Name
Abstract | ||
|---|---|---|
Application of point clouds is in critical demand, which, however, are composed of large amounts of data and difficult to stream in bandwidth-constrained networks. To address this, we propose a QoE-driven and tile-based adaptive streaming approach for point clouds, to reduce transmission redundancy and maximize user's QoE. Specifically, by utilizing the perspective projection, we model the QoE of a 3D tile as a function of the bitrate of its representation, user's view frustum and spatial position, occlusion between tiles, and the resolution of rendering device. We then formulate the QoE-optimized rate adaptation problem as a multiple-choice knapsack problem that allocates bitrates for different tiles under a given transmission capacity. We equivalently convert it as a submodular function maximization problem subject to knapsack constraints, and develop a practical greedy algorithm with a theoretical performance guarantee. Experimental results further demonstrate superiority of the proposed rate adaptation algorithm over existing schemes, in terms of both user's visual quality and transmission efficiency. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICASSP39728.2021.9414121 | 2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021) |
Keywords | DocType | Citations |
Point clouds, rate adaptation, perspective projection, submodular function maximization | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lisha Wang | 1 | 0 | 0.34 |
| Chenglin Li | 2 | 116 | 17.93 |
| Wenrui Dai | 3 | 64 | 25.01 |
| J. Zou | 4 | 203 | 35.51 |
| Hongkai Xiong | 5 | 512 | 82.84 |