Climbing: A Unified Approach for Global Constraints on Hierarchical Segmentation
Abstract
The paper deals with global constraints for hierarchical segmentations. The proposed framework associates, with an input image, a hierarchy of segmentations and an energy, and the subsequent optimization problem. It is the first paper that compiles the different global constraints and unifies them as Climbing energies . The transition from global optimization to local optimization is attained by the h -increasingness property, which allows to compare parent and child partition energies in hierarchies. The laws of composition of such energies are established and examples are given over the Berkeley Dataset for colour and texture segmentation.
Cite
Text
Kiran et al. "Climbing: A Unified Approach for Global Constraints on Hierarchical Segmentation." European Conference on Computer Vision, 2012. doi:10.1007/978-3-642-33885-4_33Markdown
[Kiran et al. "Climbing: A Unified Approach for Global Constraints on Hierarchical Segmentation." European Conference on Computer Vision, 2012.](https://mlanthology.org/eccv/2012/kiran2012eccv-climbing/) doi:10.1007/978-3-642-33885-4_33BibTeX
@inproceedings{kiran2012eccv-climbing,
title = {{Climbing: A Unified Approach for Global Constraints on Hierarchical Segmentation}},
author = {Kiran, Bangalore Ravi and Serra, Jean and Cousty, Jean},
booktitle = {European Conference on Computer Vision},
year = {2012},
pages = {324-334},
doi = {10.1007/978-3-642-33885-4_33},
url = {https://mlanthology.org/eccv/2012/kiran2012eccv-climbing/}
}