Streaming and User Behaviour in Omnidirectional Videos

Omnidirectional videos (ODVs) have gone beyond the passive paradigm of traditional video, offering higher degrees of immersion and interaction. The revolutionary novelty of this technology is the possibility for users to interact with the surrounding environment, and to feel a sense of engagement and presence in a virtual space. Users are clearly the main driving force of immersive applications and consequentially the services need to be properly tailored to them. In this context, this chapter highlights the importance of the new role of users in ODV streaming applications, and thus the need for understanding their behaviour while navigating within ODVs. A comprehensive overview of the research efforts aimed at advancing ODV streaming systems is also presented. In particular, the state-of-the-art solutions under examination in this chapter are distinguished in terms of system-centric and user-centric streaming approaches: the former approach comes from a quite straightforward extension of well-established solutions for the 2D video pipeline while the latter one takes the benefit of understanding users’ behaviour and enable more personalised ODV streaming

A Measurement Study of Live 360 Video Streaming Systems

360-degree live video streaming is becoming increasingly popular. While providing viewers with enriched experience, 360-degree live video streaming is challenging to achieve since it requires a significantly higher bandwidth and a powerful computation infrastructure. A deeper understanding of this emerging system would benefit both viewers and system designers. Although prior works have extensively studied regular video streaming and 360-degree video on demand streaming, we for the first time investigate the performance of 360-degree live video streaming. We conduct a systematic measurement of YouTube’s 360-degree live video streaming using various metrics in multiple practical settings. Our research insight will help to build a clear understanding of today’s 360-degree live video streaming and lay a foundation for future research on this emerging yet relatively unexplored area. To further understand the delay measured in YouTube’s 360-degree live video streaming, we conduct the second measurement study on a 360-degree live video streaming platform. While live 360-degree video streaming provides an enriched viewing experience, it is challenging to guarantee the user experience against the negative effects introduced by start-up delay, event-to-eye delay, and low frame rate. It is therefore imperative to understand how different computing tasks of a live 360-degree streaming system contribute to these three delay metrics. Our measurement provide insights for future research directions towards improving the user experience of live 360-degree video streaming. Based on our measurement results, we propose a motion-based trajectory transmission method for 360-degree video streaming. First, we design a testbed for 360-degree video playback. The testbed can collect the users viewing data in real time. Then we analyze the trajectories of the moving targets in the 360-degree videos. Specifically, we utilize optical flow algorithms and gaussian mixture model to pinpoint the trajectories. Then we choose the trajectories to be delivered based on the size of the moving targets. The experiment results indicates that our method can obviously reduce the bandwidth consumption

Delivery of 360° videos in edge caching assisted wireless cellular networks

In recent years, 360° videos have become increasingly popular on commercial social platforms, and are a vital part of emerging Virtual Reality (VR) applications. However, the delivery of 360° videos requires significant bandwidth resources, which makes streaming of such data on mobile networks challenging. The bandwidth required for delivering 360° videos can be reduced by exploiting the fact that users are interested in viewing only a part of the video scene, the requested viewport. As different users may request different viewports, some parts of the 360° scenes may be more popular than others. 360° video delivery on mobile networks can be facilitated by caching popular content at edge servers, and delivering it from there to the users. However, existing edge caching schemes do not take full potential of the unequal popularity of different parts of a video, which renders them inefficient for caching 360° videos. Inspired by the above, in this thesis, we investigate how advanced 360° video coding tools, i.e., encoding into multiple quality layers and tiles, can be utilized to build more efficient wireless edge caching schemes for 360° videos. The above encoding allows the caching of only the parts of the 360° videos that are popular in high quality. To understand how edge caching schemes can benefit from 360° video coding, we compare the caching of 360° videos encoded into multiple quality layers and tiles with layer-agnostic and tile-agnostic schemes. To cope with the fact that the content popularity distribution may be unknown, we use machine learning techniques, for both Video on Demand (VoD), and live streaming scenarios. From our findings, it is clear that by taking into account the aforementioned 360° video characteristics leads to an increased performance in terms of the quality of the video delivered to the users, and the usage of the backhaul links

Understanding user interactivity for the next-generation immersive communication: design, optimisation, and behavioural analysis

Recent technological advances have opened the gate to a novel way to communicate remotely still feeling connected. In these immersive communications, humans are at the centre of virtual or augmented reality with a full sense of immersion and the possibility to interact with the new environment as well as other humans virtually present. These next-generation communication systems hide a huge potential that can invest in major economic sectors. However, they also posed many new technical challenges, mainly due to the new role of the final user: from merely passive to fully active in requesting and interacting with the content. Thus, we need to go beyond the traditional quality of experience research and develop user-centric solutions, in which the whole multimedia experience is tailored to the final interactive user. With this goal in mind, a better understanding of how people interact with immersive content is needed and it is the focus of this thesis. In this thesis, we study the behaviour of interactive users in immersive experiences and its impact on the next-generation multimedia systems. The thesis covers a deep literature review on immersive services and user centric solutions, before develop- ing three main research strands. First, we implement novel tools for behavioural analysis of users navigating in a 3-DoF Virtual Reality (VR) system. In detail, we study behavioural similarities among users by proposing a novel clustering algorithm. We also introduce information-theoretic metrics for quantifying similarities for the same viewer across contents. As second direction, we show the impact and advantages of taking into account user behaviour in immersive systems. Specifically, we formulate optimal user centric solutions i) from a server-side perspective and ii) a navigation aware adaptation logic for VR streaming platforms. We conclude by exploiting the aforementioned behavioural studies towards a more in- interactive immersive technology: a 6-DoF VR. Overall in this thesis, experimental results based on real navigation trajectories show key advantages of understanding any hidden patterns of user interactivity to be eventually exploited in engineering user centric solutions for immersive systems

