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Journal article accepted: ACM TOMM: HTTP Adaptive Streaming: A Review on Current Advances and Future Challenges

ACM Transactions on Multimedia Computing, Communications, and Applications

 

Christian Timmerer (AAU, AT), Hadi Amirpour (AAU, AT), Farzad Tashtarian (AAU, AT), Samira Afzal (AAU, AT), Amr Rizk (Leibniz University Hannover, DE), Michael Zink (University of Massachusetts Amherst, US), and Hermann Hellwagner (AAU, AT)

Abstract: Video streaming has evolved from push-based, broad-/multicasting approaches with dedicated hard-/software infrastructures to pull-based unicast schemes utilizing existing Web-based infrastructure to allow for better scalability. In this article, we provide an overview of the foundational principles of HTTP adaptive streaming (HAS), from video encoding to end user consumption, while focusing on the key advancements in adaptive bitrate algorithms, quality of experience (QoE), and energy efficiency. Furthermore, the article highlights the ongoing challenges of optimizing network infrastructure, minimizing latency, and managing the environmental impact of video streaming. Finally, future directions for HAS, including immersive media streaming and neural network-based video codecs, are discussed, positioning HAS at the forefront of next-generation video delivery technologies.

Keywords: HTTP Adaptive Streaming, HAS, DASH, Video Coding, Video Delivery, Video Consumption, Quality of Experience, QoE

 

https://athena.itec.aau.at/2025/03/acm-tomm-http-adaptive-streaming-a-review-on-current-advances-and-future-challenges/

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DORBINE project @ Der Standard

Farzad recently participated in an interview with the Austrian newspaper Der Standard. The conversation covered a range of topics, and the final article has now been published. You can find the full piece at the following link:

https://www.derstandard.at/story/3000000262214/forscher-aus-klagenfurt-inspizieren-windraeder-mit-drohnenschwaermen

 

 

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SPIRIT (EU project) has successfully completed its periodic review!

Title: Project “Scalable Platform for Innovations on Real-time Immersive Telepresence” (SPIRIT) successfully passed periodic review

The “Scalable Platform for Innovations on Real-time Immersive Telepresence” (SPIRIT) project, a Horizon Europe innovation initiative uniting seven consortium partners, including ITEC from the University of Klagenfurt, has successfully completed its periodic review that took place in November 2024.

SPIRIT aims to develop a “multi-site, interconnected framework dedicated for supporting the operation of heterogeneous collaborative telepresence applications at large scale”.

ITEC focuses on three key areas in SPIRIT:

  • determining subjective and objective metrics for the Quality of Experience (QoE) of volumetric video,
  • developing a Live Low Latency DASH (Dynamic Adaptive Streaming over HTTP) system for the transmission of volumetric video, and
  • contributing to standardisation bodies regarding work done in volumetric video.

The review committee was satisfied with the project’s progress, and accepted all deliverables. The project was praised for a successful first round of open calls, which saw a remarkable 61 applicants for 11 available spots.

ITEC’s work with researching QoE of volumetric video through subjective testing was also deemed impressive, with us having obtained over 2000 data points across two rounds of testing. Contributions to standardisation bodies such as MPEG and 3GPP were also praised.

ITEC continues to work in the SPIRIT project, focusing on the second round of open calls and Live Low Latency DASH transmission of volumetric video.

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Project DORBINE accepted

DORBINE is a cooperative project between AIR6 Systems and Alpen-Adria-Universität Klagenfurt (AAU) (Farzad Tashtarian, project leader; Christian Timmerer and Hamid Amirpourazarian) and is funded by the Austrian Research Promotion Agency FFG.

Project description: Renewable energy plays a critical role in the global transition to sustainable and environmentally friendly power sources, and among the various technologies, turbines stand out as a key contributor. Wind turbines, for example, can convert up to 45% of the available wind energy into electricity, with modern designs reaching efficiencies as high as 50%, depending on conditions. The DORBINE project aims to enhance wind turbine efficiency in electricity production by developing an innovative inspection framework powered by cutting-edge AI techniques. It leverages a swarm of drones equipped with high-resolution cameras and advanced sensors to perform real-time, detailed blade inspections without the need for turbine shutdowns.

 

The Graph-Massivizer project team is looking forward to growing the community in 2025!

The Graph-Massivizer Project is glad to announce that their research expands beyond the European borders. The website receives continuous visits from colleagues from US, Canada, China…and the project team is happy to develop connections with top researchers in #graphprocessing wherever they are.

In such context, Radu Prodan presented Graph-Massivizer Project at the Indian Institute of Science (IISc) in #Bangalore, at the invitation of Prof. Yogesh Simmhan.

