Toward a unified scheme for fast interactive segmentation

This paper presents an efficient and effective interactive segmentation scheme for extracting the region of a foreground object in an image. Our goal is to design an interactive segmentation algorithm that unifies the bounding-box-based, seed-based, and query-based interaction mechanisms for pursuing (i) high efficiency in simple interaction mechanism, (ii) few interaction rounds, and (iii) short response time. The proposed algorithm starts with a user-provided bounding box and obtains candidate background superpixels for inferring the foreground object. Our algorithm tolerates imprecise bounding boxes and provides two kinds of interactions for acquiring correct labels from the user. The user can either input the seed/scribble annotations or label the algorithm-queried regions. Our algorithm selects the most uncertain region as a query, and this query-based interaction mechanism reduces the burden of the user on deciding suitable annotation locations. The average response time per-interaction of our algorithm is merely 0.014 s. Our experiments demonstrate that the algorithm achieves an efficient unified scheme for interactive image segmentation.