ML Anthology

Delineating Trees in Noisy 2D Images and 3D Image-Stacks

Germán González, Engin Türetken, François Fleuret, Pascal Fua
CVPR 2010 pp. 2799-2806
doi:10.1109/CVPR.2010.5540010 /cvpr/2010/gonzalez2010cvpr-delineating/

Abstract

We present a novel approach to fully automated delineation of tree structures in noisy 2D images and 3D image stacks. Unlike earlier methods that rely mostly on local evidence, our method builds a set of candidate trees over many different subsets of points likely to belong to the final one and then chooses the best one according to a global objective function. Since we are not systematically trying to span all nodes, our algorithm is able to eliminate noise while retaining the right tree structure.

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Cite

Text

González et al. "Delineating Trees in Noisy 2D Images and 3D Image-Stacks." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2010. doi:10.1109/CVPR.2010.5540010

Markdown

[González et al. "Delineating Trees in Noisy 2D Images and 3D Image-Stacks." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2010.](https://mlanthology.org/cvpr/2010/gonzalez2010cvpr-delineating/) doi:10.1109/CVPR.2010.5540010

BibTeX

@inproceedings{gonzalez2010cvpr-delineating,
  title     = {{Delineating Trees in Noisy 2D Images and 3D Image-Stacks}},
  author    = {González, Germán and Türetken, Engin and Fleuret, François and Fua, Pascal},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2010},
  pages     = {2799-2806},
  doi       = {10.1109/CVPR.2010.5540010},
  url       = {https://mlanthology.org/cvpr/2010/gonzalez2010cvpr-delineating/}
}