Title
HoloCast: Graph Signal Processing for Graceful Point Cloud Delivery.
Abstract
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 multidimensional 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.
Year
Venue
Field
2019
IEEE International Conference on Communications
Entropy encoding,Wireless,Computer science,Communication channel,Real-time computing,Point cloud,Quantization (signal processing),3D reconstruction,Cliff effect,Octree
DocType
Volume
ISSN
Journal
abs/1903.03247
1550-3607
Citations 
PageRank 
References 
0
0.34
9
Authors
4
Name
Order
Citations
PageRank
Takuya Fujihashi13411.65
Toshiaki Koike-Akino261067.09
takashi watanabe38423.31
Philip V. Orlik439059.37