Aligning Images in the Wild

Wen-Yan Lin, Linlin Liu, Yasuyuki Matsushita, Kok-Lim Low, Siying Liu

CVPR 2012 pp. 1-8

doi:10.1109/CVPR.2012.6247651 /cvpr/2012/lin2012cvpr-aligning/

Abstract

Aligning image pairs with significant appearance change is a long standing computer vision challenge. Much of this problem stems from the local patch descriptors' instability to appearance variation. In this paper we suggest this instability is due less to descriptor corruption and more the difficulty in utilizing local information to canonically define the orientation (scale and rotation) at which a patch's descriptor should be computed. We address this issue by jointly estimating correspondence and relative patch orientation, within a hierarchical algorithm that utilizes a smoothly varying parameterization of geometric transformations. By collectively estimating the correspondence and orientation of all the features, we can align and orient features that cannot be stably matched with only local information. At the price of smoothing over motion discontinuities (due to independent motion or parallax), this approach can align image pairs that display significant inter-image appearance variations.

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Cite

Text

Lin et al. "Aligning Images in the Wild." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2012. doi:10.1109/CVPR.2012.6247651

Markdown

[Lin et al. "Aligning Images in the Wild." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2012.](https://mlanthology.org/cvpr/2012/lin2012cvpr-aligning/) doi:10.1109/CVPR.2012.6247651

BibTeX

@inproceedings{lin2012cvpr-aligning,
  title     = {{Aligning Images in the Wild}},
  author    = {Lin, Wen-Yan and Liu, Linlin and Matsushita, Yasuyuki and Low, Kok-Lim and Liu, Siying},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2012},
  pages     = {1-8},
  doi       = {10.1109/CVPR.2012.6247651},
  url       = {https://mlanthology.org/cvpr/2012/lin2012cvpr-aligning/}
}