Fast interactive segmentation in stereo images based on multi-scale graph

It is hard for current interactive stereo image segmentation methods to deal with large scale images with fast feedback after each interaction. In this paper, we present an interactive stereo image segmentation method. Different from current methods, our method introduces a multi-scale graph structure for fast graph cut optimization. Besides, we use GPU parallel computing to handle single instruction multiple data tasks involved in the segmentation. Compared with state-of-the-art methods, our approach significantly accelerates segmentation speed. In the meanwhile, our method obtains segmentation accuracy comparable with state-of-the-art methods.