 

 

Hadi
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Paper accepted: MVCD: Multi-Dimensional Video Compression Dataset

Authors: Hadi Amirpour (AAU, Austria), Mohammad Ghasempour (AAU, Austria), Farzad Tashtarian (AAU, Austria), Ahmed Telili (TII, UAE), Samira Afzal (AAU, Austria), Wassim Hamidouche (INSA, France), Christian Timmerer (AAU, Austria)

Conference: IEEE Visual Communications and Image Processing (IEEE VCIP 2024) – Tokyo, Japan, December 8-11, 2024

Abstract: In the field of video streaming, the optimization of video encoding and decoding processes is crucial for delivering high-quality video content. Given the growing concern about carbon dioxide emissions, it is equally necessary to consider the energy consumption associated with video streaming. Therefore, to take advantage of machine learning techniques for optimizing video delivery, a dataset encompassing the energy consumption of the encoding and decoding process is needed. This paper introduces a comprehensive dataset featuring diverse video content, encoded and decoded using various codecs and spanning different devices. The dataset includes 1000 videos encoded with four resolutions (2160p, 1080p, 720p, and 540p) at two frame rates (30 fps and 60 fps), resulting in eight unique encodings for each video. Each video is further encoded with four different codecs — AVC (libx264), HEVC (libx265), AV1 (libsvtav1), and VVC (VVenC) — at four quality levels defined by QPs of 22, 27, 32, and 37. In addition, for AV1, three additional QPs of 35, 46, and 55 are considered. We measure both encoding and decoding time and energy consumption on various devices to provide a comprehensive evaluation, employing various metrics and tools. Additionally, we assess encoding bitrate and quality using quality metrics such as PSNR, SSIM, MS-SSIM, and VMAF. All data and the reproduction commands and scripts have been made publicly available as part of the dataset, which can be used for various applications such as rate and quality control, resource allocation, and energy-efficient streaming.

Dataset URL: https://github.com/cd-athena/MVCD

Index Terms— Video encoding, decoding, energy, complexity, quality.

Hadi
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Paper accepted: Characterizing the Geometric Complexity of G-PCC Compressed Point Clouds

Authors: Annalisa Gallina (UNIPD, Italy), Hadi Amirpour (AAU, Austria), Sara Baldoni (UNIPD, Italy), Giuseppe Valenzise (UPSaclay, France), Federica Battisti (UNIPD, Italy).

Conference: IEEE Visual Communications and Image Processing (IEEE VCIP 2024) – Tokyo, Japan, December 8-11, 2024

Abstract: Measuring the complexity of visual content is crucial in various applications, such as selecting sources to test processing algorithms, designing subjective studies, and efficiently determining the appropriate encoding parameters and bandwidth allocation for streaming. While spatial and temporal complexity measures exist for 2D videos, a geometric complexity measure for 3D content is still lacking. In this paper, we present the first study to characterize the geometric complexity of 3D point clouds. Inspired by existing complexity measures, we propose several compression-based definitions of geometric complexity derived from the rate-distortion curves obtained by compressing a dataset of point clouds using G-PCC. Additionally, we introduce density-based and geometry-based descriptors to predict complexity. Our initial results show that even simple density measures can accurately predict the geometric complexity of point clouds.

Index Terms— Point cloud, complexity, compression, G-PCC.

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Haleh @ First International Workshop on Scaling Knowledge Graphs for Industry” in Conference “Semantics 24: 20th International Conference on Semantic Systems”

Haleh gave a presentation at the first International Workshop on Scaling Knowledge Graphs for Industry (co-located with the 20th International Conference on Semantic Systems – SEMANTICS 2024)  – in Amsterdam, Sept. 17-19, 2024.

Title: “Modeling and Generating Extreme Volumes of Financial Synthetic Time-Series Data with Knowledge Graphs”

Authors: Laurentiu Vasiliu, S. Haleh S. Dizaji , Aaron Eberhart, Dumitru Roman and Radu Prodan

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CERCIRAS Summer School @ AAU – 25.-30.08.2024

CERCIRAS (CA19135), short for Connecting Education and Research Communities for an Innovative Resource Aware Society is a 4-year long COST Action, started at the end of September 2020 and now nearing completion. One of the highlights of CERCIRAS has been its yearly Training School, a week-long residential school designed for current and future PhD students with research interests falling within the thematic scope of the Action and open to other profiles, including industry professionals. While perturbed by unfortunate overlap with the outbreak of the COVID pandemic, CERCIRAS managed to execute three consecutive Training Schools successfully: mid-September 2022 in Split (HR); early September 2023 in Riga (LV); and late August 2024 in Klagenfurt (AT). All editions of the CERCIRAS Training School follow a common structure: 4 selected lecture topics, which alternate frontal lessons and assisted hands-on works; 25 to 35 participants from as many participating countries as possible, with rich diversity for provenance, seniority level, and research focus; a rich portfolio of social activities.

The Training School places a considerable burden on the local hosts, which includes securing comfortable and affordable accommodation for a large troop, providing a modern and spacious lecture hall for all lectures and labs, with refreshments for the two daily breaks and nearby canteens for lunch, and arranging exciting options for a whole-afternoon diversion.

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6G Continuum Kick-Off Meeting and Research Collaboration

Dragi Kimovski recently visited Mother Theresa University in Skopje as part of the OeAD 6G Continuum project, which focuses on developing middleware for Artificial Intelligence over 6G networks. This visit is the next step in the collaboration between the involved institutions. During the stay, the kick-off meeting for the 6G Continuum project took place, bringing together researchers from both institutions to discuss the project’s goals and clarify the the research activities in terms of supporting AI traning and inference in the Edge over 6G networks. In addition to the research focus, this visit also helped to strengthen the ongoing partnership between the institutions. They explored new opportunities for collaboration in teaching and research, including student and faculty exchanges through Erasmus and CEEPUS programs.