Multimedia Communication

, ,

Paper accepted MMM’21: Towards Optimal Multirate Encoding for HTTP Adaptive Streaming

Authors: Hadi Amirpour (Alpen-Adria-Universität Klagenfurt),Ekrem Çetinkaya (Alpen-Adria-Universität Klagenfurt), Christian Timmerer (Alpen-Adria-Universität Klagenfurt, Bitmovin), and Mohammad Ghanbari (School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK)

Abstract: HTTP Adaptive Streaming (HAS) enables high quality stream-ing of video contents. In HAS, videos are divided into short intervalscalled segments, and each segment is encoded at various quality/bitratesto adapt to the available bandwidth. Multiple encodings of the same con-tent imposes high cost for video content providers. To reduce the time-complexity of encoding multiple representations, state-of-the-art methods typically encode the highest quality representation first and reusethe information gathered during its encoding to accelerate the encodingof the remaining representations. As encoding the highest quality rep-resentation requires the highest time-complexity compared to the lowerquality representations, it would be a bottleneck in parallel encoding scenarios and the overall time-complexity will be limited to the time-complexity of the highest quality representation. In this paper and toaddress this problem, we consider all representations from the highestto the lowest quality representation as a potential, single reference toaccelerate the encoding of the other, dependent representations. We for-mulate a set of encoding modes and assess their performance in terms ofBD-Rate and time-complexity, using both VMAF and PSNR as objec-tive metrics. Experimental results show that encoding a middle qualityrepresentation as a reference, can significantly reduce the maximum en-coding complexity and hence it is an efficient way of encoding multiplerepresentations in parallel. Based on this fact, a fast multirate encodingmethod is proposed which utilizes depth and prediction mode of a middle quality representation to accelerate the encoding of the dependentrepresentations.

The International MultiMedia Modeling Conference (MMM)

25-27 January 2021, Prague, Czech Republic

Link: https://mmm2021.cz

Keywords: HEVC, Video Encoding , Multirate Encoding , DASH

,

Paper accepted ISM’20: Dynamic Segment Repackaging at the Edge for HTTP Adaptive Streaming

Authors: Jesús Aguilar Armijo (Alpen-Adria-Universität Klagenfurt), Babak Taraghi (Alpen-Adria-Universität Klagenfurt), Christian Timmerer (Alpen-Adria-Universität Klagenfurt, Bitmovin), and Hermann Hellwagner (Alpen-Adria-Universität Klagenfurt)

Abstract: Adaptive video streaming systems typically support different media delivery formats, e.g., MPEG-DASH and HLS, replicating the same content multiple times into the network. Such a diversified system results in inefficient use of storage, caching, and bandwidth resources. The Common Media Application Format (CMAF) emerges to simplify HTTP Adaptive Streaming (HAS), providing a single encoding and packaging
format of segmented media content and offering the opportunities of bandwidth savings, more cache hits and less storage needed. However, CMAF is not yet supported by most devices. To solve this issue, we present a solution where we maintain the main
advantages of CMAF while supporting heterogeneous devices using different media delivery formats. For that purpose, we propose to dynamically convert the content from CMAF to the desired media delivery format at an edge node. We study the bandwidth savings with our proposed approach using an analytical model and simulation, resulting in bandwidth savings of up to 20% with different media delivery format distributions.
We analyze the runtime impact of the required operations on the segmented content performed in two scenarios: the classic one, with four different media delivery formats, and the proposed scenario, using CMAF-only delivery through the network. We
compare both scenarios with different edge compute power assumptions. Finally, we perform experiments in a real video streaming testbed delivering MPEG-DASH using CMAF content to serve a DASH and an HLS client, performing the media conversion for the latter one.

IEEE International Symposium on Multimedia (ISM)

2-4 December 2020, Naples, Italy

https://www.ieee-ism.org/

Keywords: CMAF, Edge Computing, HTTP Adaptive Streaming (HAS)

