MILCut: A Sweeping Line Multiple Instance Learning Paradigm for Interactive Image Segmentation

Jiajun Wu, Yibiao Zhao, Jun-Yan Zhu, Siwei Luo, Zhuowen Tu

CVPR 2014

doi:10.1109/CVPR.2014.40 /cvpr/2014/wu2014cvpr-milcut/

Abstract

Interactive segmentation, in which a user provides a bounding box to an object of interest for image segmentation, has been applied to a variety of applications in image editing, crowdsourcing, computer vision, and medical imaging. The challenge of this semi-automatic image segmentation task lies in dealing with the uncertainty of the foreground object within a bounding box. Here, we formulate the interactive segmentation problem as a multiple instance learning (MIL) task by generating positive bags from pixels of sweeping lines within a bounding box. We name this approach MILCut. We provide a justification to our formulation and develop an algorithm with significant performance and efficiency gain over existing state-of-the-art systems. Extensive experiments demonstrate the evident advantage of our approach.

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Cite

Text

Wu et al. "MILCut: A Sweeping Line Multiple Instance Learning Paradigm for Interactive Image Segmentation." Conference on Computer Vision and Pattern Recognition, 2014. doi:10.1109/CVPR.2014.40

Markdown

[Wu et al. "MILCut: A Sweeping Line Multiple Instance Learning Paradigm for Interactive Image Segmentation." Conference on Computer Vision and Pattern Recognition, 2014.](https://mlanthology.org/cvpr/2014/wu2014cvpr-milcut/) doi:10.1109/CVPR.2014.40

BibTeX

@inproceedings{wu2014cvpr-milcut,
  title     = {{MILCut: A Sweeping Line Multiple Instance Learning Paradigm for Interactive Image Segmentation}},
  author    = {Wu, Jiajun and Zhao, Yibiao and Zhu, Jun-Yan and Luo, Siwei and Tu, Zhuowen},
  booktitle = {Conference on Computer Vision and Pattern Recognition},
  year      = {2014},
  doi       = {10.1109/CVPR.2014.40},
  url       = {https://mlanthology.org/cvpr/2014/wu2014cvpr-milcut/}
}