Mesh reconstruction from a 3D point cloud is an important topic in the fields of computer graphic, computer vision, and multimedia analysis. In this paper, we propose a voxel structure-based mesh reconstruction framework. It provides the intrinsic metric to improve the accuracy of local region detection. Based on the detected local regions, an initial reconstructed mesh can be obtained. With the mesh optimization in our framework, the initial reconstructed mesh is optimized into an isotropic one with the important geometric features such as external and internal edges. The experimental results indicate that our framework shows great advantages over peer ones in terms of mesh quality, geometric feature keeping, and processing speed.

中文翻译：

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从3D点云基于体素结构的网格重建

从3D点云进行网格重建是计算机图形学，计算机视觉和多媒体分析领域的重要主题。在本文中，我们提出了一种基于体素结构的网格重建框架。它提供了固有的指标来提高局部区域检测的准确性。基于检测到的局部区域，可以获得初始的重构网格。通过我们框架中的网格优化，可以将初始重建的网格优化为各向同性的网格，并具有重要的几何特征，例如外部和内部边缘。实验结果表明，我们的框架在网格质量，几何特征保持和处理速度方面显示出优于同类框架的巨大优势。