Hadi Amirpour to give a talk at INSA France

LiVE: Toward Better Live Video Experience

INSA, France

 27th September 2022 | Rennes, France

 

Abstract: In this presentation, we first introduce the principles of video streaming and the existing challenges. While live video streaming is expected to continue growing at an accelerated pace, one potential area for optimization that has remained relatively untapped is the use of content-aware encoding to improve the quality of live contribution streams due to avoid of latency. In this talk, we introduce revolutionary real-time content-aware video quality improvement methods for live applications that keep the added latency very low.

 

Hadi Amirpour is a postdoctoral researcher at the University of Klagenfurt. He received his B.Sc. degrees in Electrical and Biomedical Engineering, and he pursued his M.Sc. in Electrical Engineering. He got his Ph.D. in computer science from the University of Klagenfurt in 2022. He was involved in the project EmergIMG, a Portuguese consortium on emerging imaging technologies, funded by the Portuguese funding agency and H2020. Currently, he is working on the ATHENA project in cooperation with its industry partner Bitmovin. His research interests are image processing and compression, video processing and compression, quality of assessment, emerging 3D imaging technology, and medical image analysis.

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CADLAD: Device-aware Bitrate Ladder Construction for HTTP Adaptive Streaming

18th International Conference on Network and Service Management (CNSM 2022)

31 October – 4 November, 2022 | Thessaloniki, Greece

[PDF][Slides]

Minh Nguyen (AAU, Austria), Babak Taraghi (AAU, Austria), Abdelhak Bentaleb (National University of Singapore, Singapore), Roger Zimmermann (National University of Singapore, Singapore), and Christian Timmerer (AAU, Austria)

Abstract: Considering network conditions, video content, and viewer device type/screen resolution to construct a bitrate ladder is necessary to deliver the best Quality of Experience (QoE). A large-screen device like a TV needs a high bitrate with high resolution to provide good visual quality, whereas a small one like a phone requires a low bitrate with low resolution. In addition, encoding high-quality levels at the server side while the network is unable to deliver them causes unnecessary cost for the content provider. Recently, the Common Media Client Data (CMCD) standard has been proposed, which defines the data that is collected at the client and sent to the server with its HTTP requests. This data is useful in log analysis, quality of service/experience monitoring and delivery improvements.

cadlad

In this paper, we introduce a CMCD-Aware per-Device bitrate LADder construction (CADLAD) that leverages CMCD to address the above issues. CADLAD comprises components at both client and server sides. The client calculates the top bitrate (tb) — a CMCD parameter to indicate the highest bitrate that can be rendered at the client — and sends it to the server together with its device type and screen resolution. The server decides on a suitable bitrate ladder, whose maximum bitrate and resolution are based on CMCD parameters, to the client device with the purpose of providing maximum QoE while minimizing delivered data. CADLAD has two versions to work in Video on
Demand (VoD) and live streaming scenarios. Our CADLAD is client agnostic; hence, it can work with any players and ABR algorithms at the client. The experimental results show that CADLAD is able to increase the QoE by 2.6x while saving 71% of delivered data, compared to an existing bitrate ladder of an available video dataset. We implement our idea within CAdViSE — an open-source testbed for reproducibility.

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Video Coding Enhancements for HTTP Adaptive Streaming

ACM Multimedia Conference – Doctoral Symposium Track

Lisbon, Portugal | 10-14 October 2022

[PDF][Video][Slides]

Vignesh V Menon (Christian Doppler Laboratory ATHENA, Alpen-Adria-Universität Klagenfurt)

Abstract: Rapid growth in multimedia streaming traffic over the Internet motivates the research and further investigation of the video coding performance of such services in terms of speed and Quality of Experience (QoE). HTTP Adaptive Streaming (HAS) is today’s de-facto standard to deliver clients the highest possible video quality. In HAS, the same video content is encoded at multiple bitrates, resolutions, framerates, and coding formats called representations. This study aims to (i) provide fast and compression-efficient multi-bitrate, multi-resolution representations, (ii) provide fast and compression-efficient multi-codec representations, (iii) improve the encoding efficiency of Video on Demand (VoD) streaming using content-adaptive encoding optimizations, and (iv) provide encoding schemes with optimizations per-title for live streaming applications to decrease the storage or delivery costs or/and increase QoE.

The ideal video compression system for HAS envisioned in this doctoral study.

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Doctoral Student Positions @ ATHENA

The Institute of Information Technology at the
Alpen-Adria-Universität Klagenfurt
invites applications for:

Doctoral Student Positions (100% employment; all genders welcome)

within the Christian Doppler (CD) Pilot Laboratory ATHENA

Adaptive Streaming over HTTP and
Emerging Networked Multimedia Services

The expected start date of employment is April 1st, 2023.
Application deadline: December 1st, 2022.

Find the complete job description here.
Come and join our ATHENA team!

