Dr Angeliki Katsenou

Senior Research Fellow

    Leverhulme Early-Career Fellow

    1.23, 1 Cathedral Square

    University of Bristol

    Bristol BS1 5DD

    United Kingdom

    angeliki.katsenou at bristol.ac.uk

About

In 2015 joined as a Research Fellow the Visual Information Laboratory, led by Prof. David Bull, within the Department of Electrical and Electronic Engineering, University of Bristol. My main research interests include topics around the video processing pipeline: acquisition, analysis, compression, and communication. I am also interested in image and video quality, modelling the perceptual quality and experience. Another research area I am interested in is optimised parameter selection for video streaming.

News & Activities

  • Sep 2020: Invited Talk on Content-gnostic Bitrate Ladder Prediction for Adaptive Video Streaming, Förderverein Technische Fakultät, Alpen-Adria-Klagenfurt University, Austria. [slides and video]
  • Mar-Jul 2020: Organising the Encoding in the Dark Challenge in IEEE ICME 2020.
  • Jan-May 2020: Lecturing on Biomedical Imaging amd running Tutorials.
  • Jan- 2020: Technical Program Co-chair of PCS 2021.

Projects

  • 2018-2021 Leverhulme Early-Career Fellowship: Deep Video Analysis and Compression
  • 2017-2018 EPSRC Platform Grant: Video Texture Analysis
  • 2015-2017 FP7 MSCA ITN: ProVision - Perceptual Video Compression


Research Outputs


Recent Journal Papers
  1. BVI-SynTex: A Synthetic Video Texture Dataset for Video Compression and Video Quality Assessment [paper] [dataset]
    A. Katsenou, G. Dimitrov, D. Ma, and D. R. Bull, IEEE Transactions on Multimedia, accepted, 2020.

  2. Comparing VVC, HEVC and AV1 using Objective and Subjective Assessments [paper] [dataset]
    F. Zhang, A. V. Katsenou, M. Afonso, G. Dimitrov, and D. R. Bull, arXiv:2003. 10282, 2020.

  3. A Multi-Metric Approach for Block-Level Video Quality Assessment [paper]
    M. A. Papadopoulos, A. V. Katsenou, D. Agrafiotis, and D. R. Bull, Signal Processing: Image Communication, June 2019.

Recent Conference Papers
  1. 2-year Prognosis Estimation of Advanced High Grade Serous Ovarian Cancer Patients Using Machine Learning
    A. Laios, A. V. Katsenou, Y. Tan, M. Otify, R. Hutson, A. Kaufmann A, S. Munot, A. Thangavelu, D. De Jong, T. Broadhead, G. Theophilou, D. Nugent, 4th ESGO State of the Art Conference of the European Society of Gynaecological Oncology, 2020.

  2. Encoding in the Dark: an Overview [paper]
    N. Anantrasirichai, F. Zhang, A. Malyugina, P. Hill, and A. V. Katsenou, IEEE International Conference on Multimedia and Expo, London, UK, 2020.

  3. Content-gnostic Bitrate Ladder Prediction for Adaptive Streaming [paper]
    A. V. Katsenou, J. Sole and D. R. Bull, Picture Coding Symposium, Ningbo, China, 2019.


For all papers and datasets see the links below: