QoE-Driven and Tile-Based Adaptive Streaming for Point Clouds

• Published in: Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) pp. 1930 - 1934
• Main Authors: Wang, Lisha, Li, Chenglin, Dai, Wenrui, Zou, Junni, Xiong, Hongkai
• Format: Conference Proceeding
• Language: English
• Published: IEEE 06.06.2021
• Subjects: Bit rate; perspective projection; Point clouds; rate adaptation; Rendering (computer graphics); Signal processing; Signal processing algorithms; Solid modeling; submodular function maximization; Three-dimensional displays; Visualization
• ISSN: 2379-190X
• DOI: 10.1109/ICASSP39728.2021.9414121

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.