Efficient Squared Curvature

Claudia Nieuwenhuis, Eno Toeppe, Lena Gorelick, Olga Veksler, Yuri Boykov

CVPR 2014

doi:10.1109/CVPR.2014.522 /cvpr/2014/nieuwenhuis2014cvpr-efficient/

Abstract

Curvature has received increasing attention as an important alternative to length based regularization in computer vision. In contrast to length, it preserves elongated structures and fine details. Existing approaches are either inefficient, or have low angular resolution and yield results with strong block artifacts. We derive a new model for computing squared curvature based on integral geometry. The model counts responses of straight line triple cliques. The corresponding energy decomposes into submodular and supermodular pairwise potentials. We show that this energy can be efficiently minimized even for high angular resolutions using the trust region framework. Our results confirm that we obtain accurate and visually pleasing solutions without strong artifacts at reasonable runtimes.

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Cite

Text

Nieuwenhuis et al. "Efficient Squared Curvature." Conference on Computer Vision and Pattern Recognition, 2014. doi:10.1109/CVPR.2014.522

Markdown

[Nieuwenhuis et al. "Efficient Squared Curvature." Conference on Computer Vision and Pattern Recognition, 2014.](https://mlanthology.org/cvpr/2014/nieuwenhuis2014cvpr-efficient/) doi:10.1109/CVPR.2014.522

BibTeX

@inproceedings{nieuwenhuis2014cvpr-efficient,
  title     = {{Efficient Squared Curvature}},
  author    = {Nieuwenhuis, Claudia and Toeppe, Eno and Gorelick, Lena and Veksler, Olga and Boykov, Yuri},
  booktitle = {Conference on Computer Vision and Pattern Recognition},
  year      = {2014},
  doi       = {10.1109/CVPR.2014.522},
  url       = {https://mlanthology.org/cvpr/2014/nieuwenhuis2014cvpr-efficient/}
}