Contour-based Interactive Segmentation
This addresses the need for more efficient image editing and labeling tools, particularly for selecting small or complex objects, though it is incremental as it builds on existing interactive segmentation approaches.
The paper tackles the problem of reducing user interactions in interactive segmentation by proposing a contour-based method, demonstrating that a single contour achieves the same accuracy as multiple clicks.
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 objects, minor parts of an object, or a group of objects 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.