal of Computer Vision · doi:10.1007/s11263-018-1117-z · Cited by 601
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Metadata
- Authors
- Leordeanu, M., & Hebert, M.
- Venue
- Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1
- Publisher
- IEEE
- Published
- 2005
- Pages
- 1482-1489 Vol. 2
- OpenAlex
- W2166820607
- Cited by
- 1,222
- References
- 2
- FWCI
- 13.29
- Type
- conference paper
- Language
- en
- Open access
- green
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- Leordeanu, M., & Hebert, M. (2005). A spectral technique for correspondence problems using pairwise constraints. Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1. https://doi.org/10.1109/iccv.2005.20
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