Multimedia Communication

Christian Timmerer

QUALINET announces its recent White Paper on Definitions of Immersive Media Experience (IMEx)

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With the coming of age of virtual/augmented reality and interactive media, numerous definitions, frameworks, and models of immersion have emerged across different fields ranging from computer graphics to literary works. Immersion is oftentimes used interchangeably with presence as both concepts are closely related. However, there are noticeable interdisciplinary differences regarding definitions, scope, and constituents that are required to be addressed so that a coherent understanding of the concepts can be achieved. Such consensus is vital for paving the directionality of the future of immersive media experiences (IMEx) and all related matters. Read more

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ACM Multimedia’20: Relevance-Based Compression of Cataract Surgery Videos Using Convolutional Neural Networks

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Authors: Negin Ghamsarian (Alpen-Adria-Universität Klagenfurt), Hadi Amirpour (Alpen-Adria-Universität Klagenfurt), Christian Timmerer (Alpen-Adria-Universität Klagenfurt, Bitmovin), Mario Taschwer (Alpen-Adria-Universität Klagenfurt), and Klaus Schöffmann (Alpen-Adria-Universität Klagenfurt)

Abstract: Recorded cataract surgery videos play a prominent role in training and investigating the surgery, and enhancing the surgical outcomes. Due to storage limitations in hospitals, however, the recorded cataract surgeries are deleted after a short time and this precious source of information cannot be fully utilized. Lowering the quality to reduce the required storage space is not advisable since the degraded visual quality results in the loss of relevant information that limits the usage of these videos. To address this problem, we propose a relevance-based compression technique consisting of two modules: (i) relevance detection, which uses neural networks for semantic segmentation and classification of the videos to detect relevant spatio-temporal information, and (ii) content-adaptive compression, which restricts the amount of distortion applied to the relevant content while allocating less bitrate to irrelevant content. The proposed relevance-based compression framework is implemented considering five scenarios based on the definition of relevant information from the target audience’s perspective. Experimental results demonstrate the capability of the proposed approach in relevance detection. We further show that the proposed approach can achieve high compression efficiency by abstracting substantial redundant information while retaining the high quality of the relevant content.

ACM International Conference on Multimedia 2020, Seattle, United States.

Link: https://2020.acmmm.org

Keywords: Video Coding, Convolutional Neural Networks, HEVC, ROI Detection, Medical Multimedia.

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Paper “Scalable High Efficiency Video Coding based HTTP Adaptive Streaming over QUIC Using Retransmission” hs been accepted at EPIQ 2020

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Authors: Minh Nguyen, Hadi Amirpour, Christian Timmerer, Hermann Hellwagner (Alpen-Adria-Universität Klagenfurt)

Abstract: HTTP/2 has been explored widely for video streaming, but still suffers from Head-of-Line blocking, and three-way hand-shake delay due to TCP. Meanwhile, QUIC running on top of UDP can tackle these issues. In addition, although many adaptive bitrate (ABR) algorithms have been proposed for scalable and non-scalable video streaming, the literature lacks an algorithm designed for both types of video streaming approaches. In this paper, we investigate the impact of quick and HTTP/2 on the performance of adaptive bitrate(ABR) algorithms in terms of different metrics. Moreover, we propose an efficient approach for utilizing scalable video coding formats for adaptive video streaming that combines a traditional video streaming approach (based on non-scalable video coding formats) and a retransmission technique. The experimental results show that QUIC benefits significantly from our proposed method in the context of packet loss and retransmission.

Compared to HTTP/2, it improves the average video quality and also provides a smoother adaptation behavior. Finally, we demonstrate that our proposed method originally designed for non-scalable video codecs also works efficiently for scalable videos such as Scalable High EfficiencyVideo Coding (SHVC).

Keywords: QUIC, H2BR, HTTP adaptive streaming, Retransmission, SHVC

Conference: ACM SIGCOMM 2020 Workshop on Evolution, Performance, and Interoperability of QUIC (EPIQ 2020), August 10-14, 2020, Newyork City, USA.

