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Paper accepted: Towards Low Latency Live Streaming: Challenges in a Real-World Deployment

The 13th ACM Multimedia Systems Conference (ACM MMSys 2022)

June 14–17, 2022 |  Athlone, Ireland

Conference Website

Reza Shokri Kalan (Digiturk Company, Istanbul), Reza Farahani (Alpen-Adria-Universität Klagenfurt), Emre Karsli (Digiturk Company, Istanbul), Christian Timmerer (Alpen-Adria-Universität Klagenfurt), and Hermann Hellwagner (Alpen-Adria-Universität Klagenfurt)

Over-the-Top (OTT) service providers need faster, cheaper, and Digital Rights Management (DRM)-capable video streaming solutions. Recently, HTTP Adaptive Streaming (HAS) has become the dominant video delivery technology over the Internet. In HAS, videos are split into short intervals called segments, and each segment is encoded at various qualities/bitrates (i.e., representations) to adapt to the available bandwidth. Utilizing different HAS-based technologies with various segment formats imposes extra cost, complexity, and latency to the video delivery system. Enabling an integrated format for transmitting and storing segments at Content Delivery Network (CDN) servers can alleviate the aforementioned issues. To this end, MPEG Common Media Application Format (CMAF) is presented as a standard format for cost-effective and low latency streaming. However, CMAF has not been adopted by video streaming providers yet and it is incompatible with most legacy end-user players. This paper reveals some useful steps for achieving low latency live video streaming that can be implemented for non-DRM sensitive contents before jumping to CMAF technology. We first design and instantiate our testbed in a real OTT provider environment, including a heterogeneous network and clients, and then investigate the impact of changing format, segment duration, and Digital Video Recording (DVR) window length on a real live event. The results illustrate that replacing the transport stream (.ts) format with fragmented MP4 (.fMP4) and shortening segments’ duration reduces live latency significantly.

 

 

 

 

 

 

 

 

Keywords: HAS, DASH, HLS, CMAF, Live Streaming, Low Latency

 

Hadi
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Workshop “IXR’22: Interactive eXtended Reality 2022”

colocated with ACM Multimedia 2022

October, 2022, Lisbon, Portugal

Workshop Chairs:

  • Irene Viola, CWI, Netherlands
  • Hadi Amirpour, Klagenfurt University, Austria
  • Asim Hameed, NTNU, Norway
  • Maria Torres Vega, Ghent University, Belgium

Topics of interest include, but are not limited to:

  • Novel low latency encoding techniques for interactive XR applications
  • Novel networking systems and protocols to enable interactive immersive applications. This includes optimizations ranging from hardware (i.e., millimeter-wave networks or optical wireless), physical and MAC layer up to the network, transport and application layers (such as over the top protocols);
  • Significative advances and optimization in 3D modeling pipelines for AR/VR visualization, accessible and inclusive GUI, interactive 3D models;
  • Compression and delivery strategies for immersive media contents, such as omnidirectional video, light fields, point clouds, dynamic and time varying meshes;
  • Quality of Experience management of interactive immersive media applications;
  • Novel rendering techniques to enhance interactivity of XR applications;
  • Application of interactive XR to different areas of society, such as health (i.e., virtual reality exposure therapy), industry (Industry 4.0), XR e-learning (according to new global aims);

Dates:

  • Submission deadline: 20 June 2022, 23:59 AoE
  • Notifications of acceptance: 29 July 2022
  • Camera ready submission: 21 August 2022
  • Workshop: 10th or 14th October
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Workshop “Artificial Intelligence for Live Video Streaming (ALIS 2022)”

ALIS’22: Artificial Intelligence for Live Video Streaming


colocated with ACM Multimedia 2022


October 2022, Lisbon, Portugal

Download ALIS’22 Poster/ CfP

 

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Horizon Europe project “Scalable Platform for Innovations on Real-time Immersive Telepresence” (SPIRIT) accepted

Project Lead: H. Hellwagner, Ch. Timmerer

Abstract: Immersive telepresence technologies will have game-changing impacts on interactions amongst individuals or with non-human objects (e.g. machines), in cyberspace with blurred boundaries between the virtual and physical world. The impacts of this technology are expected to range in a variety of vertical sectors, including education and training, entertainment, healthcare, manufacturing industry, etc. The key challenges include limitations of both the application platform and the underlying network support to achieve seamless presentation, processing, and delivery of immersive telepresence content at a large scale. Innovative design, rigorous validation, and testing exercises aim to fulfill the key technical requirements identified such as low-latency communication, high bandwidth demand, and complex content encoding/rendering tasks in real-time. The industry-leading SPIRIT consortium will build on the existing TRL4 application platforms and network infrastructures developed by the project partners, aiming to address key technical challenges and further develop all major aspects of telepresence technologies to achieve targeted TRL7. The SPIRIT Project will focus its innovations in network-layer, transport-layer, application/content-layer techniques, as well as security and privacy mechanisms to facilitate the large-scale operation of telepresence applications. The project team will develop a fully distributed, interconnected testing infrastructure across two geographical sites in Germany and UK, allowing large-scale testing of heterogeneous telepresence applications in real-life Internet environments. The network infrastructure will host two mainstream application
environments based on WebRTC and low-latency DASH. In addition to the project-designated use case scenarios, the project team will test a variety of additional use cases covering heterogeneous vertical sectors through FSTP participation.

