GRiNS: A GRaphical INterface for Creating and Playing SMIL Documents.

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.

A Survey on Adaptive 360° Video Streaming: Solutions, Challenges and Opportunities

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.

Visual Distortions in 360° Videos

In contrast with traditional images, omnidirectional image (OI) has a higher resolution and provides the user with an interactive wide field of view. OI with equirectangular projection (ERP) format, as the default for encoding and transmitting omnidirectional visual contents, is not suitable for quality assessment of OI because of serious geometric distortion in the bipolar regions, especially for blind image quality assessment. In this paper, a segmented spherical projection (SSP) based blind omnidirectional image quality assessment (SSP-BOIQA) method is proposed. The OI with ERP format is first converted into that with SSP format, so as to solve the problem of stretching distortion in the bipolar regions of ERP format, but retain the equatorial region of ERP format. On the one hand, considering that the bipolar regions of the SSP format are circular, a local/global perceptual features extraction scheme with fan-shaped window is proposed for estimating the distortion in the bipolar regions of OI. On the other hand, the perceptual features of the equatorial region are extracted with heat map as weighting factor to reflect users' visual behavior. Then, the features extracted from the OI's bipolar and equatorial regions are pooled to predict the quality of distorted OIs. The experiments on two databases, namely CVIQD2018 and MVAQD databases, demonstrate that the proposed SSP-BOIQA method outperforms the state-of-the-art blind quality assessment methods, and is more consistent with human visual perception.

Segmented Spherical Projection-Based Blind Omnidirectional Image Quality Assessment

360-degree video streaming is expected to grow as the next disruptive innovation due to the ultra-high network bandwidth (60–100 Mbps for 6k streaming), ultra-high storage capacity, and ultra-high computation requirements. Video consumers are more interested in the immersive experience instead of conventional broadband televisions. The visible area (known as user’s viewport) of the video is displayed through Head-Mounted Display (HMD) with a very high frame rate and high resolution. Delivering the whole 360-degree frames in ultra-high-resolution to the end-user significantly adds pressure to the service providers’ overall intention. This paper surveys 360-degree video streaming by focusing on different paradigms from capturing to display. It overviews different projections, compression, and streaming techniques that either incorporate the visual features or spherical characteristics of 360-degree video. Next, the latest ongoing standardization efforts for enhanced degree-of-freedom immersive experience are presented. Furthermore, several 360-degree audio technologies and a wide range of immersive applications are consequently deliberated. Finally, some significant research challenges and implications in the immersive multimedia environment are presented and explained in detail.

360-Degree Video Streaming: A Survey of the State of the Art

In this paper, we give an overview of the semantic gap problem in multimedia and discuss how machine learning and symbolic AI can be combined to narrow this gap. We describe the gap in terms of a classical architecture for multimedia processing and discuss a structured approach to bridge it. This approach combines machine learning (for mapping signals to objects) and symbolic AI (for linking objects to meanings). Our main goal is to raise awareness and discuss the challenges involved in this structured approach to multimedia understanding, especially in the view of the latest developments in machine learning and symbolic AI.

Bridging the Gap between Semantics and Multimedia Processing

Nowadays, tablets and smartphones are commonly used by children for both entertainment and education purposes. In special, interactive multimedia eBooks running on those devices allow a richer experience when compared to traditional text-only books, being potentially more engaging and entertaining to readers. However, to explore the most exciting features in these environments, authors are currently left alone in the sense that there is no high level (less technical) support, and these features are usually accessible only through programming or some other technical skill. In this work, we aim at extracting the main features on enhanced children's eBooks and propose a model, named Fabulas - the Portuguese word for fables -that allows authors to create interactive multimedia children's eBooks declaratively. The model was conceived by taking, as a starting point, a systematic analysis of the common concepts, with the focus on identifying and categorizing recurring characteristics and pointing out functional and non-functional requirements that establish a strong orientation towards the set of desirable abstractions of an underlying model. Moreover, the paper presents a case study for the implementation of Fabulas on the Web, and discusses the authoring of a complete interactive story over it.

The Fábulas Model for Authoring Web-based Children's eBooks

This short course is an introduction to GStreamer, one of the main free/open-source frameworks for multimedia processing. We start presenting GStreamer, its architecture and the dataflow programming model, and then adopt a hands-on approach. Starting with an example, a simple video player, we introduce each concept of GStreamer's basic C API and implement it over the initial example incrementally, so that at the end of the course we get a complete video player with support for the usual playback operations (start, stop, pause, seek, fast-forward, and rewind). We also discuss sample filters'processing elements that manipulate audio and video samples. We present the various filters natively available in GStreamer and show how one can extend the framework by creating a plugin with a custom filter that manipulates video samples. The only prerequisite for the short course is a basic knowledge of the C programming language. At the end of the short course, we expect that participants acquire a general view of GStreamer, and be able to create simple multimedia applications and explore its more advanced features.

Programming Multimedia Applications in GStreamer

Omnidirectional video streaming is usually implemented based on the representations of tiles, where the tiles are obtained by splitting the video frame into several rectangular areas and each tile is converted into multiple representations with different resolutions and encoded at different bitrates. One key issue in omnidirectional video streaming is how to choose the optimal representations for each tile at the server to save the overall transmission bitrate to all users while offering them satisfactory quality. This is different from the adaptive bitrate-based method that optimizes the downloading procedure of individual users, where the given video representations are stored on the server. In this work, we focus on optimization for the encoding of omnidirectional video streaming by using the optimal combination of tile representations. To achieve our goal, we formulate the selection of the representations into an optimization problem in which the transmission bitrate of all the representations is minimized with a quality constraint. By using this constraint, we can improve the average quality of omnidirectional videos for users. More specifically, we first construct the tile-level rate-distortion (R-D) model and determine the available tile bandwidth based on the previous viewers’ statistics. Then, we formulate the representation selection problem based on the obtained R-D model and tile bandwidth. Finally, we solve this problem to obtain the optimal combination of tile representations so that we can transmit the omnidirectional video to users with satisfactory quality but low bitrate. The experimental results demonstrate the effectiveness of our proposed approach when it is applied to omnidirectional video streaming. 

Quality-Constrained Encoding Optimization for Omnidirectional Video Streaming

We present a graphics architecture for the seamless integration of 3DV objects into ordinary 2D/3D multimedia applications. The architecture is based on layered-depth-image (LDI) and supports the real-time rendering of multiple views for multi-view 3D displays. We also present a prototype implementation of the proposed architecture in OpenCL, and discuss experimental results. The results indicate that the proposed approach leads to better results than other state-of-art graphics architecture for multimedia application.

Roberto Gerson de Albuquerque Azevedo

Papers

Bridging the Gap between Semantics and Multimedia Processing

The Fábulas Model for Authoring Web-based Children's eBooks

Programming Multimedia Applications in GStreamer

Quality-Constrained Encoding Optimization for Omnidirectional Video Streaming

A graphics composition architecture for multimedia applications based on layered-depth-image