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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Hybrid P2P-CDN Architecture for Live Video Streaming: An Online Learning Approach

IEEE Global Communications Conference (GLOBECOM)

December 4-8, 2022 |Rio de Janeiro, Brazil

[PDF][Slides]

Reza Farahani (Alpen-Adria-Universität Klagenfurt, Austria), Abdelhak Bentaleb (National University of Singapore, Singapore), Ekrem Cetinkaya (Alpen-Adria-Universität Klagenfurt, Austria), Christian Timmerer (Alpen-Adria-Universität Klagenfurt, Austria), Roger Zimmermann (National University of Singapore, Singapore), and Hermann Hellwagner (Alpen-Adria-Universität Klagenfurt, Austria)

Abstract: a cost-effective, scalable, and flexible architecture that supports low latency and high-quality live video streaming is still a challenge for Over-The-Top (OTT) service providers. To cope with this issue, this paper leverages Peer-to-Peer (P2P), Content Delivery Network (CDN), edge computing, Network Function Virtualization (NFV), and distributed video transcoding paradigms to introduce a hybRId P2P-CDN arcHiTecture for livE video stReaming (RICHTER). We first introduce RICHTER’s multi-layer architecture and design an action tree that considers all feasible resources provided by peers, edge, and CDN servers for serving peer requests with minimum latency and maximum quality. We then formulate the problem as an optimization model executed at the edge of the network. We present an Online Learning (OL) approach that leverages an unsupervised Self Organizing Map (SOM) to (i) alleviate the time complexity issue of the optimization model and (ii) make it a suitable solution for large-scale scenarios by enabling decisions for groups of requests instead of for single requests. Finally, we implement the RICHTER framework, conduct our experiments on a large-scale cloud-based testbed including 350 HAS players, and compare its effectiveness with baseline systems. The experimental results illustrate that RICHTER outperforms baseline schemes in terms of users’ Quality of Experience (QoE), latency, and network utilization, by at least 59%, 39%, and 70%, respectively.

Index Terms—HAS; Edge Computing; NFV; CDN; P2P; Low Latency; QoE; Video Transcoding; Online Learning.

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Between Two and Six? Towards Correct Estimation of JND Step Sizes for VMAF-based Bitrate Laddering

 14th International Conference on Quality of Multimedia Experience (QoMEX)

September 5-7, 2022 | Lippstadt, Germany

[PDF][Poster]

Hadi Amirpour (Alpen-Adria-Universität Klagenfurt)Raimund Schatz (AIT Austrian Institute of Technology, Austria)and Christian Timmerer (Alpen-Adria-Universität Klagenfurt)

Abstract:

We currently witness the rapidly growing importance of intelligent video streaming quality optimization and reduction of video delivery costs. Per-Title encoding, in contrast to a fixed bitrate ladder, shows significant promise to deliver higher quality video streams by addressing the trade-off between compression efficiency and video characteristics such as resolution and frame rate.
Selecting encodings with noticeable quality differences in between prevents the construction of an inefficient bitrate ladder that suffers from too similar quality representations.
In this respect, the VMAF metric represents a promising foundation for bitrate laddering, as it currently yields the highest video quality prediction performance. However, the minimum noticeable quality difference, referred as to just-noticeable-difference (JND), has not been properly validated for VMAF yet, with existing sources proposing highly diverse ΔVMAF step sizes ranging from two to six.

 

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FuRA: Fully Random Access Light Field Image Compression

10th European Workshop on Visual Information Processing (EUVIP)

September 11-14, 2022 | Lisbon, Portugal

[PDF]

Hadi Amirpour (Alpen-Adria-Universität Klagenfurt),   Christine Guillemot (INRIA, France)and Christian Timmerer (Alpen-Adria-Universität Klagenfurt)

Abstract:

Light fields are typically represented by multi-view images and enable post-capture
actions such as refocusing and perspective shift. To compress a light field image, its view images are typically converted into a pseudo video sequence (PVS) and the generated PVS is compressed using a video codec. However, when using the inter-coding tool of a video codec to exploit the redundancy among view images, the possibility to randomly access any view image is lost. On the other hand, when video codecs independently encode view images using the intra-coding tool, random access to view images is enabled, however, at the expense of a significant drop in the compression efficiency. To address this trade-off, we propose to use neural representations to represent 4D light fields. For each light field, a multi-layer perceptron (MLP) is trained to map the light field four dimensions to the color space, thus enabling random access even to pixels. To achieve higher compression efficiency, neural network compression techniques are deployed. The proposed method outperforms the compression efficiency of HEVC inter-coding, while providing random access to view images and even pixel values.

