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arXiv · 1510.03199

Interactive multiclass segmentation using superpixel classification

Bérengère Mathieu·Alain Crouzil·Jean-Baptiste Puel
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Abstract

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.

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Bérengère Mathieu, Alain Crouzil, Jean-Baptiste Puel. 2015-10-12. Interactive multiclass segmentation using superpixel classification. https://arxiv.org/abs/1510.03199

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