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.
翻译:3D点云的网目重建是计算机图形、计算机视觉和多媒体分析领域的一个重要主题。 在本文中,我们提出了一个基于 voxel 结构的网目重建框架。 它提供了提高本地区域探测准确性的内在测量标准。 根据所探测到的本地区域, 可以获得一个初始重建的网目。 在我们框架内的网目优化后, 初始重建后的网目将优化为具有外部和内部边缘等重要几何特征的异形网目。 实验结果显示, 我们的框架在网目质量、 几何特征保持和处理速度方面比同行框架有巨大的优势 。