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

Wei Ma, Xiaohui Qiu, Luwei Yang, Shuo Liu, Lijuan Duan
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Abstract

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.
基于多尺度图的立体图像快速交互式分割
现有的交互式立体图像分割方法难以处理每次交互后反馈快的大规模图像。本文提出了一种交互式立体图像分割方法。与现有方法不同的是,该方法引入了一种多尺度图结构,用于快速图割优化。此外,我们使用GPU并行计算来处理分割中涉及的单指令多数据任务。与最先进的方法相比,我们的方法显著加快了分割速度。同时,该方法的分割精度与现有方法相当。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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