Transductive Object Cutout

Abstract

In this paper, we address the issue of transducing the object cutout model from an example image to novel image instances. We observe that although object and background are very likely to contain similar colors in natural images, it is much less probable that they share similar color configurations. Motivated by this observation, we propose a local color pattern model to characterize the color configuration in a robust way. Additionally, we propose an edge profile model to modulate the contrast of the image, which enhances edges along object boundaries and attenuates edges inside object or background. The local color pattern model and edge model are integrated in a graph-cut framework. Higher accuracy and improved robustness of the proposed method are demonstrated through experimental comparison with state-of-the-art algorithms. ©2008 IEEE.

Cite

Text

Cui et al. "Transductive Object Cutout." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2008. doi:10.1109/CVPR.2008.4587589

Markdown

[Cui et al. "Transductive Object Cutout." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2008.](https://mlanthology.org/cvpr/2008/cui2008cvpr-transductive/) doi:10.1109/CVPR.2008.4587589

BibTeX

@inproceedings{cui2008cvpr-transductive,
  title     = {{Transductive Object Cutout}},
  author    = {Cui, Jingyu and Yang, Qiong and Wen, Fang and Wu, Qiying and Zhang, Changshui and Van Gool, Luc and Tang, Xiaoou},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2008},
  doi       = {10.1109/CVPR.2008.4587589},
  url       = {https://mlanthology.org/cvpr/2008/cui2008cvpr-transductive/}
}