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Paper accepted: Take the Red Pill for H3 and See How Deep the Rabbit Hole Goes

ACM Mile-High video 2022 (MHV)

March 01-03, 2022 | Denver, CO, USA

Conference Website

Authors: Minh Nguyen (Christian Doppler Laboratory ATHENA, Alpen-Adria-Universität Klagenfurt, Austria), Christian Timmerer (Christian Doppler Laboratory ATHENA, Alpen-Adria-Universität Klagenfurt, Austria), Stefan Pham (Fraunhofer FOKUS, Germany), Daniel Silhavy (Fraunhofer FOKUS, Germany), Ali C. Begen (Ozyegin University, Turkey)

Abstract: With the introduction of HTTP/3 (H3) and QUIC at its core, there is an expectation of significant improvements in Web-based secure object delivery. As HTTP is a central protocol to the current adaptive streaming methods in all major over-the-top (OTT) services, an important question is what H3 will bring to the table for such services. To answer this question, we present the new features of H3 and QUIC, and compare them to those of H/1.1/2 and TCP. We also share the latest research findings in this domain.

Keywords: HTTP adaptive streaming, QUIC, CDN, ABR, OTT, DASH, HLS.

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MPEG DASH video streaming technology co-developed in Klagenfurt wins Technology & Engineering Emmy® Award

The Emmy® Awards do not only honour the work of actors and directors, but they also recognise technologies that are steadily improving the viewing experience for consumers. This year, the winners include the MPEG DASH Standard. Christian Timmerer (Department of Information Technology) played a leading role in its development. Read more about it here.

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Paper accepted: Super-resolution Based Bitrate Adaptation for HTTP Adaptive Streaming for Mobile Devices

ACM Mile-High video 2022 (MHV)

March 01-03, 2022 | Denver, CO, USA

Conference Website

Minh Nguyen (Christian Doppler Laboratory ATHENA, Alpen-Adria-Universität Klagenfurt), Ekrem Çetinkaya (Christian Doppler Laboratory ATHENA, Alpen-Adria-Universität Klagenfurt), Hermann Hellwagner (Christian Doppler Laboratory ATHENA, Alpen-Adria-Universität Klagenfurt), and Christian Timmerer (Christian Doppler Laboratory ATHENA, Alpen-Adria-Universität Klagenfurt)

Abstract: The advancement of mobile hardware in recent years made it possible to apply deep neural network (DNN) based approaches on mobile devices. This paper introduces a lightweight super-resolution (SR) network, namely SR-ABR Net, deployed at mobile devices to upgrade low-resolution/low-quality videos and a novel adaptive bitrate (ABR) algorithm, namely WISH-SR, that leverages SR networks at the client to improve the video quality depending on the client’s context. WISH-SR takes into account mobile device properties, video characteristics, and user preferences. Experimental results show that the proposed SR-ABR Net can improve the video quality compared to traditional SR approaches while running in real-time. Moreover, the proposed WISH-SR can significantly boost the visual quality of the delivered content while reducing both bandwidth consumption and the number of stalling events.

Keywords: Super-resolution, Deep Neural Networks, Mobile Devices, ABR

Hadi
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Hadi Amirpour has successfully defended his PhD thesis

On Tuesday the 25th of January 2022, Hadi Amirpour successfully defended his Ph.D. thesis under supervision of Assoc.-Prof. DI Dr. Christian Timmerer and Assoc.-Prof. Dr. Klaus Schöffmann. The defense was chaired by Assoc.-Prof. DI Dr. Mathias Lux and the examiners were Emeritus Prof. Dr. Mohammad Ghanbari (University of Essex, UK) and Univ.-Prof. DI Dr. Hermann Hellwagner (University of Klagenfurt).

We are pleased to congratulate Dr. Hadi Amirpour on passing his Ph.D. exam!

Dragi Kimovski
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Paper accepted in the IEEE Computer Magazine: Decentralized Machine Learning for Intelligent Health Care Systems on the Computing Continuum

Title: Decentralized Machine Learning for Intelligent Health Care Systems on the Computing Continuum

Authors: Dragi Kimovski, Sasko Ristov, Radu Prodan

Abstract: The introduction of electronic personal health records (EHR) enables nationwide information exchange and curation among different health care systems. However, the current EHR systems do not provide transparent means for diagnosis support, medical research, or can utilize the omnipresent data produced by the personal medical devices. Besides, the EHR systems are centrally orchestrated, which could potentially lead to a single point of failure. Therefore, in this article, we explore novel approaches for decentralizing machine learning over distributed ledgers to create intelligent EHR systems that can utilize information from personal medical devices for improved knowledge extraction. Consequently, we proposed and evaluated a conceptual EHR to enable anonymous predictive analysis across multiple medical institutions. The evaluation results indicate that the decentralized EHR can be deployed over the computing continuum with reduced machine learning time of up to 60% and consensus latency of below 8 seconds.

5th Klagenfurt Winter Game Jam was a big success!

The 5th Klagenfurt Winter Game Jam took place as a hybrid event on Dec 17-19, 2021. Over 100 participants teamed up over the weekend to create altogether 26 games on the topic of “What’s in the box?”.

The games can be found and played at https://itch.io/jam/5th-winter-game-jam.