# HoloCast: Graph Signal Processing for Graceful Point Cloud Delivery

arXiv: https://arxiv.org/abs/1903.03247 · HTML: https://mlsanity.com/paper/1903.03247/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Mar 2019.

## Built on by (most cited first, 2 of 2)

- [Joint Source-Channel Coding: Fundamentals and Recent Progress in Practical Designs](https://mlsanity.com/paper/2409.17557/) (2024)
- [Point Cloud in the Air](https://mlsanity.com/paper/2401.00658/) (2024)

## Abstract (arXiv)

In conventional point cloud delivery, a sender uses octree-based digital video compression to stream three-dimensional (3D) points and the corresponding color attributes over band-limited links, e.g., wireless channels, for 3D scene reconstructions. However, the digital-based delivery schemes have an issue called cliff effect, where the 3D reconstruction quality is a step function in terms of wireless channel quality. We propose a novel scheme of point cloud delivery, called HoloCast, to gracefully improve the reconstruction quality with the improvement of wireless channel quality. HoloCast regards the 3D points and color components as graph signals and directly transmits linear-transformed signals based on graph Fourier transform (GFT), without digital quantization and entropy coding operations. One of main contributions in HoloCast is that the use of GFT can deal with non-ordered and non-uniformly distributed multi-dimensional signals such as holographic data unlike conventional delivery schemes. Performance results with point cloud data show that HoloCast yields better 3D reconstruction quality compared to digital-based methods in noisy wireless environment.