GrabCut: Interactive Foreground Extraction Using Iterated Graph Cuts
Microsoft Research (United Kingdom)
Abstract
The problem of efficient, interactive foreground/background segmentation in still images is of great practical importance in image editing. Classical image segmentation tools use either texture (colour) information, e.g. Magic Wand, or edge (contrast) information, e.g. Intelligent Scissors. Recently, an approach based on optimization by graph-cut has been developed which successfully combines both types of information. In this paper we extend the graph-cut approach in three respects. First, we have developed a more powerful, iterative version of the optimisation. Secondly, the power of the iterative algorithm is used to simplify substantially the user interaction needed for a given quality of result. Thirdly,…
Citation impact
- FWCI
- 20.56
- Percentile
- 100%
- References
- 10
Authors
3Topics & keywords
- Computer science
- Segmentation
- Artificial intelligence
- Iterated function
- Cut
- Graph
- Image segmentation
- Computer vision