Contour-based Interactive Segmentation

Recent advances in interactive segmentation (IS) allow speeding up and simplifying image editing and labeling greatly. The majority of modern IS approaches accept user input in the form of clicks. However, using clicks may require too many user interactions, especially when selecting small ob- jects, minor parts of an object, or a group of ob- jects of the same type. In this paper, we consider such a natural form of user interaction as a loose contour, and introduce a contour-based IS method. We evaluate the proposed method on the standard segmentation benchmarks, our novel UserContours dataset, and its subset UserContours-G containing difficult segmentation cases. Through experiments, we demonstrate that a single contour provides the same accuracy as multiple clicks, thus reducing the required amount of user interactions.

Authors

• Polina Popenova
• Danil Galeev
• Anna Vorontsova NEURA Robotics GmbH, Metzingen, Germany
• Anton Konushin Artificial Intelligence Research Institute, Moscow, Russia

Keywords

• Computer Vision: CV: Machine learning for vision
• Computer Vision: CV: Segmentation