392 research outputs found
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
Leveraging Tiled Display for Big Data Visualization Using D3.js
Data visualization has proven effective at detecting patterns and drawing inferences from raw data by transforming it into visual representations. As data grows large, visualizing it faces two major challenges: 1) limited resolution i.e. a screen is limited to a few million pixels but the data can have a billion data points, and 2) computational load i.e. processing of this data becomes computationally challenging for a single node system. This work addresses both of these issues for efficient big data visualization. In the developed system, a High Pixel Density and Large Format display was used enabling the display of fine details on the screen when visualizing data. Apache Spark and Hadoop used in the system allow the computation to be done on a cluster.
The system is demonstrated using a global wind flow simulation. The Global Surface Summary of the Day dataset is processed and visualized using web browsers with Data-Driven Documents (D3).js code. We conducted both a performance evaluation and a user study to measure the performance and effectiveness of the system. It was seen that the system was most efficient when visualizing data using streamed bitmap images rather than streamed raw data. The system only rendered images at 6-10 Frames Per Second (FPS) and did not meet our target of rendering images at 30 FPS. The results of the user study concluded that the system is effective and easy to use for data visualization. The outcome of our experiment suggests that the current state of Google Chrome may not be as powerful as required to perform heavy 2D data visualization on the web and still needs more development for visualizing data of large magnitude
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Video Adaptation for High-Quality Content Delivery
Modern video players employ complex algorithms to adapt the bitrate of the video that is shown to the user. Bitrate adaptation requires a tradeoff between reducing the probability that the video freezes (rebuffers) and enhancing the quality of the video. A bitrate that is too high leads to frequent rebuffering, while a bitrate that is too low leads to poor video quality. In this dissertation we propose video-adaptation algorithms to deliver content and maximize the viewer\u27s quality of experience (QoE).
Video providers partition videos into short segments and encode each segment at multiple bitrates. The video player adaptively chooses the bitrate of each segment to download, possibly choosing different bitrates for successive segments. We formulate bitrate adaptation as a utility-maximization problem, and design algorithms to provide provably near-optimal time-average utility.
Real-world systems are generally too complex to be fully represented in a theoretical model and thus present a new set of challenges. We design algorithms that deliver video on production systems, maintaining the strengths of the theoretical algorithms while also tackling challenges faced in production. Our algorithms are now part of the official DASH reference player dash.js and are being used by video providers in production environments.
Most online video is streamed via HTTP over TCP. TCP provides reliable delivery at the expense of additional latency incurred when retransmitting lost packets and head-of-line blocking. Using QUIC allows the video player to tolerate some packet loss without incurring the performance penalties. We design and implement algorithms that exploit this added flexibility to provide higher overall QoE by reducing latency and rebuffering while allowing some packet loss.
Recently virtual reality content is increasing in popularity, and delivering 360° video comes with new challenges and opportunities. The viewing space is often partitioned in tiles, and a viewer using a head-mounted display only sees a subset of the tiles at any time. We develop an open source simulation environment for fast and reproducible testing of 360° algorithms. We develop adaptation algorithms that provide high QoE by allocating more bandwidth resources to deliver the tiles that the viewer is more likely to see, while ensuring that the video player reacts in a timely manner when the viewer changes their head pose
Navigation-Aware Adaptive Streaming Strategies for Omnidirectional Video
Virtual reality (VR) applications target high-quality and zero-latency scene navigation to provide users with a full-immersion sensation within a scene. From a network perspective, this requires transmission of the omnidirectional content in its entirety, at a high resolution, which is not always feasible in bandwidth-limited networks. In this work, we propose an optimal transmission strategy for virtual reality applications able to fulfill the bandwidth requirements, while optimizing the end-user quality experienced in the navigation. In further detail, we consider a tile-based coded content for adaptive streaming systems, and we propose a navigation-aware transmission strategy at the clientside (i.e., adaptation logic), which is able to optimize the rate at which each tile is downloaded. First, we introduce the viewport- quality as metric that reflects the quality of any portion of the sphere displayed by the end-user. Then, we cast the tile-rate optimization as an integer linear programming problem and show that the proposed solution achieves substantial quality gains when compared to state-of-the-art adaptation logic methods
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
Serious Games in Cultural Heritage
Although the widespread use of gaming for leisure purposes has been well documented, the use of games to support cultural heritage purposes, such as historical teaching and learning, or for enhancing museum visits, has been less well considered. The state-of-the-art in serious game technology is identical to that of the state-of-the-art in entertainment games technology. As a result the field of serious heritage games concerns itself with recent advances in computer games, real-time computer graphics, virtual and augmented reality and artificial intelligence. On the other hand, the main strengths of serious gaming applications may be generalised as being in the areas of communication, visual expression of information, collaboration mechanisms, interactivity and entertainment. In this report, we will focus on the state-of-the-art with respect to the theories, methods and technologies used in serious heritage games. We provide an overview of existing literature of relevance to the domain, discuss the strengths and weaknesses of the described methods and point out unsolved problems and challenges. In addition, several case studies illustrating the application of methods and technologies used in cultural heritage are presented
Visual Distortions in 360-degree Videos.
Omnidirectional (or 360°) images and videos are emergent signals being used in many areas, such as robotics and virtual/augmented reality. In particular, for virtual reality applications, they allow an immersive experience in which the user can interactively navigate through a scene with three degrees of freedom, wearing a head-mounted display. Current approaches for capturing, processing, delivering, and displaying 360° content, however, present many open technical challenges and introduce several types of distortions in the visual signal. Some of the distortions are specific to the nature of 360° images and often differ from those encountered in classical visual communication frameworks. This paper provides a first comprehensive review of the most common visual distortions that alter 360° signals going through the different processing elements of the visual communication pipeline. While their impact on viewers' visual perception and the immersive experience at large is still unknown-thus, it is an open research topic-this review serves the purpose of proposing a taxonomy of the visual distortions that can be encountered in 360° signals. Their underlying causes in the end-to-end 360° content distribution pipeline are identified. This taxonomy is essential as a basis for comparing different processing techniques, such as visual enhancement, encoding, and streaming strategies, and allowing the effective design of new algorithms and applications. It is also a useful resource for the design of psycho-visual studies aiming to characterize human perception of 360° content in interactive and immersive applications
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