TR2022-005
Overhead Reduction for Graph-Based Point Cloud Delivery Using Non-Uniform Quantization
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- , "Overhead Reduction for Graph-Based Point Cloud Delivery Using Non-Uniform Quantization", IEEE International Conference on Consumer Electronics (ICCE), DOI: 10.1109/ICCE53296.2022.9730509, January 2022.BibTeX TR2022-005 PDF
- @inproceedings{Fujihashi2022jan,
- author = {Fujihashi, Takuya and Koike-Akino, Toshiaki and Watanabe, Takashi},
- title = {Overhead Reduction for Graph-Based Point Cloud Delivery Using Non-Uniform Quantization},
- booktitle = {IEEE International Conference on Consumer Electronics (ICCE)},
- year = 2022,
- month = jan,
- publisher = {IEEE},
- doi = {10.1109/ICCE53296.2022.9730509},
- issn = {2158-4001},
- isbn = {978-1-6654-4154-4},
- url = {https://www.merl.com/publications/TR2022-005}
- }
- , "Overhead Reduction for Graph-Based Point Cloud Delivery Using Non-Uniform Quantization", IEEE International Conference on Consumer Electronics (ICCE), DOI: 10.1109/ICCE53296.2022.9730509, January 2022.
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Abstract:
Graph-based compression can compact the signal energy of the three-dimensional (3D) point cloud and realize high- quality 3D point cloud delivery over wireless channels. However, it requires significant communication overhead of graph Fourier transform (GFT) orthogonal matrix. For significant overhead reduction, our scheme integrates two methods: Givens rotation and non-uniform quantization. The Givens rotation transforms the GFT orthogonal matrix into angle parameters. The angle parameters are then non-uniformly quantized based on an empir- ical concave cumulative distribution function (CDF). Evaluation results show the proposed scheme reduces 28.6% communication overhead and improve up to 3.8dB 3D reconstruction quality compared with the conventional schemes.