@inproceedings{sun2024multi,
author = {Sun, Yuan-Chun and Shi, Yuang and Ooi, Wei Tsang and Huang, Chun-Ying and Hsu, Cheng-Hsin},
title = {Multi-frame Bitrate Allocation of Dynamic 3D Gaussian Splatting Streaming Over Dynamic Networks},
year = {2024},
isbn = {9798400707117},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3672196.3673394},
doi = {10.1145/3672196.3673394},
abstract = {Dynamic 3D Gaussian splats have emerged as an exciting new data type for modeling interactive photo-realistic 3D scenes. This work considers the problem of bitrate allocation for streaming dynamic 3D Gaussian splats under dynamic network conditions. We model four parameters that influence the rate-distortion trade-offs for different attribute categories and propose an efficient Model-driven Gradient Ascent (MGA) algorithm to search for the optimal parameters that achieve high visual quality while keeping the bitrate below a given threshold across multiple frames. In our experiments, MGA achieves up to 5.46 dB in PSNR improvement over the baseline. We further proposed an adaptive MGA that reduces close to 3x computational time with negligible visual quality loss.},
booktitle = {Proceedings of the 2024 SIGCOMM Workshop on Emerging Multimedia Systems},
pages = {1–7},
numpages = {7},
keywords = {3D Gaussian Splatting, Adaptive streaming, Bitrate allocation, Computer graphics, System design},
location = {Sydney, NSW, Australia},
series = {EMS '24}
}