  This paper adresses the problem of interactive multiclass segmentation. We
propose a fast and efficient new interactive segmentation method called
Superpixel Classification-based Interactive Segmentation (SCIS). From a few
strokes drawn by a human user over an image, this method extracts relevant
semantic objects. To get a fast calculation and an accurate segmentation, SCIS
uses superpixel over-segmentation and support vector machine classification. In
this paper, we demonstrate that SCIS significantly outperfoms competing
algorithms by evaluating its performances on the reference benchmarks of
McGuinness and Santner.
