Approximate Intrinsic Voxel Structure for Point Cloud Simplification

A point cloud as an information-intensive 3D representation usually requires a large amount of transmission, storage and computing resources, which seriously hinder its usage in many emerging fields. In this paper, we propose novel simplification method, Approximate Intrinsic Voxel Structure (AIVS), to meet the diverse demands real-world application scenarios. The method includes pre-processing (denoising down-sampling), AIVS-based realization for isotropic flexible with intrinsic control distance. To demonstrate effectiveness proposed conducted extensive experiments by comparing it several relevant methods on three public datasets, including Stanford, SHREC, RGB-D scene models. experimental results indicate that AIVS has great advantages over peers terms moving least squares (MLS) surface approximation quality, curvature-sensitive sampling, sharp-feature keeping processing speed. source code is publicly available. ( https://github.com/vvvwo/AIVS-project ).