Paper accepted: LiDeR: Lightweight Dense Residual Network for Video Super-Resolution on Mobile Devices

IEEE 14th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP 2022)

June 26-29, 2022 | Nafplio, Greece

Conference Website

[Video]

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

 

Abstract: Video is now an essential part of the Internet. The increasing popularity of video streaming on mobile devices and the improvement in mobile displays brought together challenges to meet user expectations. Advancements in deep neural networks have seen successful applications on several computer vision tasks such as super-resolution (SR). Although DNN-based SR methods significantly improve over traditional methods, their computational complexity makes them challenging to apply on devices with limited power, such as smartphones. However, with the improvement in mobile hardware, especially GPUs, it is now possible to use DNN based solutions, though existing DNN based SR solutions are still too complex. This paper proposes LiDeR, a lightweight video SR network specifically tailored toward mobile devices. Experimental results show that LiDeR can achieve competitive SR performance with state-of-the-art networks while improving the execution speed significantly, i.e., 267 % for X4 upscaling and 353 % for X2 upscaling compared to ESPCN.

Keywords: Super-resolution, Mobile machine learning, Video super-resolution.

 

Paper Accepted @ The Journal of Supercomputing

Title: An Elastic and Traffic-Aware Scheduler for Distributed Data Stream Processing in Heterogeneous Clusters

Authors: Hamid Hadian, Mohammadreza Farrokh, Mohsen Sharifi, and Ali Jafari

Abstract:

Existing Data Stream Processing (DSP) systems perform poorly while encountering heavy workloads, particularly on clustered set of (heterogeneous) computers. Elasticity and changing application parallelism degree can limit the performance degradation in the face of varying workloads that negatively impact the overall application response time. Elasticity can be achieved by operator scaling, i.e., by replication and relocation of operators at runtime. However, scaling decisions at runtime is challenging, since it first increases the overall communication overhead between operators and secondly changes any initial scheduling that could lead to a non-optimal scheduling plan. In this paper, we investigate the problem of elasticity and scaling decisions and propose a DSP system called ER-Storm. To curb communication overhead, we propose a new 3-step mechanism for replication and relocation of operators upon detecting a bottleneck operator that overutilizes a worker node. The other challenge is to select the proper worker nodes to host relocated operators. By discretizing the input workload, we model the relocation of operators between worker nodes at runtime through a scalable Markov Decision Process (MDP) and use a model-free notion of reinforcement learning (Q-Learning) to find optimal solutions. We have implemented our propositions on the Apache Storm version 2.1.0. Our experimental results show that ER-Storm reduces the average topology response time by 20 to 60 percent based on the rate of input workload (low or high) compared to the R-Storm scheduler and the Online-Scheduler of Storm.

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

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

IEEE Transactions on Multimedia

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).

Hadi
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Hadi Amirpour to give a talk at Fraunhofer FOKUS MWS

Video Encoding Optimizations for Live Video Streaming

FOKUS Media Web Symposium

20th – 24th June 2022 | Berlin, Germany

 

Abstract: Live video streaming is expected to become mainstream in the fifth-generation (5G) mobile networks. Optimizing video encoding for live video streaming is challenging due to the latency introduced by any optimization method. In this talk, we introduce low-latency video optimization methods that are utilized to improve the quality of video encodings by predicting optimized encoding parameters.

Hadi Amirpour is a postdoc research fellow at ATHENA  directed by Prof. Christian Timmerer. 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 appointed co-chair of Task Force 7 (TF7) Immersive Media Experience (IMEx) at the 15th Qualinet meeting. 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 experience, emerging 3D imaging technology, and medical image analysis.

Hadi
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IEEE Transactions on Multimedia: Detection and Localization of Video Transcoding From AVC to HEVC Based on Deep Representations of Decoded Frames and PU Maps

Authors: 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).

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Radu Prodan is Guest Advisor and Content Acquisition Editor of the Open Research Europe, the European Commission’s fully open access publishing platform.

https://open-research-europe.ec.europa.eu/collections/cloud-based-technologies/about

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Paper Accepted @ 25th IEEE Flagship International Conference on Intelligent Transportation Systems

Results of collaborative work in the ADAPT between Austira (FFG) and China (CAS) accteped at flagship conference of IEEE Intelligent Transportation Systems Society

Title: Hybrid On/Off Blockchain Approach for Vehicle Data Management, Processing and Visualization Exemplified by the ADAPT Platform

Authors: Aso Validi, Vladislav Kashansky, Jihed Khiari, Hamid Hadian, Radu Pordan, Juanjuan Li, Fei-Yue Wang, Cristina Olaverri-Monreal

Abstract: Hybrid on/off-blockchain vehicle data management approaches have received a lot of attention in recent years. However, there are various technical challenges remained to deal with. In this paper we relied on real-world data from Austria to investigate the effects of connectivity on the transport of personal protective equipment. We proposed a three-step mechanism to process, simulate, and store/visualize aggregated vehicle datasets together with a formal pipeline process workflow model. To this end, we implemented a hybrid blockchain platform based on the hyperledger fabric and Gluster file systems. The obtained results demonstrated efficiency and stability for both hyperledger fabric and gluster file system, ability of the both on/off-blockchain mechanisms to meet the platform’s quality of service requirements.

ATHENA at ACM MMSys Conference 2022

The 13th ACM Multimedia Systems Conference MMSys’22

14th – 17th June 2022 | Athlone, Ireland.

Conference Website

The ACM Multimedia Systems Conference (MMSys) provides a forum for researchers to present and share their latest research findings in multimedia systems. While research about specific aspects of multimedia systems is regularly published in the various proceedings and transactions of the networking, operating systems, real-time systems, databases, mobile computing, distributed systems, computer vision, and middleware communities, MMSys aims to cut across these domains in the context of multimedia data types.

This year, MMSys hosted around 150 on-site participants from academia and industry. Five ATHENA members travelled to Athlone, Ireland, to present four papers by Reza Farahani, Babak Taraghi, and Vignesh V Menon in two tracks, i.e., Open Dataset & Software Track and Demo & Industry Track.

Moreover, two presentations in Mentoring & Postdoc Networking event by ATHENA postdocs:

  • Hadi Amirpour,  “Video Encoding Optimization for Live Video Streaming” (pdf)

  • Farzad Tashtarian, “QoE Optimization in Live Streaming” (pdf)

 

ACSD’22: The Power in Your Pocket: Boosting Video Quality with Super-Resolution on Mobile Devices

We presented the poster “The Power in Your Pocket: Boosting Video Quality with Super-Resolution on Mobile Devices” at the Austrian Computer Science Day 2022 conference. The poster summarizes research about improving the visual quality of video streaming on mobile devices by utilizing deep neural network-based enhancement techniques.

Here is the list of papers that we cover in the poster:

  1. Super-resolution Based Bitrate Adaptation for HTTP Adaptive Streaming for Mobile Devices

  2. MoViDNN: A Mobile Platform for Evaluating Video Quality Enhancement with Deep Neural Networks

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A Webbing Journey @ A1 Austria eSports Festival 2022

On Saturday (June 18, 2022), Sebastian Uitz presented his game “A Webbing Journey” with his partner Manuel Santner at the A1 Austria eSports Festival in the Austria Center Vienna. The game didn’t fit into the Esports-themed event, but the 2 PCs prepared to play the game were constantly used by players of all ages. Especially the target audience (children 8-12) had so much fun, and the parents had to wait until the kids were done playing. The event was a great success as it was the biggest play session yet and resulted in tons of feedback that will be implemented and bugs that will be fixed until the next event.