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

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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

ARTICONF’s paper, “Decentralized Social Media Applications as a Service: a Car-Sharing Perspective” accepted for publication at IEEE workshop on blockchain theory and applications (BRAIN 2020) in conjunction with ISCC 2020

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Authors: Anandhakumar Palanisamy, Mirsat Sefidanoski, Spiros Koulouzis, Carlos Rubia, Nishant Saurabh and Radu Prodan

Abstract: Social media applications are essential for next generation connectivity. Today, social media are centralized platforms with a single proprietary organization controlling the network and posing critical trust and governance issues over the created and propagated content. The ARTICONF project funded by the European Union’s Horizon 2020 program researches a decentralized social media platform based on a novel set of trustworthy, resilient and globally sustainable tools to fulfil the privacy, robustness and autonomy-related promises that proprietary social media platforms have failed to deliver so far. This paper presents the ARTICONF approach to a car-sharing use case application, as a new collaborative peer-to-peer model providing an alternative solution to private car ownership. We describe a prototype implementation of the car-sharing social media application and illustrate through real snapshots how the different ARTICONF tools support it in a simulated scenario.

Link: https://sites.google.com/view/brain-2020/

Natalia Sokolova

Paper “Pixel-Based Iris and Pupil Segmentation in Cataract Surgery Videos Using Mask R-CNN” was accepted at the workshop of the International Symposium on Biomedical Imaging

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Authors: Natalia Sokolova, Mario Taschwer, Stephanie Sarny, Doris Putzgruber-Adamitsch and Klaus Schoeffmann

Abstract: Automatically detecting clinically relevant events in surgery video recordings is becoming increasingly important for documentary, educational, and scientific purposes in the medical domain. From a medical image analysis perspective, such events need to be treated individually and associated with specific visible objects or regions. In the field of cataract surgery (lens replacement in the human eye), pupil reaction (dilation or restriction) during surgery may lead to complications and hence represents a clinically relevant event. Its detection requires automatic segmentation and measurement of pupil and iris in recorded video frames. In this work, we contribute to research on pupil and iris segmentation methods by (1) providing a dataset of 82 annotated images for training and evaluating suitable machine learning algorithms, and (2) applying the Mask R-CNN algorithm to this problem, which – in contrast to existing techniques for pupil segmentation – predicts free-form pixel-accurate segmentation masks for iris and pupil.

The proposed approach achieves consistent high segmentation accuracies on several metrics while delivering an acceptable prediction efficiency, establishing a promising basis for further segmentation and event detection approaches on eye surgery videos.

Link: http://2020.biomedicalimaging.org/

Hadi Amirpour awarded the Best Engagement Award at ACM MMSys 2020

This year’s ACM MMSys was held as a fully virtual/online event and Slido was used for asking questions about keynotes and presentations including offline discussions with presenters. The interaction report provides some interesting key insights including the word cloud below which provides an overview of this year’s discussion items. Although ACM MMSys 2020 is over, everyone is welcome joining the MMSys Slack workspace where the discussion will continue until ACM MMSys 2021 (available soon!) and hopefully beyond.

Roland Matha

Excellence badge for Roland Mathá et al. recently published IEEE TPDS paper

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The IEEE Transactions on Parallel and Distributed Systems (TPDS) paper “Simplified Workflow Simulation on Clouds based on Computation and Communication Noisiness”, published by Roland Mathá and Prof. Radu Prodan et al. got awarded the Code Reviewed Reproducibility EXCELLENCE Badge.