Link: https://conferences.sigcomm.org/sigcomm/2020/workshop-epiq.html

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Christian Timmerer

Christian Doppler Lab ATHENA papers wins best paper award at QoMEX 2020

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Title: Objective and Subjective QoE Evaluation for Adaptive Point Cloud Streaming

Authors: Jeroen van der Hooft (Ghent University), Maria Torres Vega (Ghent University), Christian Timmerer (Alpen-Adria-Universität Klagenfurt, Bitmovin), Ali C. Begen (Ozyegin University, Networked Media), Filip De Turck (Ghent University), Raimund Schatz (Alpen-Adria Universität Klagenfurt & AIT Austrian Institute of Technology, Austria)

Abstract: Volumetric media has the potential to provide the six degrees of freedom (6DoF) required by truly immersive media. However, achieving 6DoF requires ultra-high bandwidth transmissions, which real-world wide area networks cannot provide economically. Therefore, recent efforts have started to target efficient delivery of volumetric media, using a combination of compression and adaptive streaming techniques. It remains, however, unclear how the effects of such techniques on the user perceived quality can be accurately evaluated. In this paper, we present the results of an extensive objective and subjective quality of experience (QoE) evaluation of volumetric 6DoF streaming. We use PCC-DASH, a standards-compliant means for HTTP adaptive streaming of scenes comprising multiple dynamic point cloud objects. By means of a thorough analysis we investigate the perceived quality impact of the available bandwidth, rate adaptation algorithm, viewport prediction strategy and user’s motion within the scene. We determine which of these aspects has more impact on the user’s QoE, and to what extent subjective and objective assessments are aligned.

Keywords: Volumetric Media; HTTP Adaptive Streaming; 6DoF; MPEG V-PCC; QoE Assessment; Objective Metrics

International Conference on Quality of Multimedia Experience (QoMEX)
May 26-28, 2020, Athlone, Ireland
http://qomex2020.ie/

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PV’20: H2BR: An HTTP/2-based Retransmission Technique to Improve the QoE of Adaptive Video Streaming

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Authors: Minh Nguyen (Alpen-Adria-Universität Klagenfurt), Christian Timmerer (Alpen-Adria-Universität Klagenfurt / Bitmovin Inc.), Hermann Hellwagner (Alpen-Adria-Universität Klagenfurt)

Abstract: HTTP-based Adaptive Streaming (HAS) plays a key role in over-the-top video streaming. It contributes towards reducing the rebuffering duration of video playout by adapting the video quality to the current network conditions. However, it incurs variations of video quality in a streaming session because of the throughput fluctuation, which impacts the user’s Quality of Experience (QoE). Besides, many adaptive bitrate (ABR) algorithms choose the lowest-quality segments at the beginning of the streaming session to ramp up the playout buffer as soon as possible. Although this strategy decreases the startup time, the users can be annoyed as they have to watch a low-quality video initially. In this paper, we propose an efficient retransmission technique, namely H2BR, to replace low-quality segments being stored in the playout buffer with higher-quality versions by using features of HTTP/2 including (i) stream priority, (ii) server push, and (iii) stream termination. The experimental results show that H2BR helps users avoid watching low video quality during video playback and improves the user’s QoE. H2BR can decrease by up to more than 70% the time when the users suffer the lowest-quality video as well as benefits the QoE by up to 13%.

Keywords: HTTP adaptive streaming, DASH, ABR algorithms, QoE, HTTP/2

Packet Video Workshop 2020 (PV) June 10-11, 2020, Istanbul, Turkey (co-located with ACM MMSys’20)

Link: https://2020.packet.video/

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ICME’20: Towards View-aware Adaptive Streaming of Holographic content

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Authors: Hadi Amirpour (Alpen-Adria-Universität Klagenfurt), Christian Timmerer (Alpen-Adria-Universität Klagenfurt, Bitmovin), and Mohammad Ghanbari (University of Essex)

Abstract: Holography is able to reconstruct a three-dimensional structure of an object by recording full wave fields of light emitted from the object. This requires a huge amount of data to be encoded, stored, transmitted, and decoded for holographic content, making its practical usage challenging especially for bandwidth-constrained networks and memory-limited devices. In the delivery of holographic content via the internet, bandwidth wastage should be avoided to tackle high bandwidth demands of holography streaming. For real-time applications, encoding time-complexity is also a major problem. In this paper, the concept of dynamic adaptive streaming over HTTP (DASH) is extended to holography image streaming and view-aware adaptation techniques are studied. As each area of a hologram contains information of a specific view, instead of encoding and decoding the entire hologram, just the part required to render the selected view is encoded and transmitted via the network based on the users’ interactivity. Four different strategies, namely, monolithic, single view, adaptive view, and non-real time streaming strategies are explained and compared in terms of bandwidth requirements, encoding time-complexity, and bitrate overhead. Experimental results show that the view-aware methods reduce the required bandwidth for holography streaming at the cost of a bitrate increase.

Keywords: Holography, compression, bitrate adaptation, dynamic adaptive streaming over HTTP, DASH.

