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Advanced Predictive Tile Selection Using Dynamic Tiling for Prioritized 360° Video VR Streaming

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PubDate:July 2023

Teams:Dublin City University

Writers:Abid Yaqoob,Gabriel-Miro Muntean

PDF:Advanced Predictive Tile Selection Using Dynamic Tiling for Prioritized 360° Video VR Streaming

Abstract

The widespread availability of smart computing and display devices such as mobile phones, gaming consoles, laptops, and tethered/untethered head-mounted displays has fueled an increase in demand for omnidirectional (360°) videos. 360° video applications enable users to change their viewing angles while interacting with the video during playback. This allows users to have a more personalized and interactive viewing experience. Unfortunately, these applications require substantial network and computational resources that the conventional infrastructure and end devices cannot support. Recently proposed viewport adaptive fixed tiling solutions stream only relevant video tiles based on user interaction with the virtual reality (VR) space to use existing transmission resources more efficiently. However, achieving real-time accurate viewport extraction and transmission in response to both head movements and bandwidth dynamics can be challenging, which can impact the user’s Quality of Experience (QoE). This article proposes innovative dynamic tiling-based adaptive 360° video streaming solutions in order to achieve high viewer QoE. First, novel and easy-to-scale tiling layout selection methods are introduced, and the best tiling layouts are employed in each adaptation interval based on the prediction-assisted visual quality metric and the observed viewport divergence. Second, a novel proactive tile selection approach is presented, which adaptively extracts tiles for each selected tiling layout based on two low-complex viewport prediction mechanisms. Finally, a practical dynamic tile priority-oriented bitrate adaptation scheme is introduced, which uniformly distributes the bitrate budget among different tiles during 360° video streaming. Extensive trace-driven experiments are conducted to evaluate the proposed solutions using head motion traces from 48 VR users for five 360° videos with tiling layouts of 4 × 3, 6 × 4, and 8 × 6 and segment durations of 1s, 1.5s, and 2s. The experimental evaluations show that the dynamic video tiling solutions achieve up to 11.2% more viewport matches and an average improvement in QoE of 9.7% to 18% compared to state-of-the-art 360° streaming approaches.

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