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Farzad Tashtarian <[log in to unmask]>
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Farzad Tashtarian <[log in to unmask]>
Tue, 28 Jun 2022 00:03:07 +0200
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The submission deadline for the ALIS 2022 workshop has been extended to 
July 8, 2022.

CALL FOR PAPERS Workshop on Artificial Intelligence for Live Video 
Streaming (ALIS2022)

colocated with ACM Multimedia 2022
10 – 14 October 2022, Lisbon, Portugal.
Delivering video content from a video server to viewers over the 
Internet is time-consuming in the streaming workflow and has to be 
handled to offer an uninterrupted streaming experience. The delay is 
particularly problematic for live streaming. Some streaming-based 
applications such as virtual events, online learning, webinars, and 
all-hands meetings require low latency for their operation. Video 
streaming is ubiquitous in a plethora of applications, devices, and 
fields. Delivering high Quality of Experience (QoE) to the streaming 
viewers is of crucial importance, while the requirement to process a 
large amount of data in order to satisfy such QoE cannot be handled with 
human-constrained possibilities. Artificial Intelligence (AI) and 
Machine Learning (ML) techniques can be leveraged to calculate expected 
network data rates, predict requested video contents and thus, perform 
content-aware encoding, predict flash crowd formation that impacts the 
overall network traffic, enable personalized content recommendations, 
understand a user’s viewing behavior, and enable more informed video 
caching decisions, and in several other ways. The first workshop on 
Artificial Intelligence for Video Streaming (ALIS2022) aims to bring 
together researchers and developers to satisfy the data-intensive 
processing requirements and QoE challenges of live video streaming 
applications through leveraging AI-based approaches. We warmly invite 
the submission of original, previously unpublished papers addressing key 
issues in this area, but not limited to:

  * AI-based resource allocation for live streaming
  * Using AI/ML techniques for optimizing Interactive Streaming and
    User-Generated Content
  * The tradeoff between QoE enhancement and network overhead: AI
  * Using AI/ML at the network edge and the cloud for supporting video
  * AI/ML-enabled caching of video chunks
  * Experience and lessons learned by deploying AI/ML algorithms for
    large-scale network-assisted video streaming
  * Design, analysis, and evaluation of AI-based Adaptive Bitrate (ABR)
    algorithms for video streaming
  * Network aspects in video streaming: cloud computing, virtualization
    techniques, network control, and management, including SDN, NFV, and
    network programmability
  * AI/ML-based solutions for supporting streaming applications
    high-speed user mobility
  * Analysis, modeling, and experimentation of  WebRTC, Low-Latency
    DASH, and Low-Latency CMAF for DASH
  * Reproducible research in adaptive video streaming: datasets,
    evaluation methods, benchmarking, standardization efforts,
    open-source tools
  * AI/ML-based techniques for live streaming in 5G and 6G networks
  * AI/ML-based techniques for improving infotainment QoE in automotive


  * Submission deadline (extended): July 8,  2022, 23:59 AoE (click here
    <> for a new submission))
  * Notifications of acceptance: 29 July 2022
  * Camera-ready submission: 21 August 2022


  * Farzad Tashtarian, Alpen-Adria-Universität Klagenfurt, Austria
  * Eirini Liotou, Institute of Communication & Computer Systems (ICCS),
    Athens, Greece
  * Mohsen Amini Salehi, University of Louisiana, USA
  * Christian Timmerer, Alpen-Adria-Universität Klagenfurt, Austria

Keynote Speech

  * The workshop keynote speech will be delivered by Prof. Amr Rizk.

Any questions regarding submission issues should be directed to 
[log in to unmask]

Dr. Farzad Tashtarian,
Post-Doctoral Researcher at ITEC,
Alpen-Adria-Universität Klagenfurt, Austria



[log in to unmask]

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