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Piecewise Planar Scene Reconstruction and Optimization for Multi-view Stereo

机译:分段平面场景重建和多视图立体声的优化

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This paper presents a multi-view stereo algorithm for piece-wise planar scene reconstruction and optimization. Our segmentation-based reconstruction algorithm is iterative to minimize our defined energy function, consisting of reconstruction, refinement and optimization steps. The first step is a plane initialization to allow each segment to have a set of initial plane candidates. Then a plane refinement based on non-linear optimization improves the accuracy of the segment planes. Finally a plane optimization with a segment-adjacency graph leads to optimal segment planes, each of which is chosen among possible plane candidates by evaluating its relationship with adjacent planes in 3D. This algorithm yields better accuracy and performance, compared to the previous algorithms described in this paper. The results show our method is suitable for outdoor or aerial urban scene reconstruction, especially in wide baselines and images with textureless regions.
机译:本文介绍了一种多视图立体声算法,用于转换平面场景重建和优化。我们基于分段的重建算法迭代可最大限度地减少我们定义的能量函数,包括重建,改进和优化步骤。第一步是允许每个段具有一组初始平面候选的平面初始化。然后基于非线性优化的平面细化提高了段平面的精度。最后,具有分段邻接图的平面优化导致最佳的段平面,每个平面通过评估其与3D中的相邻平面的关系来选择在可能的平面候选中。与本文中描述的先前算法相比,该算法产生更好的准确性和性能。结果表明我们的方法适用于户外或空中城市场景重建,特别是在宽的基线和图像中,具有Textulless区域。

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