细化包围体用于体素化点云几何的无损压缩
计算机视觉与模式识别
2021-06-03 v1 多媒体
摘要
本文描述了一种新颖的点云几何无损压缩方法，其构建于近期一种仅旨在重建点云包围体的有损压缩方法之上。所提方案首先从与单一投影方向相关的两张深度图中部分重建几何。通过沿一个方向逐截面扫描，并编码未包含在这两张深度图中的点，将由深度图获得的部分重建补充为点云的完整重建。主要成分是一种基于列表的内部点（位于可行区域内部的点）编码方法，通过一种新颖的算术三维上下文编码过程，有效利用输入数据中存在的旋转不变性。在基准数据集上获得了最先进的每体素比特数结果。
引用
@article{arxiv.2106.00828,
title = {Refining the bounding volumes for lossless compression of voxelized point clouds geometry},
author = {Emre Can Kaya and Sebastian Schwarz and Ioan Tabus},
journal= {arXiv preprint arXiv:2106.00828},
year = {2021}
}
备注
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