.png){kind=icon}
返回
Hypergraph Spectral Analysis and Processing in 3D Point Cloud
.png){kind=icon}
OA
AI
DOI：10.1109/TIP.2020.3042088.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Along with increasingly popular virtual reality applications, the three-dimensional (3D) point cloud has become a fundamental data structure to characterize 3D objects and surroundings. To process 3D point clouds efficiently, a suitable model for the underlying structure and outlier noises is always critical. In this work, we propose a hypergraph-based new point cloud model that is amenable to efficient analysis and processing. We introduce tensor-based methods to estimate hypergraph spectrum components and frequency coefficients of point clouds in both ideal and noisy settings. We establish an analytical connection between hypergraph frequencies and structural features. We further evaluate the efficacy of hypergraph spectrum estimation in two common applications of sampling and denoising of point clouds for which we provide specific hypergraph filter design and spectral properties. Experimental results demonstrate the strength of hypergraph signal processing as a tool in characterizing the underlying properties of 3D point clouds.
Keyword:
Three-dimensional displays
Tensors
Solid modeling
Signal processing
Spectral analysis
Octrees
Analytical models
3D point clouds
hypergraph signal processing
hypergraph construction
denoising
sampling
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
13.7
论文数:
1.0W
被引数:
8.4W
机构
引用论文
Changes in oestrous cyclicity following olfactory bulbectomy in post-pubertal pigs.png)
ReproductionOAAI
ReproductionIF0
OAAI分享收藏分享收藏
分享收藏
查看更多内容