User centered adaptive streaming of dynamic point clouds with low complexity tiling

In recent years, the development of devices for acquisition and rendering of 3D contents have facilitated the diffusion of immersive virtual reality experiences. In particular, the point cloud representation has emerged as a popular format for volumetric photorealistic reconstructions of dynamic real world objects, due to its simplicity and versatility. To optimize the delivery of the large amount of data needed to provide these experiences, adaptive streaming over HTTP is a promising solution. In order to ensure the best quality of experience within the bandwidth constraints, adaptive streaming is combined with tiling to optimize the quality of what is being visualized by the user at a given moment; as such, it has been successfully used in the past for omnidirectional contents. However, its adoption to the point cloud streaming scenario has only been studied to optimize multi-object delivery. In this paper, we present a low-complexity tiling approach to perform adaptive streaming of point cloud content. Tiles are defined by segmenting each point cloud object in several parts, which are then independently encoded. In order to evaluate the approach, we first collect real navigation paths, obtained through a user study in 6 degrees of freedom with 26 participants. The variation in movements and interaction behaviour among users indicate that a user-centered adaptive delivery could lead to sensible gains in terms of perceived quality. Evaluation of the performance of the proposed tiling approach against state of the art solutions for point cloud compression, performed on the collected navigation paths, confirms that considerable gains can be obtained by exploiting user-adaptive streaming, achieving bitrate gains up to 57% with respect to a non-adaptive approach with the same codec. Moreover, we demonstrate that the selection of navigation data has an impact on the relative objective scores

Network and Content Intelligence for 360 Degree Video Streaming Optimization

In recent years, 360° videos, a.k.a. spherical frames, became popular among users creating an immersive streaming experience. Along with the advances in smart- phones and Head Mounted Devices (HMD) technology, many content providers have facilitated to host and stream 360° videos in both on-demand and live stream- ing modes. Therefore, many different applications have already arisen leveraging these immersive videos, especially to give viewers an impression of presence in a digital environment. For example, with 360° videos, now it is possible to connect people in a remote meeting in an interactive way which essentially increases the productivity of the meeting. Also, creating interactive learning materials using 360° videos for students will help deliver the learning outcomes effectively. However, streaming 360° videos is not an easy task due to several reasons. First, 360° video frames are 4–6 times larger than normal video frames to achieve the same quality as a normal video. Therefore, delivering these videos demands higher bandwidth in the network. Second, processing relatively larger frames requires more computational resources at the end devices, particularly for end user devices with limited resources. This will impact not only the delivery of 360° videos but also many other applications running on shared resources. Third, these videos need to be streamed with very low latency requirements due their interactive nature. Inability to satisfy these requirements can result in poor Quality of Experience (QoE) for the user. For example, insufficient bandwidth incurs frequent rebuffer- ing and poor video quality. Also, inadequate computational capacity can cause faster battery draining and unnecessary heating of the device, causing discomfort to the user. Motion or cyber–sickness to the user will be prevalent if there is an unnecessary delay in streaming. These circumstances will hinder providing im- mersive streaming experiences to the much-needed communities, especially those who do not have enough network resources. To address the above challenges, we believe that enhancements to the three main components in video streaming pipeline, server, network and client, are essential. Starting from network, it is beneficial for network providers to identify 360° video flows as early as possible and understand their behaviour in the network to effec- tively allocate sufficient resources for this video delivery without compromising the quality of other services. Content servers, at one end of this streaming pipeline, re- quire efficient 360° video frame processing mechanisms to support adaptive video streaming mechanisms such as ABR (Adaptive Bit Rate) based streaming, VP aware streaming, a streaming paradigm unique to 360° videos that select only part of the larger video frame that fall within the user-visible region, etc. On the other end, the client can be combined with edge-assisted streaming to deliver 360° video content with reduced latency and higher quality. Following the above optimization strategies, in this thesis, first, we propose a mech- anism named 360NorVic to extract 360° video flows from encrypted video traffic and analyze their traffic characteristics. We propose Machine Learning (ML) mod- els to classify 360° and normal videos under different scenarios such as offline, near real-time, VP-aware streaming and Mobile Network Operator (MNO) level stream- ing. Having extracted 360° video traffic traces both in packet and flow level data at higher accuracy, we analyze and understand the differences between 360° and normal video patterns in the encrypted traffic domain that is beneficial for effec- tive resource optimization for enhancing 360° video delivery. Second, we present a WGAN (Wesserstien Generative Adversarial Network) based data generation mechanism (namely VideoTrain++) to synthesize encrypted network video traffic, taking minimal data. Leveraging synthetic data, we show improved performance in 360° video traffic analysis, especially in ML-based classification in 360NorVic. Thirdly, we propose an effective 360° video frame partitioning mechanism (namely VASTile) at the server side to support VP-aware 360° video streaming with dy- namic tiles (or variable tiles) of different sizes and locations on the frame. VASTile takes a visual attention map on the video frames as the input and applies a com- putational geometric approach to generate a non-overlapping tile configuration to cover the video frames adaptive to the visual attention. We present VASTile as a scalable approach for video frame processing at the servers and a method to re- duce bandwidth consumption in network data transmission. Finally, by applying VASTile to the individual user VP at the client side and utilizing cache storage of Multi Access Edge Computing (MEC) servers, we propose OpCASH, a mech- anism to personalize the 360° video streaming with dynamic tiles with the edge assistance. While proposing an ILP based solution to effectively select cached variable tiles from MEC servers that might not be identical to the requested VP tiles by user, but still effectively cover the same VP region, OpCASH maximize the cache utilization and reduce the number of requests to the content servers in congested core network. With this approach, we demonstrate the gain in latency and bandwidth saving and video quality improvement in personalized 360° video streaming