ATHENA Christian Doppler (CD) Laboratory

2020 Twelfth International Conference on Quality of Multimedia Experience (QoMEX)

26 – 28 May 2020 | Athlone, Ireland

Conference website

[PDF][Slides][Video]

Jeroen van der Hooft (Ghent University), Maria Torres Vega (Ghent University), Christian Timmerer (AAU, Austria), Ali C. Begen (Ozyegin University, Networked Media), Filip De Turck (Ghent University), Raimund Schatz (AAU & AIT Austrian Institute of Technology, Austria)
*** Best Paper Award ***

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 today. 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.

ACM Transactions on Multimedia Computing, Communications, and Applications (ACM TOMM)

Journal website

[PDF]

Abdelhak Bentaleb (National University of Singapore), Christian Timmerer (AAU, Austria), Ali C. Begen (Ozyegin University, Networked Media), Roger Zimmermann (National University of Singapore)

HTTP adaptive streaming with chunked transfer encoding can offer low-latency streaming without sacrificing the coding efficiency. This allows media segments to be delivered while still being packaged. However, conventional schemes often make widely inaccurate bandwidth measurements due to the presence of idle periods between the chunks and hence this is causing sub-optimal adaptation decisions. To address this issue, we earlier proposed ACTE (ABR for Chunked Transfer Encoding) [6], a bandwidth prediction scheme for low-latency chunked streaming. While ACTE was a significant step forward, in this study we focus on two still remaining open areas, namely, (i) quantifying the impact of encoding parameters, including chunk and segment durations, bitrate levels, minimum interval between IDR-frames and frame rate on ACTE, and (ii) exploring the impact of video content complexity on ACTE. We thoroughly investigate these questions and report on our findings. We also discuss some additional issues that arise in the context of pursuing very low latency HTTP video streaming.

Hadi Amirpour has been awarded the Best Engagement Award at ACM MMSys 2020.

This year’s ACM MMSys was held as a fully virtual/online event and Slido was used for asking questions about keynotes and presentations including offline discussions with presenters. The interaction report provides some interesting key insights including the word cloud below which provides an overview of this year’s discussion items.

Although ACM MMSys 2020 is over, everyone is welcome joining the MMSys Slack workspace where the discussion will continue until ACM MMSys 2021 (available soon!) and hopefully beyond.

Proceedings of the 25th ACM Workshop on Packet Video (PV’20)

June 10 – 11, 2020 | Istanbul, Turkey

Conference website

[PDF][Slides][Video]

Minh Nguyen (AAU, Austria), Christian Timmerer (AAU, Austria), Hermann Hellwagner (AAU, Austria)

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%

ACM SIGCOMM 2020 Workshop on Evolution, Performance, and Interoperability of QUIC (EPIQ 2020)
August 10–14, 2020

[PDF][Slides][Video]

Minh Nguyen (Alpen-Adria-Universität Klagenfurt), Hadi Amirpour (Alpen-Adria-Universität Klagenfurt), Christian Timmerer (Alpen-Adria-Universität Klagenfurt), 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

2020 Twelfth InterProceedings of the 11th ACM Multimedia Systems Conference (MMSys ’20)

June 8 – 11, 2020 | Istanbul, Turkey

Conference website

[PDF][Slides][Video]

Babak Taraghi (AAU, Austria), Anatoliy Zabrovskiy (AAU, Austria), Christian Timmerer (AAU, Austria) and Hermann Hellwagner (AAU, Austria)

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.

Packet Video Workshop 2020 (PV)

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

[PDF][Slides][Video]

Minh Nguyen (Alpen-Adria-Universität Klagenfurt), Christian Timmerer (Alpen-Adria-Universität Klagenfurt), 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