TR2022-005

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

    •  Fujihashi, T., Koike-Akino, T., Watanabe, T., "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}
      • }
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  • Research Areas:

    Communications, Optimization, Signal Processing

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.