Graph Cut with Ordering Constraints on Labels and Its Applications
Abstract
In the last decade, graph-cut optimization has been popular for a variety of pixel labeling problems. Typically graph-cut methods are used to incorporate a smoothness prior on a labeling. Recently several methods incorporated ordering constraints on labels for the application of object segmentation. An example of an ordering constraint is prohibiting a pixel with a ldquocar wheelrdquo label to be above a pixel with a ldquocar roofrdquo label. We observe that the commonly used graph-cut based alpha-expansion is more likely to get stuck in a local minimum when ordering constraints are used. For certain models with ordering constraints, we develop new graph-cut moves which we call order-preserving moves. Order-preserving moves act on all labels, unlike alpha-expansion. Although the global minimum is still not guaranteed, optimization with order-preserving moves performs significantly better than alpha-expansion. We evaluate order-preserving moves for the geometric class scene labeling (introduced by Hoiem et al.) where the goal is to assign each pixel a label such as ldquoskyrdquo, ldquogrounrdquo, etc., so ordering constraints arise naturally. In addition, we use order-preserving moves for certain simple shape priors in graphcut segmentation, which is a novel contribution in itself.
Cite
Text
Liu et al. "Graph Cut with Ordering Constraints on Labels and Its Applications." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2008. doi:10.1109/CVPR.2008.4587470Markdown
[Liu et al. "Graph Cut with Ordering Constraints on Labels and Its Applications." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2008.](https://mlanthology.org/cvpr/2008/liu2008cvpr-graph/) doi:10.1109/CVPR.2008.4587470BibTeX
@inproceedings{liu2008cvpr-graph,
title = {{Graph Cut with Ordering Constraints on Labels and Its Applications}},
author = {Liu, Xiaoqing and Veksler, Olga and Samarabandu, Jagath},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2008},
doi = {10.1109/CVPR.2008.4587470},
url = {https://mlanthology.org/cvpr/2008/liu2008cvpr-graph/}
}