Depth Map Repairing for Building Reconstruction

C. Andújar, O. Argudo, I. Besora, P. Brunet, A. Chica, Marc Comino
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Abstract

properties surface images from we present a simple method for detecting, classifying and filling non-valid data regions in depth maps produced by dense stereo algorithms. Triangles meshes reconstructed from our repaired depth maps exhibit much higher quality than those produced by state-of-the-art reconstruction algorithms like Screened Poisson-based techniques.
建筑重建的深度图修复
本文提出了一种在密集立体算法生成的深度图中检测、分类和填充非有效数据区域的简单方法。从我们修复的深度图中重建的三角形网格显示出比最先进的重建算法(如基于筛选泊松的技术)更高的质量。
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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