Conference proceeding
Error-Tolerant Scribbles Based Interactive Image Segmentation
2014 IEEE Conference on Computer Vision and Pattern Recognition, pp.392-399
06/2014
DOI: 10.1109/CVPR.2014.57
Abstract
Scribbles in scribble-based interactive segmentation such as graph-cut are usually assumed to be perfectly accurate, i.e., foreground scribble pixels will never be segmented as background in the final segmentation. However, it can be hard to draw perfectly accurate scribbles, especially on fine structures of the image or on mobile touch-screen devices. In this paper, we propose a novel ratio energy function that tolerates errors in the user input while encouraging maximum use of the user input information. More specifically, the ratio energy aims to minimize the graph-cut energy while maximizing the user input respected in the segmentation. The ratio energy function can be exactly optimized using an efficient iterated graph cut algorithm. The robustness of the proposed method is validated on the GrabCut dataset using both synthetic scribbles and manual scribbles. The experimental results show that the proposed algorithm is robust to the errors in the user input and preserves the "anchoring" capability of the user input.
Details
- Title: Subtitle
- Error-Tolerant Scribbles Based Interactive Image Segmentation
- Creators
- Junjie Bai - University of IowaXiaodong Wu - University of Iowa
- Resource Type
- Conference proceeding
- Publication Details
- 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp.392-399
- Publisher
- IEEE
- DOI
- 10.1109/CVPR.2014.57
- ISSN
- 1063-6919
- eISSN
- 1063-6919
- Language
- English
- Date published
- 06/2014
- Academic Unit
- Electrical and Computer Engineering; Radiation Oncology; The Iowa Institute for Biomedical Imaging
- Record Identifier
- 9984197518802771
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