Voxel Structure-based Mesh Reconstruction from a 3D Point Cloud

TL;DR

This paper introduces a voxel structure-based framework for reconstructing meshes from 3D point clouds, enhancing accuracy and geometric feature preservation while improving processing speed.

Contribution

The proposed framework utilizes an intrinsic metric for local region detection and mesh optimization, offering a novel approach to improve mesh quality from point clouds.

Findings

Outperforms peer methods in mesh quality

Preserves important geometric features effectively

Achieves faster processing speeds

Abstract

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.