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Philipp Moll

How Players Play Games: Observing the Influences of Game Mechanics

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Authors: Philipp Moll, Veit Frick, Natascha Rauscher, Mathias Lux (Alpen-Adria-Universität Klagenfurt)
Abstract: The popularity of computer games is remarkably high and is still growing. Despite the popularity and economical impact of games, data-driven research in game design, or to be more precise, in-game mechanics – game elements and rules defining how a game works – is still scarce. As data on user interaction in games is hard to get by, we propose a way to analyze players’ movement and action based on video streams of games. Utilizing this data we formulate four hypotheses focusing on player experience, enjoyment, and interaction patterns, as well as the interrelation thereof. Based on a user study for the popular game Fortnite, we discuss the interrelation between game mechanics, enjoyment of players, and different player skill levels in the observed data.
Keywords: Online Games; Game Mechanics; Game Design; Video Analysis
Links: International Workshop on Immersive Mixed and Virtual Environment Systems (MMVE)

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Hermann Hellwagner continues as TPC member of INFOCOM 2020

IEEE Communications Society extends its appreciation of Hermann Hellwagner as a distingguished member of the IEEE INFOCOM 2020.
See more Information here.
IEEE INFOCOM 2020 – Online Conference July 6-9, 2020

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Christian Timmerer

ICME’20: Multi-Period Per-Scene Optimization for HTTP Adaptive Streaming

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Authors: Venkata Phani Kumar M (Alpen-Adria-Universität Klagenfurt), Christian Timmerer (Alpen-Adria-Universität Klagenfurt, Bitmovin) and Hermann Hellwagner  (Alpen-Adria-Universität Klagenfurt)

Abstract: Video delivery over the Internet has become more and more established in recent years due to the widespread use of Dynamic Adaptive Streaming over HTTP (DASH). The current DASH specification defines a hierarchical data model for Media Presentation Descriptions (MPDs) in terms of periods, adaptation sets, representations and segments. Although multi-period MPDs are widely used in live streaming scenarios, they are not fully utilized in Video-on-Demand (VoD) HTTP adaptive streaming (HAS) scenarios. In this paper, we introduce MiPSO, a framework for Multi–Period per-Scene Optimization, to examine multiple periods in VoD HAS scenarios. MiPSO provides different encoded representations of a video at either (i) maximum possible quality or (ii) minimum possible bitrate, beneficial to both service providers and subscribers. In each period, the proposed framework adjusts the video representations (resolution-bitrate pairs) by taking into account the complexities of the video content, with the aim of achieving streams at either higher qualities or lower bitrates. The experimental evaluation with a test video data set shows that the MiPSO reduces the average bitrate of streams with the same visual quality by approximately 10% or increases the visual quality of streams by at least 1 dB in terms of Peak Signal-to-Noise (PSNR) at the same bitrate compared to conventional approaches to video content delivery.

Keywords: Adaptive Streaming, Video-on-Demand, Per-Scene Encoding, Media Presentation Description

IEEE International Conference on Multimedia and Expo. July 06 – 10, London, United Kingdom

Link:https://www.2020.ieeeicme.org/

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MMSys’20: Cloud-based Adaptive Video Streaming Evaluation Framework for the Automated Testing of Media Players (CAdViSE)

Authors: Babak Taraghi (Alpen-Adria-Universität Klagenfurt), Anatoliy Zabrovskiy (Alpen-Adria-Universität Klagenfurt), Christian Timmerer (Alpen-Adria-Universität Klagenfurt, Bitmovin) and Hermann Hellwagner (Alpen-Adria-Universität Klagenfurt)

Abstract: Attempting to cope with fluctuations of network conditions in terms of available bandwidth, latency and packet loss, and to deliver the highest quality of video (and audio) content to users, research on adaptive video streaming has attracted intense efforts from the research community and huge investments from technology giants. How successful these efforts and investments are, is a question that needs precise measurements of the results of those technological advancements. HTTP-based Adaptive Streaming (HAS) algorithms, which seek to improve video streaming over the Internet, introduce video bitrate adaptivity in a way that is scalable and efficient. However, how each HAS implementation takes into account the wide spectrum of variables and configuration options, brings a high complexity to the task of measuring the results and visualizing the statistics of the performance and quality of experience. In this paper, we introduce CAdViSE, our Cloud-based Adaptive Video Streaming Evaluation framework for the automated testing of adaptive media players. The paper aims to demonstrate a test environment which can be instantiated in a cloud infrastructure, examines multiple media players with different network attributes at defined points of the experiment time, and finally concludes the evaluation with visualized statistics and insights into the results.

Keywords: HTTP Adaptive Streaming, Media Players, MPEG-DASH, Network Emulation, Automated Testing, Quality of Experience

Link: ACM Multimedia Systems Conference 2020 (MMSys 2020)

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