This project is part of a 4 year Dual PhD degree programme between the National Tsing Hua University (NTHU) in Taiwan and the University of Liverpool in England. As Part of the NTHU-UoL Dual PhD Award students are in the unique position of being able to gain 2 PhD awards at the end of their degree from two internationally recognised world leading Universities. As well as benefiting from a rich cultural experience, Students can draw on large scale national facilities of both countries and create a worldwide network of contacts across 2 continents.
This project plans to develop optimal and approximation algorithms for bitrate adaptation and packet scheduling in 6 Degree-of-Freedom Virtual Reality streaming systems, in order to maximize the user experience.
Virtual Reality (VR) technologies have gained immense popularity, as indicated by the number of Head-Mounted Displays (HMDs) and VR applications hitting the market. Conventional VR only supports 3 Degrees-of-Freedom (3-DoF), which enables 360-degree viewing orientations using 360-degree videos. However, users can just rotate their heads to see different orientations but cannot move or walk within VR environments. 6 Degree-of-Freedom (6-DoF) was proposed to allow users to change their positions freely. To enable 6-DoF VR, various 3D data representations, e.g., point cloud, mesh, multi-view videos, and light field, are needed to describe 3D scenes. These representations have tremendous data size and are hard to be transmitted in real-time by the current network. To solve this problem, we plan to develop novel Adaptive Bitrate (ABR) algorithms to dynamically adjust the bitrate of 6-DoF streaming according to available bandwidth. To the best of our knowledge, ABR algorithms for 6-DoF VR streaming have not been investigated until very recently. For example, Van der Hooft et al.  proposed a streaming system for point clouds consisting of multiple objects. They designed several heuristic ABR algorithms to adjust bitrate according to the user's states and network conditions. Qian et al.  proposed a volumetric streaming system for commodity mobile devices, which leveraged edge computing and rate adaptation to adapt bandwidth and reduce motion-to-photon delay dynamically. These two, and other similar studies only adopted heuristic ABR algorithms with little, if any, performance guarantees. This project aims to develop a general ABR algorithm framework suitable for heterogeneous 3D data representations used in 6-DoF VR streaming.
For academic enquires please contact Prof Prudence Wong firstname.lastname@example.org & Associate Prof Cheng-Hsin Hsu email@example.com
For enquires on the application process or to find out more about the Dual programme please contact firstname.lastname@example.org