Omnidirectional or 360 • video is increasingly being used, mostly due to the latest advancements in immersive Virtual Reality (VR) technology. However, its wide adoption is hindered by the higher bandwidth and lower latency requirements than associated with traditional video content delivery. Diverse researchers propose and design solutions that help support an immersive visual experience of 360 • video, primarily when delivered over a dynamic network environment. This paper presents the state-of-the-art on adaptive 360 • video delivery solutions considering end-to-end video streaming in general and then specifically of 360 • video delivery. Current and emerging solutions for adaptive 360 • video streaming, including viewport-independent, viewport-dependent, and tile-based schemes are presented. Next, solutions for network-assisted unicast and multicast streaming of 360 • video content are discussed. Different research challenges for both on-demand and live 360 • video streaming are also analyzed. Several proposed standards and technologies and top international research projects are then presented. We demonstrate the ongoing standardization efforts for 360 • media services that ensure interoperability and immersive media deployment on a massive scale. Finally, the paper concludes with a discussion about future research opportunities enabled by 360 • video.

Recently, 360 • or omnidirectional videos have become increasingly popular for both personal and enterprize use-cases. However, 360 • video streaming has very high bandwidth and processing requirements. State-of-the-art viewport-based streaming solutions lower these requirements by performing selective streaming based on long-term Field-of-View (FoV) prediction mechanisms. However, sometimes user movement is extremely unpredictable during some parts of the video, and applying these solutions adversely affects the overall quality of experience (QoE). This paper proposes a novel Combined Field-of-View tile-based adaptive streaming solution (CFOV) that improves end-user QoE for 360 • video streaming. CFOV performs interactive tile selection based on more accurate dynamical viewing area identification by combining the results of two FoV prediction mechanisms. It also employs an innovative priority-based bitrate adaptation approach that ensures improved bitrate budget distribution between different tiles. We evaluate the proposed solution with a comprehensive set of experiments involving four immersive videos, diverse tiling patterns (i.e., 4x3, 6x4, and 8x6), different segment lengths (i.e., 1s, 2s, and 3s), and 48 empirical head movement traces under different bandwidth settings. The evaluation employs a newly defined QoE metric specifically introduced to assess the streaming performance of 360 • videos objectively. The experimental findings show that, compared to alternative approaches, our proposed solution can achieve a higher viewport match and can significantly improve the user QoE for different watching behaviors and content characteristics.

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Interactive 360°remote video applications have seen booming advancements due to the proliferation of smart display devices that enable a truly immersive experience. Compared to regular monoscopic videos, 360°videos have different requirements related to content preparation, packaging, transmission, specialized viewing equipment, and display factors (e.g., brightness, contrast, delay, frame rate, resolution, image quality, etc. In addition, 360°video requires substantial network and computational resources, which are challenging to achieve with conventional transmission and rendering infrastructure. Viewport-adaptive streaming is a common way to ensure visual quality under limited bandwidth resources. However, identifying, extracting, and rendering the true viewport in response to drastic head rotations can adversely affect user experience. This paper proposes two dynamic viewport selection approaches, which adapt the streamed regions based on content complexity variations and positional information to ensure viewport availability and smooth visual angles for VR users. They incorporate content information as well as user head movement patterns to support tile-based prioritized 360°video streaming. Moreover, a practical, prioritized bitrate adaptation approach, which requests selected tiles at appropriate quality levels, is also proposed to reduce the impact of inefficient bandwidth utilization in the VR scene. Experimental evaluations under real 4G bandwidth logs demonstrate that the proposed solutions outperform the closest state-of-theart algorithms across multiple performance metrics, i.e., viewport overlap, perceived quality levels, quality fluctuations, and viewport bandwidth utilization.