,

PCS´21 Special Session: Video encoding for large scale HAS deployments

Abstract: Video accounts for the vast majority of today’s internet traffic and video coding is vital for efficient distribution towards the end-user. Software- or/and cloud-based video coding is becoming more and more attractive, specifically with the plethora of video codecs available right now (e.g., AVC, HEVC, VVC, VP9, AV1, etc.) which is also supported by the latest Bitmovin Video Developer Report 2020. Thus, improvements in video coding enabling efficient adaptive video streaming is a requirement for current and future video services. HTTP Adaptive Streaming (HAS) is now mainstream due to its simplicity, reliability, and standard support (e.g., MPEG-DASH). For HAS, the video is usually encoded in multiple versions (i.e., representations) of different resolutions, bitrates, codecs, etc. and each representation is divided into chunks (i.e., segments) of equal length (e.g., 2-10 sec) to enable dynamic, adaptive switching during streaming based on the user’s context conditions (e.g., network conditions, device characteristics, user preferences). In this context, most scientific papers in the literature target various improvements which are evaluated based on open, standard test sequences. We argue that optimizing video encoding for large scale HAS deployments is the next step in order to improve the Quality of Experience (QoE), while optimizing costs.

Session organizers: Christian Timmerer (Bitmovin, Austria), Mohammad Ghanbari (University of Essex, UK), and Alex Giladi (Comcast, USA).

Picture Coding Symposium (PCS)  at 29 June to 2 July 2021, UK

Link: https://pcs2021.org

Christian Timmerer
,

IEEE Communication Magazine: From Capturing to Rendering: Volumetric Media Delivery With Six Degrees of Freedom

Teaser: “Help me, Obi-Wan Kenobi. You’re my only hope,” said the hologram of Princess Leia in Star Wars: Episode IV – A New Hope (1977). This was the first time in cinematic history that the concept of holographic-type communication was illustrated. Almost five decades later, technological advancements are quickly moving this type of communication from science fiction to reality.

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

Abstract: Technological improvements are rapidly advancing holographic-type content distribution. Significant research efforts have been made to meet the low-latency and high-bandwidth requirements set forward by interactive applications such as remote surgery and virtual reality. Recent research made six degrees of freedom (6DoF) for immersive media possible, where users may both move their heads and change their position within a scene. In this article, we present the status and challenges of 6DoF applications based on volumetric media, focusing on the key aspects required to deliver such services. Furthermore, we present results from a subjective study to highlight relevant directions for future research.

Link: IEEE Communication Magazine

, ,

Paper accepted: Automated Bank Cheque Verification Using Image Processing and Deep Learning Methods

Authors: Prateek Agrawal (University of Klagenfurt, Austria), Deepak Chaudhary (Lovely Professional University, India), Vishu Madaan (Lovely professional University, India), Anatoliy Zabrovskiy (University of Klagenfurt, Austria), Radu Prodan (University of Klagenfurt, Austria), Dragi Kimovski (University of Klagenfurt, Austria), Christian Timmerer (University of Klagenfurt, Austria)

Abstract: Automated bank cheque verification using image processing is an attempt to complement the present cheque truncation system, as well as to provide an alternate methodology for the processing of bank cheques with minimal human intervention. When it comes to the clearance of the bank cheques and monetary transactions, this should not only be reliable and robust but also save time which is one of the major factor for the countries having large population. Read more

,

Paper accepted VCIP’20: Fast Multirate Encoding for HTTP Adaptive Streaming Using Machine Learning

Authors: Ekrem Çetinkaya (Alpen-Adria-Universität Klagenfurt), Hadi Amirpour (Alpen-Adria-Universität Klagenfurt), Christian Timmerer (Alpen-Adria-Universität Klagenfurt, Bitmovin), and Mohammad Ghanbari (School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK)

Abstract: HTTP Adaptive Streaming (HAS) is the most common approach for delivering video content over the Internet. The requirement to encode the same content at different quality levels (i.e., representations) in HAS is a challenging problem for content providers. Fast multirate encoding approaches try to accelerate this process by reusing information from previously encoded representations. In this paper, we use convolutional neural networks (CNNs) to speed up the encoding of multiple representations with a specific focus on parallel encoding. In parallel encoding, the overall time-complexity is limited to the maximum time-complexity of one of the representations that are encoded in parallel. Therefore, instead of reducing the time-complexity for all representations, the highest time-complexities are reduced. Experimental results show that the proposed method achieves significant time-complexity savings in parallel encoding scenarios (41%) with a slight increase in bitrate and quality degradation compared to the HEVC reference software.

Keywords: Video Coding, Convolutional Neural Networks, HEVC, HTTP Adaptive Streaming (HAS)

Christian Timmerer
,

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

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

,

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

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.

,

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

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

Christian Timmerer
,

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

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/