Abstract
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.
Keywords
- Computer Vision: CV: Segmentation
- Computer Vision: CV: Machine learning for vision
