Feature correspondence and deformable object matching via agglomerative correspondence clustering

@article{Cho2009FeatureCA,
  title={Feature correspondence and deformable object matching via agglomerative correspondence clustering},
  author={Minsu Cho and Jungmin Lee and Kyoung Mu Lee},
  journal={2009 IEEE 12th International Conference on Computer Vision},
  year={2009},
  pages={1280-1287}
}
We present an efficient method for feature correspondence and object-based image matching, which exploits both photometric similarity and pairwise geometric consistency from local invariant features. We formulate object-based image matching as an unsupervised multi-class clustering problem on a set of candidate feature matches, and propose a novel pairwise dissimilarity measure and a robust linkage model in the framework of hierarchical agglomerative clustering. The algorithm handles… CONTINUE READING
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