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Stereo superpixel: An iterative framework based on parallax consistency and collaborative optimization
Information Sciences ( IF 8.1 ) Pub Date : 2021-01-18 , DOI: 10.1016/j.ins.2020.12.031
Hua Li , Runmin Cong , Sam Kwong , Chuanbo Chen , Qianqian Xu , Chongyi Li

Stereo superpixel segmentation aims to obtain the superpixel segmentation results of the left and right views more cooperatively and consistently, rather than simply performing independent segmentation directly. Thus, the correspondence between two views should be reasonably modeled and fully considered. In this paper, we propose a left-right interactive optimization framework for stereo superpixel segmentation. Considering the disparity in stereo image pairs, we first divide the images into paired region and non-paired region, and propose a collaborative optimization scheme to coordinately refine the matched superpixels of the left and right views in an interactive manner. This is, to the best of our knowledge, the first attempt to generate stereo superpixels considering the parallax consistency. Quantitative and qualitative experiments demonstrate that the proposed framework achieves superior performance in terms of consistency and accuracy compared with single-image superpixel segmentation.



中文翻译:

立体超像素:基于视差一致性和协同优化的迭代框架

立体超像素分割的目的是更协同一致地获得左视图和右视图的超像素分割结果,而不是直接执行独立的分割。因此,应该合理地建模和充分考虑两个视图之间的对应关系。在本文中,我们提出了一种用于立体声超像素分割的左右互动优化框架。考虑到立体图像对中的差异,我们首先将图像分为成对区域和非成对区域,然后提出一种协作优化方案,以交互方式协调地优化左视图和右视图的匹配超像素。据我们所知,这是考虑视差一致性生成立体超像素的首次尝​​试。

更新日期:2021-01-19
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