Overhead Reduction for Graph-Based Point Cloud Delivery Using Non-Uniform Quantization

Abstract

Graph-based compression can realize a high-quality delivery of three-dimensional (3D) point cloud data over wireless channels. However, it requires a significant amount of communication overhead in sending a graph Fourier transform (GFT) orthogonal matrix. To reduce the overhead, we integrate two methods: Givens rotation and non-uniform quantization. The Givens rotation transforms the GFT orthogonal matrix into angle parameters, and then they are non-uniformly quantized to maintain high quality at low overheads. We demonstrate that the proposed scheme can reduce a communication overhead by 28.6% and improve a 3D reconstruction quality by up to 3.8 dB compared with the conventional schemes.