 

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Low Latency Live Streaming Implementation in DASH and HLS

ACM Multimedia Conference – OSS Track

10-14 October 2022 | Lisbon, Portugal

[PDF]

Abdelhak Bentaleb (National University of Singapore), Zhengdao Zhan (National University of Singapore), Farzad Tashtarian (AAU, Austria), May Lim (National University of Singapore), Saad Harous (University of Sharjah), Christian Timmerer (AAU, Austria), Hermann Hellwagner (AAU, Austria), and Roger Zimmermann (National University of Singapore)

Low latency live streaming over HTTP using Dynamic Adaptive Streaming over HTTP (LL-DASH) and HTTP Live Streaming} (LL-HLS) has emerged as a new way to deliver live content with respectable video quality and short end-to-end latency. Satisfying these requirements while maintaining viewer experience in practice is challenging, and adopting conventional adaptive bitrate (ABR) schemes directly to do so will not work. Therefore, recent solutions including LoL$^+$, L2A, Stallion, and Llama re-think conventional ABR schemes to support low-latency scenarios. These solutions have been integrated with dash.js  that support LL-DASH. However, their performance in LL-HLS remains in question. To bridge this gap, we implement and integrate existing LL-DASH ABR schemes in the hls.js video player which supports LL-HLS.
Moreover, a series of real-world trace-driven experiments have been conducted to check their efficiency under various network conditions including a comparison with results achieved for LL-DASH in dash.js.

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Hermann Hellwagner in a BITMOVIN Webinar featuring ATHENA

Latest Edge Computing Innovations for Video Streaming (ft. ATHENA)

Webinar Recording

14th June 2022

Video streaming is not for online video providers alone. Telco providers are equal players in the game of adaptive video streaming, but to stand out, there is a constant demand for innovations at the edge.

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Detection and Localization of Video Transcoding From AVC to HEVC Based on Deep Representations of Decoded Frames and PU Maps

[PDF]

Haichao Yao (Beijing Jiaotong University), Rongrong Ni (Beijing Jiaotong University), Hadi Amirpour (Alpen-Adria-Universität Klagenfurt), Christian Timmerer (Alpen-Adria-Universität Klagenfurt)Yao Zhao (Beijing Jiaotong University).

Abstract: In general, manipulated videos will eventually undergo recompression. Video transcoding will occur when the standard of recompression is different from the prior standard. Therefore, as a special sign of recompression, video transcoding can also be considered evidence of forgery in video forensics. In this paper, we focus on the detection and localization of video transcoding from AVC to HEVC (AVC-HEVC). There are two probable cases of AVC-HEVC transcoding – whole video transcoding and partial frame transcoding. However, the existing forensic methods only consider the detection of whole video transcoding, and they do not consider partial frame transcoding localization. In view of this, we propose a framewise scheme based on a convolutional neural network. First, we analyze that the essential difference between AVC-HEVC and HEVC is reflected in the high-frequency components of decoded frames. Then, the partition and location information of prediction units (PUs) are introduced to generate frame-level PU maps to make full use of the local artifacts of PUs. Finally, taking the decoded frames and PU maps as inputs, a dual-path network including specific convolutional modules and an adaptive fusion module is proposed. Through it, the artifacts on a single frame can be better extracted, and the transcoded frames can be detected and localized. Coupled with a simple voting strategy, the results of whole transcoding detection can be easily obtained. A large number of experiments are conducted to verify the performances. The results show that the proposed scheme outperforms or rivals the state-of-the-art methods in AVC-HEVC transcoding detection and localization.

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