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Sparse stereo by edge-based search using dynamic programming

机译:使用动态编程通过基于边缘的搜索实现稀疏立体声

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In this paper, a novel edge-based stereo matching technique is presented. Depth discontinuities are specifically accounted for in the choice of support regions. We employ dynamic programming along edge-segments to efficiently enforce inter-scanline consistency. Although not performing a global optimization over the whole image we show that our approach performs successfully on the Middlebury benchmark datasets
机译:本文提出了一种新颖的基于边缘的立体声匹配技术。在选择支撑区域时特别考虑了深度不连续性。我们沿边缘段采用动态编程,以有效地增强扫描线间的一致性。尽管未对整个图像执行全局优化,但我们证明了我们的方法在Middlebury基准数据集上的执行成功

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