 

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Secure Reversible Data Hiding in Encrypted Images based on Classification Encryption Difference

IEEE 24th Workshop on MultiMedia Signal Processing (MMSP)

September 26-28, 2022 | Shanghai, China

[PDF]

Lingfeng Qu (Southwest Jiaotong University),  Hadi Amirpour (Alpen-Adria-Universität Klagenfurt),   Mohammad Ghanbari (University of Essex, UK)and Christian Timmerer (Alpen-Adria-Universität Klagenfurt), Hongjie He (Southwest Jiaotong University)

Abstract: This paper introduces an algorithm to improve the security, efficiency, and
embedding capacity of reversible data hiding in encrypted images (RDH-EI). It is based on
classification encryption difference and adaptive fixed-length coding. Firstly, the prediction error image is obtained, the difference with a bin value greater than the encryption threshold in the difference histogram is found, and it is further modified to obtain the embedding threshold range. Then, under the condition of ensuring that the difference inside and outside the threshold range is not confused, the difference within the threshold is only scrambled, and the difference outside the threshold is scrambled and mod encrypted. After obtaining the encrypted image, an adaptive difference fixed-length coding method is proposed to encode and compress the differences within the threshold. The secret data is embedded in the multiple most significant bits of the encoded difference. Experimental results show that the embedding capacity of the proposed algorithm is improved compared with the state-of-the-art algorithm.

 

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Segment Prefetching at the Edge for Adaptive Video Streaming

The Fourteen International Workshop on Selected Topics in Wireless and Mobile computing (STWiMob 2022)

October 10-12, 2022 | Thessaloniki, Greece

Conference Website

[PDF]

Jesús Aguilar Armijo (Alpen-Adria-Universität Klagenfurt), Christian Timmerer (Alpen-Adria-Universität Klagenfurt) and Hermann Hellwagner (Alpen-Adria-Universität Klagenfurt)

Abstract: Segment prefetching is a technique that consists of sending the next segment(s) in advance closer to the user to serve content with reduced latency. Due to its location and capabilities, an edge computing node is an ideal component for executing
segment prefetching policies and storing/caching the prefetched segments. In this work, we study segment prefetching techniques deployed at the edge computing node for adaptive video streaming. We propose different types of segment prefetching policies
and study their costs and benefits, including segment prefetching based on past segment requests, transrating, a Markov prediction model, and machine learning. Besides, we analyze which segment prefetching policy is better under which circumstances, and the
influence of the ABR algorithm and the bitrate ladder on segment prefetching.

Keywords: Edge computing, MEC, content delivery, adaptive video streaming, HAS, segment prefetching

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Interns at ATHENA (Summer 2022)

In July-August 2022, the ATHENA Christian Doppler Laboratory hosted four interns working on the following topics:

  • Fabio Zinner: A Study and Evaluation on HTTP Adaptive Video Streaming using Mininet
  • Moritz Pecher: Dataset Creation and HAS Basics
  • Per-Luca Thalmann: Codec-war: is it necessary? Welcome to the multi-codec world
  • Georg Kelih: Server Client Simulator for QoE with practical Implementation

At the end of their internships, they presented their works and achieved results, and received official certificates from the university. We believe the joint work with them was beneficial for both the laboratory and the interns. We would like to thank the interns for their genuine interest, productive work, and excellent feedback about our laboratory.

Fabio Zinner: my four weeks, I had an amazingly practical and theoretical experience which is very important for my future practical and academic line of work! It was great and fascinating working with Python, Mininet, Linux, FFMpeg, Gpac, Iperf, etc. I really liked working with ATHENA, and the experience I gathered was exceptional. Also, I am very happy that I had Reza Farahani as my supervisor!

Per-Luca Thalmann:I really enjoyed my 4 weeks at ATHENA. At first, I had to read a lot of articles and papers to get a basic understanding of Video Codecs and encoding. As I started my Main Project, which evaluated the performance of modern codecs with different video complexities, I noticed that everything I had read before was useful to progress faster towards my end goal. After I got the results of my script, which ran for over a week, I also noticed some outcomes which were not expected. Basically, that an older codecs get at some very specific settings higher Scores than his successor. Whenever I got stuck or had any questions, my supervisor, Vignesh, helped me. I did not only improve my technical knowledge, I also got a lot insights into how research works, what is the motivation of research and also about the process for scientific research.

Georg Kelih:I worked by Athena as an Intern for a month and got the tasks to build a simulator which simulates the server client communication (ABR, bitrate ladder, resource allocation) and shows the results in a graph and a Server Client script where the server runs on the local host and the client requests segments and plays them using python-vlc
My daily routine was pretty chill, not only because we had only 30 hours to work, but also the programming was quite fun and challenging. So my day looked something like this I stand up go to work play a round table soccer and then start to work start Visual Studio Code and write the code I thought about yesterday hope that it runs, but it shows you just a few error messages start debugging then notice that it’s already time to eat something and that I am hungry, eat something and find finally after your lunch the silly error I made think about new implementation and better ways to solve something and then it is already time to go, so you go to the strandbad to swim a round and then drive home. Something like this, my daily routine looked like. For me, I think it was a bit too chill for my taste because I like the stress of a 40-hour week especially when I only work in my holidays.
But the rest was absolutely nice, especially that here by Athena are so many people from different countries is pretty cool. For my self, I learned not many new skills, but I found out about many new Linux tools and how to find information even more efficiently.

 

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